Collaborative Arrival Planning: Data Sharing and User Preference Tools
NASA Technical Reports Server (NTRS)
Zelenka, Richard E.; Edwards, Thomas A. (Technical Monitor)
1998-01-01
Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.
Real-time stress monitoring of highway bridges with a secured wireless sensor network.
DOT National Transportation Integrated Search
2011-12-01
"This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...
Road Traffic Anomaly Detection via Collaborative Path Inference from GPS Snippets
Wang, Hongtao; Wen, Hui; Yi, Feng; Zhu, Hongsong; Sun, Limin
2017-01-01
Road traffic anomaly denotes a road segment that is anomalous in terms of traffic flow of vehicles. Detecting road traffic anomalies from GPS (Global Position System) snippets data is becoming critical in urban computing since they often suggest underlying events. However, the noisy and sparse nature of GPS snippets data have ushered multiple problems, which have prompted the detection of road traffic anomalies to be very challenging. To address these issues, we propose a two-stage solution which consists of two components: a Collaborative Path Inference (CPI) model and a Road Anomaly Test (RAT) model. CPI model performs path inference incorporating both static and dynamic features into a Conditional Random Field (CRF). Dynamic context features are learned collaboratively from large GPS snippets via a tensor decomposition technique. Then RAT calculates the anomalous degree for each road segment from the inferred fine-grained trajectories in given time intervals. We evaluated our method using a large scale real world dataset, which includes one-month GPS location data from more than eight thousand taxicabs in Beijing. The evaluation results show the advantages of our method beyond other baseline techniques. PMID:28282948
ATM: The Key To Harnessing the Power of Networked Multimedia.
ERIC Educational Resources Information Center
Gross, Rod
1996-01-01
ATM (Asynchronous Transfer Mode) network technology handles the real-time continuous traffic flow necessary to support desktop multimedia applications. Describes network applications already used: desktop video collaboration, distance learning, and broadcasting video delivery. Examines the architecture of ATM technology, video delivery and sound…
Al-Shargabi, Mohammed A; Shaikh, Asadullah; Ismail, Abdulsamad S
2016-01-01
Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.
Al-Shargabi, Mohammed A.; Ismail, Abdulsamad S.
2016-01-01
Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively. PMID:27583557
Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations
NASA Technical Reports Server (NTRS)
Sharma, Shivanjli; Fergus, John
2017-01-01
To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.
Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations
NASA Technical Reports Server (NTRS)
Sharma, Shivanjli; Fergus, John
2017-01-01
A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.
A Sarsa(λ)-based control model for real-time traffic light coordination.
Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei
2014-01-01
Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.
Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio
2016-12-29
One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps' generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.
Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio
2016-01-01
One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work. PMID:28036065
Near real-time traffic routing
NASA Technical Reports Server (NTRS)
Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)
2012-01-01
A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.
DOT National Transportation Integrated Search
2003-07-01
Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...
Fast packet switching algorithms for dynamic resource control over ATM networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tsang, R.P.; Keattihananant, P.; Chang, T.
1996-12-01
Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less
A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination
Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei
2014-01-01
Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183
Development of decision support systems for real-time freeway traffic routing : volume II.
DOT National Transportation Integrated Search
1998-01-01
Real-time traffic flow routing is a promising approach to alleviating congestion. Existing approaches to developing real-time routing strategies, however, have limitations. This study explored the potential for using case-based reasoning (CBR), an em...
Real-time traffic sign recognition based on a general purpose GPU and deep-learning.
Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran
2017-01-01
We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).
DOT National Transportation Integrated Search
2011-07-11
This report presents a prototype of a secure, dependable, real-time weather-responsive traffic signal system. The prototype executes two tasks: 1) accesses weather information that provides near real-time atmospheric and pavement surface condition ob...
Adaptive route choice modeling in uncertain traffic networks with real-time information.
DOT National Transportation Integrated Search
2013-03-01
The objective of the research is to study travelers' route choice behavior in uncertain traffic networks : with real-time information. The research is motivated by two observations of the traffic system: 1) : the system is inherently uncertain with r...
Real-time traffic sign recognition based on a general purpose GPU and deep-learning
Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran
2017-01-01
We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). PMID:28264011
Evaluation of Traffic Information and Prediction System (TIPS) as work zone traffic control.
DOT National Transportation Integrated Search
2004-03-01
As part of a pavement rehabilitation project on I-64, the Traffic Information and Prediction System (TIPS) was installed as a a means of providing real-time data for motorists in advance and through the work zone. This system collects real-time data ...
DOT National Transportation Integrated Search
2001-09-01
RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchang...
Predicting reduced visibility related crashes on freeways using real-time traffic flow data.
Hassan, Hany M; Abdel-Aty, Mohamed A
2013-06-01
The main objective of this paper is to investigate whether real-time traffic flow data, collected from loop detectors and radar sensors on freeways, can be used to predict crashes occurring at reduced visibility conditions. In addition, it examines the difference between significant factors associated with reduced visibility related crashes to those factors correlated with crashes occurring at clear visibility conditions. Random Forests and matched case-control logistic regression models were estimated. The findings indicated that real-time traffic variables can be used to predict visibility related crashes on freeways. The results showed that about 69% of reduced visibility related crashes were correctly identified. The results also indicated that traffic flow variables leading to visibility related crashes are slightly different from those variables leading to clear visibility crashes. Using time slices 5-15 minutes before crashes might provide an opportunity for the appropriate traffic management centers for a proactive intervention to reduce crash risk in real-time. Copyright © 2013 Elsevier Ltd. All rights reserved.
Caselli, Federico; Corradi, Antonio
2018-01-01
The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%). PMID:29522427
Dynamics of traffic flow with real-time traffic information
NASA Astrophysics Data System (ADS)
Yokoya, Yasushi
2004-01-01
We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.
A video-based real-time adaptive vehicle-counting system for urban roads.
Liu, Fei; Zeng, Zhiyuan; Jiang, Rong
2017-01-01
In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.
A video-based real-time adaptive vehicle-counting system for urban roads
2017-01-01
In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984
Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research
Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi
2016-01-01
The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637
The Traffic Management Advisor
NASA Technical Reports Server (NTRS)
Nedell, William; Erzberger, Heinz; Neuman, Frank
1990-01-01
The traffic management advisor (TMA) is comprised of algorithms, a graphical interface, and interactive tools for controlling the flow of air traffic into the terminal area. The primary algorithm incorporated in it is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 n.m. from touchdown. A unique feature of the TMA is its graphical interface that allows the traffic manager to modify the computer-generated schedules for specific aircraft while allowing the automatic scheduler to continue generating schedules for all other aircraft. The graphical interface also provides convenient methods for monitoring the traffic flow and changing scheduling parameters during real-time operation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Franzese, Oscar; Zhang, Li; Mahmoud, Anas M.
There are many instances in which it is possible to plan ahead for an emergency evacuation (e.g., an explosion at a chemical processing facility). For those cases, if an accident (or an attack) were to happen, then the best evacuation plan for the prevailing network and weather conditions would be deployed. In other cases (e.g., the derailment of a train transporting hazardous materials), there may not be any previously developed plan to be implemented and decisions must be made ad-hoc on how to proceed with an emergency evacuation. In both situations, the availability of real-time traffic information plays a criticalmore » role in the management of the evacuation operations. To improve public safety during a vehicular emergency evacuation it is necessary to detect losses of road capacity (due to incidents, for example) as early as possible. Once these bottlenecks are identified, re-routing strategies must be determined in real-time and deployed in the field to help dissipate the congestion and increase the efficiency of the evacuation. Due to cost constraints, only large urban areas have traffic sensor deployments that permit access to some sort of real-time traffic information; any evacuation taking place in any other areas of the country would have to proceed without real-time traffic information. The latter was the focus of this SERRI/DHS (Southeast Region Research Initiative/Department of Homeland Security) sponsored project. That is, the main objective on the project was to improve the operations during a vehicular emergency evacuation anywhere by using newly developed real-time traffic-information-gathering technologies to assess traffic conditions and therefore to potentially detect incidents on the main evacuation routes. Phase A of the project consisted in the development and testing of a prototype system composed of sensors that are engineered in such a way that they can be rapidly deployed in the field where and when they are needed. Each one of these sensors is also equipped with their own power supply and a GPS (Global Positioning System) device to auto-determine its spatial location on the transportation network under surveillance. The system is capable of assessing traffic parameters by identifying and re-identifying vehicles in the traffic stream as those vehicles pass over the sensors. The system of sensors transmits, through wireless communication, real-time traffic information (travel time and other parameters) to a command and control center via an NTCIP (National Transportation Communication for ITS Protocol) -compatible interface. As an alternative, an existing NTCIP-compatible system accepts the real-time traffic information mentioned and broadcasts the traffic information to emergency managers, the media and the public via the existing channels. A series of tests, both in a controlled environment and on the field, were conducted to study the feasibility of rapidly deploying the system of traffic sensors and to assess its ability to provide real-time traffic information during an emergency evacuation. The results of these tests indicated that the prototype sensors are reliable and accurate for the type of application that is the focus of this project.« less
Collaborative Aviation Weather Statement - An Impact-based Decision Support Tool
NASA Astrophysics Data System (ADS)
Blondin, Debra
2016-04-01
Historically, convection causes the highest number of air traffic constraints on the United States National Air Space (NAS). Increased NAS predictability allows traffic flow managers to more effectively initiate, amend or terminate planned or active traffic management initiatives, resulting in more efficient use of available airspace. A Collaborative Aviation Weather Statement (CAWS) is an impact-based decision support tool used for the timely delivery of high-confidence, high-relevance aviation convective weather forecasts to air traffic managers. The CAWS is a graphical and textual forecast produced by a collaborative team of meteorologists from the Aviation Weather Center (AWC), Center Weather Service Units, and airlines to bring attention to high impact areas of thunderstorms. The CAWS addresses thunderstorm initiation or movement into the airports having the highest volume of traffic or into traffic sensitive jet routes. These statements are assessed by planners at the Federal Aviation Administration's (FAA) Air Route Traffic Control Centers and are used for planning traffic management initiatives to balance air traffic flow across the United States. The FAA and the airline industry use the CAWS to plan, manage, and execute operations in the NAS, thereby improving the system efficiency and safety and also saving dollars for industry and the traveling public.
Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents
NASA Astrophysics Data System (ADS)
Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui
2015-09-01
The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.
Transportation Energy Futures (TEF) Data and Sources
|agency|4-d|gis|geographic information systems?|municipal|neighborhood|urban density|municipal |carsharing|marketing|real-time|traffic information|eco-driving|idle)$ ^(vmt|vehicle miles traveled|reduction drive|eco-driving|congestion|commute|telework|alternative work|parking|real-time|traffic information
DOT National Transportation Integrated Search
2006-04-01
The objective of this part of the research study was to select and acquire a mobile traffic counter capable of providing traffic flow and average speed data in intervals of time no greater than 15 minutes and transmit the data back to a central locat...
Traffic analysis and control using image processing
NASA Astrophysics Data System (ADS)
Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.
2017-11-01
This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.
Tan, Tan-Hsu; Gochoo, Munkhjargal; Chen, Yung-Fu; Hu, Jin-Jia; Chiang, John Y.; Chang, Ching-Su; Lee, Ming-Huei; Hsu, Yung-Nian; Hsu, Jiin-Chyr
2017-01-01
This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios. PMID:28117724
Tan, Tan-Hsu; Gochoo, Munkhjargal; Chen, Yung-Fu; Hu, Jin-Jia; Chiang, John Y; Chang, Ching-Su; Lee, Ming-Huei; Hsu, Yung-Nian; Hsu, Jiin-Chyr
2017-01-21
This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients' biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient's biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.
Proactive assessment of accident risk to improve safety on a system of freeways : [research brief].
DOT National Transportation Integrated Search
2012-05-01
As traffic safety on freeways continues to be a growing concern, much progress has been made in shifting from reactive (incident detection) to proactive (real-time crash risk assessment) traffic strategies. Reliable models that can take in real-time ...
Pedestrian Friendly Traffic Signal Control.
DOT National Transportation Integrated Search
2016-01-01
This project continues research aimed at real-time detection and use of pedestrian : traffic flow information to enhance adaptive traffic signal control in urban areas : where pedestrian traffic is substantial and must be given appropriate attention ...
Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries
NASA Astrophysics Data System (ADS)
Wang, Yu-Qing; Chu, Xing-Jian; Zhou, Chao-Fan; Yan, Bo-Wen; Jia, Bin; Fang, Chen-Hao
2018-06-01
Motivated by the previous traffic flow model considering the real-time traffic state, a modified macroscopic traffic flow model is established. The periodic boundary condition is applied to the car-following model. Besides, the traffic state factor R is defined in order to correct the real traffic conditions in a more reasonable way. It is a key step that we introduce the relaxation time as a density-dependent function and provide corresponding evolvement of traffic flow. Three different typical initial densities, namely the high density, the medium one and the low one, are intensively investigated. It can be found that the hysteresis loop exists in the proposed periodic-boundary system. Furthermore, the linear and nonlinear stability analyses are performed in order to test the robustness of the system.
NASA Technical Reports Server (NTRS)
Credeur, Leonard; Houck, Jacob A.; Capron, William R.; Lohr, Gary W.
1990-01-01
A description and results are presented of a study to measure the performance and reaction of airline flight crews, in a full workload DC-9 cockpit, flying in a real-time simulation of an air traffic control (ATC) concept called Traffic Intelligence for the Management of Efficient Runway-scheduling (TIMER). Experimental objectives were to verify earlier fast-time TIMER time-delivery precision results and obtain data for the validation or refinement of existing computer models of pilot/airborne performance. Experimental data indicated a runway threshold, interarrival-time-error standard deviation in the range of 10.4 to 14.1 seconds. Other real-time system performance parameters measured include approach speeds, response time to controller turn instructions, bank angles employed, and ATC controller message delivery-time errors.
Development and Preliminary Results of CTAS on Airline Operational Control Center Operations
NASA Technical Reports Server (NTRS)
Zelenka, Richard; Beatty, Roger; Falcone, Richard; Engelland, Shawn; Tobias, Leonard (Technical Monitor)
1998-01-01
Continued growth and expansion of air traffic and increased air carrier economic pressures have mandated greater flexibility and collaboration in air traffic management. The ability of airspace users to select their own routes, so called "free-flight", and to more actively manage their fleet operations for maximum economic advantage are receiving great attention. A first step toward greater airspace user and service provider collaboration is information sharing. In this work, arrival scheduling and airspace management data generated by the NASA/FAA Center/TRACON Automation System (CTAS) and used by the FAA service provider is shared with an airline with extensive operations within the CTAS operational domain. The design and development of a specialized airline CTAS "repeater" system is described, as well as some preliminary results of the impact and benefits of this information on the air carrier's operations. FAA controller per aircraft scheduling information, such as that provided by CTAS, has never before been shared in real-time with an airline. Expected airline benefits include improved fleet planning and arrival gate management, more informed "hold-go" decisions, and avoidance of costly aircraft diversions to alternate airports when faced with uncertain airborne arrival delays.
Development and Preliminary Results of CTAS on Airline Operational Control Center Operations
NASA Technical Reports Server (NTRS)
Zelenka, Richard; Beatty, Roger; Engelland, Shawn
2004-01-01
Continued growth and expansion of air traffic and increased air carrier economic pressures have mandated greater flexibility and collaboration in air traffic management. The ability of airspace users to select their own routes, so called "free-flight", and to more actively manage their fleet operations for maximum economic advantage are receiving great attention. A first step toward greater airspace user and service provider collaboration is information sharing. In this work, arrival scheduling and airspace management data generated by the NASA/FAA Center/TRACON Automation System (CTAS) and used by the FAA service provider is shared with an airline with extensive operations within the CTAS operational domain. The design and development of a specialized airline CTAS "repeater" system is described, as well as some preliminary results of the impact and benefits of this information on the air carrier's operations. FAA controller per aircraft scheduling information, such as that provided by CTAS, has never before been shared in real-time with an airline. Expected airline benefits include improved fleet planning and arrival gate management, more informed "hold-go decisions, and avoidance of costly aircraft diversions to alternate airports when faced with uncertain airborne arrival delays.
Chen, Feng; Chen, Suren; Ma, Xiaoxiang
2016-01-01
Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306
DOT National Transportation Integrated Search
1997-01-01
The success of Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) depends on the availability and dissemination of timely and accurate estimates of current and emerging traffic network conditions. Real-time Dy...
Xu, Chengcheng; Wang, Wei; Liu, Pan; Zhang, Fangwei
2015-01-01
This study aimed to identify the traffic flow variables contributing to crash risks under different traffic states and to develop a real-time crash risk model incorporating the varying crash mechanisms across different traffic states. The crash, traffic, and geometric data were collected on the I-880N freeway in California in 2008 and 2009. This study considered 4 different traffic states in Wu's 4-phase traffic theory. They are free fluid traffic, bunched fluid traffic, bunched congested traffic, and standing congested traffic. Several different statistical methods were used to accomplish the research objective. The preliminary analysis showed that traffic states significantly affected crash likelihood, collision type, and injury severity. Nonlinear canonical correlation analysis (NLCCA) was conducted to identify the underlying phenomena that made certain traffic states more hazardous than others. The results suggested that different traffic states were associated with various collision types and injury severities. The matching of traffic flow characteristics and crash characteristics in NLCCA revealed how traffic states affected traffic safety. The logistic regression analyses showed that the factors contributing to crash risks were quite different across various traffic states. To incorporate the varying crash mechanisms across different traffic states, random parameters logistic regression was used to develop a real-time crash risk model. Bayesian inference based on Markov chain Monte Carlo simulations was used for model estimation. The parameters of traffic flow variables in the model were allowed to vary across different traffic states. Compared with the standard logistic regression model, the proposed model significantly improved the goodness-of-fit and predictive performance. These results can promote a better understanding of the relationship between traffic flow characteristics and crash risks, which is valuable knowledge in the pursuit of improving traffic safety on freeways through the use of dynamic safety management systems.
DOT National Transportation Integrated Search
2006-04-01
In this research report, an investigation was conducted to identify a suitable traffic monitoring device for collecting traffic data during actual emergency evacuation conditions that may result from hurricanes in Louisiana. The study reviewed thorou...
Joint parameter and state estimation algorithms for real-time traffic monitoring.
DOT National Transportation Integrated Search
2013-12-01
A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Song; Wang, Yihong; Luo, Wei
In virtualized data centers, virtual disk images (VDIs) serve as the containers in virtual environment, so their access performance is critical for the overall system performance. Some distributed VDI chunk storage systems have been proposed in order to alleviate the I/O bottleneck for VM management. As the system scales up to a large number of running VMs, however, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. Here, we propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue. In comparisonmore » with the existing research, our solution is able to dynamically balance the traffic workloads in accessing VDI chunks, based on the run-time network state. Specifically, compute nodes with lightly loaded traffic will be adaptively assigned more chunk access requests from remote VMs and vice versa, which can effectively eliminate the above problem and thus improves the I/O performance of VMs. We also implement a prototype based on our ACStor design, and evaluate it by various benchmarks on a real cluster with 32 nodes and a simulated platform with 256 nodes. Experiments show that under different network traffic patterns of data centers, our solution achieves up to 2-8 performance gain on VM booting time and VM’s I/O throughput, in comparison with the other state-of-the-art approaches.« less
DOT National Transportation Integrated Search
2005-01-01
This document discusses the significant issues encountered during the development effort of integrating the Transportation Management System (OpenTMS) deployed at the VDOT Richmond District Smart Traffic Center (STC) with the real time State Police d...
Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic
NASA Astrophysics Data System (ADS)
Manogaran, Saargunawathy; Ali, Muhammad; Yusof, Kamaludin Mohamad; Suhaili, Ramdhan
2017-09-01
Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was successfully been extracted and analyzed using Open Traffic. It was observed that the congestion occurs on every major road in Kuala Lumpur and most of it owes to the offices and the economic and commercial centers during rush hours. At some roads the congestion occurs at night due to the tourism activities.
Pedestrian friendly traffic signal control : final research report.
DOT National Transportation Integrated Search
2016-01-01
This project continues research aimed at real-time detection and use of pedestrian : traffic flow information to enhance adaptive traffic signal control in urban areas : where pedestrian traffic is substantial and must be given appropriate attention ...
Composable Flexible Real-time Packet Scheduling for Networks on-Chip
2012-05-16
unclassified b . ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Copyright © 2012...words, real-time flows need to be composable. We set this as the design goal for our packet scheduling discipline developed in this paper. B . Motivating...with closest deadline is chosen to forward to the next router. B . Traffic Model We assume a traffic model for real-time flows similar to the one used
Design and implementation of a telecommunication interface for the TAATM/TCV real-time experiment
NASA Technical Reports Server (NTRS)
Nolan, J. D.
1981-01-01
The traffic situation display experiment of the terminal configured vehicle (TCV) research program requires a bidirectional data communications tie line between an computer complex. The tie line is used in a real time environment on the CYBER 175 computer by the terminal area air traffic model (TAATM) simulation program. Aircraft position data are processed by TAATM with the resultant output sent to the facility for the generation of air traffic situation displays which are transmitted to a research aircraft.
Theofilatos, Athanasios
2017-06-01
The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.
Leveraging traffic and surveillance video cameras for urban traffic.
DOT National Transportation Integrated Search
2014-12-01
The objective of this project was to investigate the use of existing video resources, such as traffic : cameras, police cameras, red light cameras, and security cameras for the long-term, real-time : collection of traffic statistics. An additional ob...
Traffic safety measures using multiple streams real time data : final report
DOT National Transportation Integrated Search
2017-01-04
Traffic crashes and accidents result from many complex factors, but at a basic level, they are conflicts : among vehicles and/or other road users. Roadway conditions, traffic signals, weather, traffic flow, : drivers' behavior and health of vehicles ...
Pan, Long; Yao, Enjian; Yang, Yang
2016-12-01
With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hybrid monitoring scheme for end-to-end performance enhancement of multicast-based real-time media
NASA Astrophysics Data System (ADS)
Park, Ju-Won; Kim, JongWon
2004-10-01
As real-time media applications based on IP multicast networks spread widely, end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) a next-generation group collaboration tool based on multi-party media services, the applicability of hybrid monitoring scheme that combines active and passive monitoring is investigated. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks both application-layer metrics (i.e., user traffic condition by analyzing RTCP packets) and system metrics. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.
Midenet, Sophie; Saunier, Nicolas; Boillot, Florence
2011-11-01
This paper proposes an original definition of the exposure to lateral collision in signalized intersections and discusses the results of a real world experiment. This exposure is defined as the duration of situations where the stream that is given the right-of-way goes through the conflict zone while road users are waiting in the cross-traffic approach. This measure, obtained from video sensors, makes it possible to compare different operating conditions such as different traffic signal strategies. The data from a real world experiment is used, where the adaptive real-time strategy CRONOS (ContRol Of Networks by Optimization of Switchovers) and a time-plan strategy with vehicle-actuated ranges alternately controlled an isolated intersection near Paris. Hourly samples with similar traffic volumes are compared and the exposure to lateral collision is different in various areas of the intersection and various traffic conditions for the two strategies. The total exposure under peak hour traffic conditions drops by roughly 5 min/h with the CRONOS strategy compared to the time-plan strategy, which occurs mostly on entry streams. The results are analyzed through the decomposition of cycles in phase sequences and recommendations are made for traffic control strategies. Copyright © 2011 Elsevier Ltd. All rights reserved.
Towards a Cloud Based Smart Traffic Management Framework
NASA Astrophysics Data System (ADS)
Rahimi, M. M.; Hakimpour, F.
2017-09-01
Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.
Large Scale Traffic Simulations
DOT National Transportation Integrated Search
1997-01-01
Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computation speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated "looping" between t...
Virtualized Traffic: reconstructing traffic flows from discrete spatiotemporal data.
Sewall, Jason; van den Berg, Jur; Lin, Ming C; Manocha, Dinesh
2011-01-01
We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatiotemporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e., the dynamic motions of multiple cars over time) between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur. We demonstrate our reconstruction technique with both synthetic and real-world input. © 2011 IEEE Published by the IEEE Computer Society
Traveling With Success, How Local Governments Use Intelligent Transportation Systems
DOT National Transportation Integrated Search
1995-01-01
ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT OR ETC/ETTM, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ELECTRONIC PAYMENTS SYSTEMS, TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, TRANSIT MANAGEM...
Self-Organized Transport System
DOT National Transportation Integrated Search
2009-09-28
This report presents the findings of the simulation model for a self-organized transport system where traffic lights communicate with neighboring traffic lights and make decisions locally to adapt to traffic conditions in real time. The model is insp...
ERIC Educational Resources Information Center
Chounta, Irene-Angelica; Avouris, Nikolaos
2016-01-01
This paper presents the integration of a real time evaluation method of collaboration quality in a monitoring application that supports teachers in class orchestration. The method is implemented as an automatic rater of collaboration quality and studied in a real time scenario of use. We argue that automatic and semi-automatic methods which…
Son, Sanghyun; Baek, Yunju
2015-01-01
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%. PMID:26295230
Son, Sanghyun; Baek, Yunju
2015-08-18
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
DOT National Transportation Integrated Search
2013-11-30
Travel time reliability information includes static data about traffic speeds or trip times that capture historic variations from day to day, and it can help individuals understand the level of variation in traffic. Unlike real-time travel time infor...
Characterization, adaptive traffic shaping, and multiplexing of real-time MPEG II video
NASA Astrophysics Data System (ADS)
Agrawal, Sanjay; Barry, Charles F.; Binnai, Vinay; Kazovsky, Leonid G.
1997-01-01
We obtain network traffic model for real-time MPEG-II encoded digital video by analyzing video stream samples from real-time encoders from NUKO Information Systems. MPEG-II sample streams include a resolution intensive movie, City of Joy, an action intensive movie, Aliens, a luminance intensive (black and white) movie, Road To Utopia, and a chrominance intensive (color) movie, Dick Tracy. From our analysis we obtain a heuristic model for the encoded video traffic which uses a 15-stage Markov process to model the I,B,P frame sequences within a group of pictures (GOP). A jointly-correlated Gaussian process is used to model the individual frame sizes. Scene change arrivals are modeled according to a gamma process. Simulations show that our MPEG-II traffic model generates, I,B,P frame sequences and frame sizes that closely match the sample MPEG-II stream traffic characteristics as they relate to latency and buffer occupancy in network queues. To achieve high multiplexing efficiency we propose a traffic shaping scheme which sets preferred 1-frame generation times among a group of encoders so as to minimize the overall variation in total offered traffic while still allowing the individual encoders to react to scene changes. Simulations show that our scheme results in multiplexing gains of up to 10% enabling us to multiplex twenty 6 Mbps MPEG-II video streams instead of 18 streams over an ATM/SONET OC3 link without latency or cell loss penalty. This scheme is due for a patent.
Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie
2018-02-01
There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.
ACStor: Optimizing Access Performance of Virtual Disk Images in Clouds
Wu, Song; Wang, Yihong; Luo, Wei; ...
2017-03-02
In virtualized data centers, virtual disk images (VDIs) serve as the containers in virtual environment, so their access performance is critical for the overall system performance. Some distributed VDI chunk storage systems have been proposed in order to alleviate the I/O bottleneck for VM management. As the system scales up to a large number of running VMs, however, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. Here, we propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue. In comparisonmore » with the existing research, our solution is able to dynamically balance the traffic workloads in accessing VDI chunks, based on the run-time network state. Specifically, compute nodes with lightly loaded traffic will be adaptively assigned more chunk access requests from remote VMs and vice versa, which can effectively eliminate the above problem and thus improves the I/O performance of VMs. We also implement a prototype based on our ACStor design, and evaluate it by various benchmarks on a real cluster with 32 nodes and a simulated platform with 256 nodes. Experiments show that under different network traffic patterns of data centers, our solution achieves up to 2-8 performance gain on VM booting time and VM’s I/O throughput, in comparison with the other state-of-the-art approaches.« less
Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor
NASA Technical Reports Server (NTRS)
Landry, Steven J.; Farley, Todd; Hoang, Ty
2005-01-01
Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.
A review of the effect of traffic and weather characteristics on road safety.
Theofilatos, Athanasios; Yannis, George
2014-11-01
Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research. Copyright © 2014 Elsevier Ltd. All rights reserved.
Real-time color/shape-based traffic signs acquisition and recognition system
NASA Astrophysics Data System (ADS)
Saponara, Sergio
2013-02-01
A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.
DOT National Transportation Integrated Search
2013-10-01
In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...
Real-Time SCADA Cyber Protection Using Compression Techniques
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lyle G. Roybal; Gordon H Rueff
2013-11-01
The Department of Energy’s Office of Electricity Delivery and Energy Reliability (DOE-OE) has a critical mission to secure the energy infrastructure from cyber attack. Through DOE-OE’s Cybersecurity for Energy Delivery Systems (CEDS) program, the Idaho National Laboratory (INL) has developed a method to detect malicious traffic on Supervisory, Control, and Data Acquisition (SCADA) network using a data compression technique. SCADA network traffic is often repetitive with only minor differences between packets. Research performed at the INL showed that SCADA network traffic has traits desirable for using compression analysis to identify abnormal network traffic. An open source implementation of a Lempel-Ziv-Welchmore » (LZW) lossless data compression algorithm was used to compress and analyze surrogate SCADA traffic. Infected SCADA traffic was found to have statistically significant differences in compression when compared against normal SCADA traffic at the packet level. The initial analyses and results are clearly able to identify malicious network traffic from normal traffic at the packet level with a very high confidence level across multiple ports and traffic streams. Statistical differentiation between infected and normal traffic level was possible using a modified data compression technique at the 99% probability level for all data analyzed. However, the conditions tested were rather limited in scope and need to be expanded into more realistic simulations of hacking events using techniques and approaches that are better representative of a real-world attack on a SCADA system. Nonetheless, the use of compression techniques to identify malicious traffic on SCADA networks in real time appears to have significant merit for infrastructure protection.« less
Real Time Data Management for Estimating Probabilities of Incidents and Near Misses
NASA Astrophysics Data System (ADS)
Stanitsas, P. D.; Stephanedes, Y. J.
2011-08-01
Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.
Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques
DOT National Transportation Integrated Search
1978-11-01
Real-time surveillance of traffic conditions on urban freeway corridors using spatially discrete presence detectors is addressed. Using a finite-dimensional (macroscopic) fluid-analog model for freeway vehicular traffic flow, an extended Kalman filte...
Traffic data collection and anonymous vehicle detection using wireless sensor networks.
DOT National Transportation Integrated Search
2012-05-01
New traffic sensing devices based on wireless sensing technologies were designed and tested. Such devices encompass a cost-effective, battery-free, and energy self-sustained architecture for real-time traffic measurement over distributed points in a ...
Active traffic management case study: phase 1 : final report.
DOT National Transportation Integrated Search
2016-03-01
This study developed a systematic approach for using data from multiple sources to provide active traffic management : solutions. The feasibility of two active traffic management solutions is analyzed in this report: ramp-metering and real-time : cra...
Nonuniform traffic spots (NUTS) in multistage interconnection networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lang, T.; Kurisaki, L.
1990-09-01
The performance of multistage interconnection networks for multiprocessors is degraded when the traffic pattern produces nonuniform congestion in the blocking switches, that is, when there exist nonuniform traffic spots. For some specific patterns the authors evaluate this degradation in performance and propose modifications to the network organization and operation to reduce the degradation. Successful modifications are the use of diverting switches and the extension of the network with additional links. The use of these modifications makes the network more effective for a larger variety of traffic patterns. The authors also consider the case in which the network carries the superpositionmore » of two types of traffic. One type is the high throughput data and instruction traffic, while the other consists of control and I/O packets which are of low throughput but have severe real-time constraints. The authors conclude that diverting switches and networks with additional links are also suitable for assuring low latency for the real-time traffic, especially when using the displacing mode.« less
Architectural impact of FDDI network on scheduling hard real-time traffic
NASA Technical Reports Server (NTRS)
Agrawal, Gopal; Chen, Baio; Zhao, Wei; Davari, Sadegh
1991-01-01
The architectural impact on guaranteeing synchronous message deadlines in FDDI (Fiber Distributed Data Interface) token ring networks is examined. The FDDI network does not have facility to support (global) priority arbitration which is a useful facility for scheduling hard real time activities. As a result, it was found that the worst case utilization of synchronous traffic in an FDDI network can be far less than that in a centralized single processor system. Nevertheless, it is proposed and analyzed that a scheduling method can guarantee deadlines of synchronous messages having traffic utilization up to 33 pct., the highest to date.
Study of Collaborative Management for Transportation Construction Project Based on BIM Technology
NASA Astrophysics Data System (ADS)
Jianhua, Liu; Genchuan, Luo; Daiquan, Liu; Wenlei, Li; Bowen, Feng
2018-03-01
Abstract. Building Information Modeling(BIM) is a building modeling technology based on the relevant information data of the construction project. It is an advanced technology and management concept, which is widely used in the whole life cycle process of planning, design, construction and operation. Based on BIM technology, transportation construction project collaborative management can have better communication through authenticity simulation and architectural visualization and can obtain the basic and real-time information such as project schedule, engineering quality, cost and environmental impact etc. The main services of highway construction management are integrated on the unified BIM platform for collaborative management to realize information intercommunication and exchange, to change the isolated situation of information in the past, and improve the level of information management. The final BIM model is integrated not only for the information management of project and the integration of preliminary documents and design drawings, but also for the automatic generation of completion data and final accounts, which covers the whole life cycle of traffic construction projects and lays a good foundation for smart highway construction.
Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network
NASA Astrophysics Data System (ADS)
Yang, Bin
2017-07-01
Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately
A wireless sensor network for urban traffic characterization and trend monitoring.
Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A
2015-10-15
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.
TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation
NASA Technical Reports Server (NTRS)
Okuniek, Nikolai; Zhu, Zhifan
2017-01-01
This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.
23 CFR 511.309 - Provisions for traffic and travel conditions reporting.
Code of Federal Regulations, 2012 CFR
2012-04-01
... requirements for traffic and travel conditions made available by real-time information programs are: (1... or less from the time the hazardous conditions, blockage, or closure is observed. (4) Travel time information. The timeliness for the availability of travel time information along limited access roadway...
Delivering real-time status and arrival information to commuter rail passengers at complex stations
DOT National Transportation Integrated Search
2003-08-01
Software was developed for calculating real-time train status in an Automated Train Information Display System (ATIDS) at NJ Transit. Interfaces were developed for passing schedules and real-time train position and routing data from a rail traffic co...
The use of real-time ground-to-air video during aeromedical response to traffic crashes.
DOT National Transportation Integrated Search
2002-01-01
Deteriorating traffic conditions and resulting safety problems on I-81 have long been a topic of concern. This, coupled with increasing traffic congestion along this largely four-lane highway, has resulted in increased crash rates. Emergency medical ...
DOT National Transportation Integrated Search
2011-10-17
"Under the aegis of Intelligent Transportation Systems (ITS), real-time traffic information provision strategies are being proposed to manage traffic congestion, alleviate the effects of incidents, enhance response efficiency after disasters, and imp...
NASA Astrophysics Data System (ADS)
Liang, Haijun; Ren, Jialong; Song, Tao
2017-05-01
Operating requirement of air traffic control system, the multi-platform real-time message-oriented middleware was studied and realized, which is composed of CDCC and CDCS. The former provides application process interface, while the latter realizes data synchronism of CDCC and data exchange. MQM, as one important part of it, provides message queue management and, encrypt and compress data during transmitting procedure. The practical system application verifies that the middleware can simplify the development of air traffic control system, enhance its stability, improve its systematic function and make it convenient for maintenance and reuse.
Data forwarding mechanism for supporting real-time services during relocations in UMTS systems
NASA Astrophysics Data System (ADS)
Cai, Wei; Liao, Xianglong; Zheng, Liang; Liu, Zehong
2004-04-01
To minimize the interruption during the handovers or relocations invoked by subscribers moving is a very critical factor to enhance the performance of the UMTS systems. We know that the 2G systems have been optimized to minimize the interruption of speech during handovers by two main technologies: one is the bi-casting for the DL traffic and the other is the fast radio resynchronization by the UE for the UL traffic. In the UMTS systems, we have also implemented lossless relocations for non real-time services with high reliability by data buffering in the source RNC and target RNC for the UE. However, the UMTS systems support four QoS classes traffic flow: conversational class, streaming class, interactive class and background class. The main distinguishing factor between these QoS classes is how delay sensitive the traffic is: Conversational and Streaming classes are mainly used to carry real-time traffic flows, like video telephony, interactive and background classes are mainly used by traditional Internet applications like WWW, E-mail and FTP. It"s essential to provide the solutions for supporting real-time services to meet the requirement for QoS in UMTS systems. Apparently, the Data buffering mechanism is not adapted to real-time services because of it"s delay may exceed the basic requirement for real-time services. Under this background, the paper discussed two data forwarding solutions for real-time services from the PS domain in the UMTS systems: packet duplication and Core Network bi-casting. The former mechanism does not require any new procedures, messages nor information elements. The later mechanism requires that the GGSN or SGSN is able to bi-cast the DL traffic to the target RNC according to the relocations involving two SGSNs or just involving one SGSN. It also implicitly shows that we need change procedures at the nodes SGSN, GGSN and RNC which are involved in the relocation procedure based on existing procedures that we have already designed if adopt the later solution. In a detail way, the paper analyzed the characteristic for these two solutions respectively, concentrated on the packet flows and the message flows in those nodes involved in relocations. Additionally, also gave out the impact on present transport technologies in the wireless communication systems. However we shall minimize the impact of evolution of transport mechanism and utilize the resource efficiently according to the general requirements for QoS in UMTS systems.
A Fast-Time Simulation Tool for Analysis of Airport Arrival Traffic
NASA Technical Reports Server (NTRS)
Erzberger, Heinz; Meyn, Larry A.; Neuman, Frank
2004-01-01
The basic objective of arrival sequencing in air traffic control automation is to match traffic demand and airport capacity while minimizing delays. The performance of an automated arrival scheduling system, such as the Traffic Management Advisor developed by NASA for the FAA, can be studied by a fast-time simulation that does not involve running expensive and time-consuming real-time simulations. The fast-time simulation models runway configurations, the characteristics of arrival traffic, deviations from predicted arrival times, as well as the arrival sequencing and scheduling algorithm. This report reviews the development of the fast-time simulation method used originally by NASA in the design of the sequencing and scheduling algorithm for the Traffic Management Advisor. The utility of this method of simulation is demonstrated by examining the effect on delays of altering arrival schedules at a hub airport.
Development of prototype decision support systems for real-time freeway traffic routing. Volume I.
DOT National Transportation Integrated Search
1998-01-01
For a traffic management system (TMS) to improve traffic flow, TMS operators must develop effective routing strategies based on the data collected by the system. The purpose of this research was to build prototype decision support systems (DSS) for t...
DOT National Transportation Integrated Search
2016-09-01
What is the incremental relevance of real-time traffic volume data for taking the pulse of the U.S. economy? Although prior research has identified a positive link between traffic volume and economic activity, there is a dearth of evidence on the rel...
DOT National Transportation Integrated Search
2010-10-25
Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...
Xie, Meiquan; Cheng, Wen; Gill, Gurdiljot Singh; Zhou, Jiao; Jia, Xudong; Choi, Simon
2018-02-17
Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR. This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model. Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime. This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.
A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring
Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.
2015-01-01
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278
2007 Ikhana Western States and Southern California Emergency UAS Fire Missions
NASA Technical Reports Server (NTRS)
Cobleigh, Brent
2008-01-01
Four demonstration and four emergency fire imaging missions completed: a) Thermal infrared imagery delivered in near real-time (5 to 15 minutes) to: 1) SoCal Emergency: FEMA, NIFC, NorthCom, California EOC; 2) Demo Flights: NIFC, Individual Fire Incident Commands. Imagery used for tactical and strategic decision making. Air Traffic Control gave excellent support. Mission plans flown in reverse. Real time requests for revisits of active fires. Added new fire during mission. Moved fire loiter points as fires moved. Real-time reroute around thunderstorm activity. Pre & Post flight telecons with FAA were held to review mission and discuss operational improvements. No issues with air traffic control during the 8 fire missions flown.
Path Flow Estimation Using Time Varying Coefficient State Space Model
NASA Astrophysics Data System (ADS)
Jou, Yow-Jen; Lan, Chien-Lun
2009-08-01
The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.
Traffic Predictive Control: Case Study and Evaluation
DOT National Transportation Integrated Search
2017-06-26
This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...
Dynamic traffic assignment : genetic algorithms approach
DOT National Transportation Integrated Search
1997-01-01
Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...
Implementation and testing of the travel time prediction system (TIPS) : final report, May 2001.
DOT National Transportation Integrated Search
2001-05-01
The Travel Time Prediction System (TIPS) is a portable automated system for predicting and displaying travel time for motorists in advance of and through freeway construction work zones, on a real-time basis. It collects real-time traffic flow data u...
DOT National Transportation Integrated Search
2001-05-01
The Travel Time Prediction System (TIPS) is a portable automated system for predicting and displaying travel time for motorists in advance of and through freeway construction work zones, on a real-time basis. It collects real-time traffic flow data u...
NASA Astrophysics Data System (ADS)
Balouchestani, Mohammadreza
2017-05-01
Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.
Agent-based Large-Scale Emergency Evacuation Using Real-Time Open Government Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Wei; Liu, Cheng; Bhaduri, Budhendra L
The open government initiatives have provided tremendous data resources for the transportation system and emergency services in urban areas. This paper proposes a traffic simulation framework using high temporal resolution demographic data and real time open government data for evacuation planning and operation. A comparison study using real-world data in Seattle, Washington is conducted to evaluate the framework accuracy and evacuation efficiency. The successful simulations of selected area prove the concept to take advantage open government data, open source data, and high resolution demographic data in emergency management domain. There are two aspects of parameters considered in this study: usermore » equilibrium (UE) conditions of traffic assignment model (simple Non-UE vs. iterative UE) and data temporal resolution (Daytime vs. Nighttime). Evacuation arrival rate, average travel time, and computation time are adopted as Measure of Effectiveness (MOE) for evacuation performance analysis. The temporal resolution of demographic data has significant impacts on urban transportation dynamics during evacuation scenarios. Better evacuation performance estimation can be approached by integrating both Non-UE and UE scenarios. The new framework shows flexibility in implementing different evacuation strategies and accuracy in evacuation performance. The use of this framework can be explored to day-to-day traffic assignment to support daily traffic operations.« less
NASA Technical Reports Server (NTRS)
Robinson, John E., III; Lee, Alan; Lai, Chok Fung
2017-01-01
This paper describes the Shadow-Mode Assessment Using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed. The SMART-NAS Test Bed is an air traffic simulation platform being developed by the National Aeronautics and Space Administration (NASA). The SMART-NAS Test Bed's core purpose is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the United States' Next Generation Air Transportation System called NextGen. The setup, configuration, coordination, and execution of realtime, human-in-the-loop air traffic management simulations are complex, tedious, time intensive, and expensive. The SMART-NAS Test Bed framework is an alternative to the current approach and will provide services throughout the simulation workflow pipeline to help alleviate these shortcomings. The principle concepts to be simulated include advanced gate-to-gate, trajectory-based operations, widespread integration of novel aircraft such as unmanned vehicles, and real-time safety assurance technologies to enable autonomous operations. To make this possible, SNTB will utilize Web-based technologies, cloud resources, and real-time, scalable, communication middleware. This paper describes the SMART-NAS Test Bed's vision, purpose, its concept of use, and the potential benefits, key capabilities, high-level requirements, architecture, software design, and usage.
Torija, Antonio J; Ruiz, Diego P
2012-10-01
Road traffic has a heavy impact on the urban sound environment, constituting the main source of noise and widely dominating its spectral composition. In this context, our research investigates the use of recorded sound spectra as input data for the development of real-time short-term road traffic flow estimation models. For this, a series of models based on the use of Multilayer Perceptron Neural Networks, multiple linear regression, and the Fisher linear discriminant were implemented to estimate road traffic flow as well as to classify it according to the composition of heavy vehicles and motorcycles/mopeds. In view of the results, the use of the 50-400 Hz and 1-2.5 kHz frequency ranges as input variables in multilayer perceptron-based models successfully estimated urban road traffic flow with an average percentage of explained variance equal to 86%, while the classification of the urban road traffic flow gave an average success rate of 96.1%. Copyright © 2012 Elsevier B.V. All rights reserved.
Effect of signals on two-route traffic system with real-time information
NASA Astrophysics Data System (ADS)
Tobita, Kazuhiro; Nagatani, Takashi
2012-12-01
We study the effect of signals on the vehicular traffic in the two-route system at the tour-time feedback strategy where the vehicles move ahead through a series of signals. The Nagel-Schreckenberg model is applied to the vehicular motion. The traffic signals are controlled by both cycle time and split. The tour times on two routes fluctuate periodically and alternately. The period increases with decreasing the split. Also, the tour time on each route varies with time by synchronizing with the density. The dependences of tour times and densities on both split and cycle time are clarified.
Baldauf, Richard; Thoma, Eben; Hays, Michael; Shores, Richard; Kinsey, John; Gullett, Brian; Kimbrough, Sue; Isakov, Vlad; Long, Thomas; Snow, Richard; Khlystov, Andrey; Weinstein, Jason; Chen, Fu-Lin; Seila, Robert; Olson, David; Gilmour, Ian; Cho, Seung-Hyun; Watkins, Nealson; Rowley, Patricia; Bang, John
2008-07-01
A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.
U27 : real-time commercial vehicle safety & security monitoring final report.
DOT National Transportation Integrated Search
2012-12-01
Accurate real-time vehicle tracking has a wide range of applications including fleet management, drug/speed/law enforcement, transportation planning, traffic safety, air quality, electronic tolling, and national security. While many alternative track...
Zhang, Binbin; Chen, Jun; Jin, Long; Deng, Weili; Zhang, Lei; Zhang, Haitao; Zhu, Minhao; Yang, Weiqing; Wang, Zhong Lin
2016-06-28
Wireless traffic volume detectors play a critical role for measuring the traffic-flow in a real-time for current Intelligent Traffic System. However, as a battery-operated electronic device, regularly replacing battery remains a great challenge, especially in the remote area and wide distribution. Here, we report a self-powered active wireless traffic volume sensor by using a rotating-disk-based hybridized nanogenerator of triboelectric nanogenerator and electromagnetic generator as the sustainable power source. Operated at a rotating rate of 1000 rpm, the device delivered an output power of 17.5 mW, corresponding to a volume power density of 55.7 W/m(3) (Pd = P/V, see Supporting Information for detailed calculation) at a loading resistance of 700 Ω. The hybridized nanogenerator was demonstrated to effectively harvest energy from wind generated by a moving vehicle through the tunnel. And the delivered power is capable of triggering a counter via a wireless transmitter for real-time monitoring the traffic volume in the tunnel. This study further expands the applications of triboelectric nanogenerators for high-performance ambient mechanical energy harvesting and as sustainable power sources for driving wireless traffic volume sensors.
NASA Astrophysics Data System (ADS)
Zhao, Fang-Ming; Jiang, Ling-Ge; He, Chen
In this paper, a channel allocation scheme is studied for overlay wireless networks to optimize connection-level QoS. The contributions of our work are threefold. First, a channel allocation strategy using both horizontal channel borrowing and vertical traffic overflowing (HCBVTO) is presented and analyzed. When all the channels in a given macrocell are used, high-mobility real-time handoff requests can borrow channels from adjacent homogeneous cells. In case that the borrowing requests fail, handoff requests may also be overflowed to heterogeneous cells, if possible. Second, high-mobility real-time service is prioritized by allowing it to preempt channels currently used by other services. And third, to meet the high QoS requirements of some services and increase the utilization of radio resources, certain services can be transformed between real-time services and non-real-time services as necessary. Simulation results demonstrate that the proposed schemes can improve system performance.
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-01-01
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-11-27
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.
Scalability Issues for Remote Sensing Infrastructure: A Case Study.
Liu, Yang; Picard, Sean; Williamson, Carey
2017-04-29
For the past decade, a team of University of Calgary researchers has operated a large "sensor Web" to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system's memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.
DOT National Transportation Integrated Search
1995-10-01
REAL-TIME TRAFFIC INFORMATION, ROUTE GUIDANCE, ROUTE PLANNING, INTELLIGENT VEHICLE INITIATIVE OR IVI ">">KEYWORDS: OPERATIONAL TESTS, TRAVTEK, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, INTELLI...
An investigation into incident duration forecasting for FleetForward
DOT National Transportation Integrated Search
2000-08-01
Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...
Minnesota : innovative choices for congestion relief.
DOT National Transportation Integrated Search
2011-01-01
Minnesota UPA projects focus on reducing traffic congestion in the I-35W corridor and in downtown Minneapolis. ITS technologies underlie many of the Minnesota UPA projects, including those centered on tolling, real-time traffic and transit informatio...
High-speed and high-fidelity system and method for collecting network traffic
Weigle, Eric H [Los Alamos, NM
2010-08-24
A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.
How to determine an optimal threshold to classify real-time crash-prone traffic conditions?
Yang, Kui; Yu, Rongjie; Wang, Xuesong; Quddus, Mohammed; Xue, Lifang
2018-08-01
One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.
Surface Operations Simulator and Scheduler (SOSS) Presentation
NASA Technical Reports Server (NTRS)
Zhu, Zhifan
2016-01-01
NASA - KAIA (Korea Agency for Infrastructure Technology Advancement) - KARI (Korea Aerospace Research Institute) collaboration surface air traffic management research has been ongoing since May 2015. In the first year collaboration, NASA's SOSS software has been transferred to KAIA and KARI teams to provide fast time simulation capability. Incheon International Airport model has been developed for SOSS.
DOT National Transportation Integrated Search
2014-05-01
As Advanced Traveler Information Systems (ATIS) are being more widely accessed by drivers, understanding drivers behavioral responses to real-time travel information through ATIS and its consequential benefits are important to the widespread deplo...
Advanced computer architecture for large-scale real-time applications.
DOT National Transportation Integrated Search
1973-04-01
Air traffic control automation is identified as a crucial problem which provides a complex, real-time computer application environment. A novel computer architecture in the form of a pipeline associative processor is conceived to achieve greater perf...
Real time freeway incident detection.
DOT National Transportation Integrated Search
2014-04-01
The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...
NASA Astrophysics Data System (ADS)
Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.
2011-06-01
For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.
Road Network State Estimation Using Random Forest Ensemble Learning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hou, Yi; Edara, Praveen; Chang, Yohan
Network-scale travel time prediction not only enables traffic management centers (TMC) to proactively implement traffic management strategies, but also allows travelers make informed decisions about route choices between various origins and destinations. In this paper, a random forest estimator was proposed to predict travel time in a network. The estimator was trained using two years of historical travel time data for a case study network in St. Louis, Missouri. Both temporal and spatial effects were considered in the modeling process. The random forest models predicted travel times accurately during both congested and uncongested traffic conditions. The computational times for themore » models were low, thus useful for real-time traffic management and traveler information applications.« less
Large-scale machine learning and evaluation platform for real-time traffic surveillance
NASA Astrophysics Data System (ADS)
Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel
2016-09-01
In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.
RHODES-ITMS-MILOS : ramp metering system test
DOT National Transportation Integrated Search
2002-04-01
The RHODES-Integrated Traffic Management System Program addresses the design and development of a real-time traffic adaptive control system for an integrated system of freeways and arterial roads. The goals of this project were to test coordinated, a...
Real-time traffic management to maximize throughput of automated vehicles.
DOT National Transportation Integrated Search
2015-03-01
In intelligent transportation systems, most of the research work has focused on lane change assistant : systems. No existing work considers minimizing the disruption of traffic flow by maximizing the number : of lane changes while eliminating the col...
Estimate benefits of crowdsourced data from social media.
DOT National Transportation Integrated Search
2014-12-01
Traffic Management Centers (TMCs) acquire, process, and integrate data in a variety of ways to support real-time operations. Crowdsourcing has been identified as one of the top trends and technologies that traffic management agencies can adapt and ta...
Video image processing to create a speed sensor
DOT National Transportation Integrated Search
1999-11-01
Image processing has been applied to traffic analysis in recent years, with different goals. In the report, a new approach is presented for extracting vehicular speed information, given a sequence of real-time traffic images. We extract moving edges ...
Intelligent Traffic Light Based on PLC Control
NASA Astrophysics Data System (ADS)
Mei, Lin; Zhang, Lijian; Wang, Lingling
2017-11-01
The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.
Chen, Feng; Chen, Suren; Ma, Xiaoxiang
2018-06-01
Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.
A Study of Synchronous versus Asynchronous Collaboration in an Online Business Writing Class
ERIC Educational Resources Information Center
Mabrito, Mark
2006-01-01
A case study examined the collaborative experiences of students in an online business writing classroom. The purpose was to examine the same groups of students working on collaborative writing assignments in both a synchronous (real-time) and an asynchronous (non-real-time) discussion forum. This study focused on examining the amount, pattern, and…
Agent-based real-time signal coordination in congested networks.
DOT National Transportation Integrated Search
2014-01-01
This study is the continuation of a previous NEXTRANS study on agent-based reinforcement : learning methods for signal coordination in congested networks. In the previous study, the : formulation of a real-time agent-based traffic signal control in o...
Sonification of network traffic flow for monitoring and situational awareness
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543
Sonification of network traffic flow for monitoring and situational awareness.
Debashi, Mohamed; Vickers, Paul
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.
Evaluating the benefits of dynamic message signs on Missouri's rural corridors.
DOT National Transportation Integrated Search
2011-12-01
Dynamic message signs (DMSs) are traffic control devices that provide real-time traveler information and are used for traffic warning, regulation, routing and management. DMSs on freeways in rural areas in southeast Missouri were evaluated. First, mo...
DOT National Transportation Integrated Search
2003-01-01
This study evaluated existing traffic signal optimization programs including Synchro,TRANSYT-7F, and genetic algorithm optimization using real-world data collected in Virginia. As a first step, a microscopic simulation model, VISSIM, was extensively ...
Demonstration of the application of traffic management center decision support tools : [summary].
DOT National Transportation Integrated Search
2013-03-01
Among the most important advances in transportation systems in recent years has been the development and implementation of intelligent transportation systems (ITS), which relies on several means of monitoring traffic flows, coupled with real-time and...
Real time driver information for congestion management.
DOT National Transportation Integrated Search
2015-07-01
Traffic demand in the U.S. has grown substantially over the past few years because of the increase in population and : urbanization in large cities. This causes traffic congestion to spread out over U.S. highways and arterials, and subsequently : lea...
Quantifying incident-induced travel delays on freeways using traffic sensor data : phase II
DOT National Transportation Integrated Search
2010-12-01
Traffic incidents cause approximately 50 percent of freeway congestion in metropolitan areas, resulting in extra travel time and fuel cost. Quantifying incident-induced delay (IID) will help people better understand the real costs of incidents, maxim...
DOT National Transportation Integrated Search
1996-08-01
KEYWORDS: : TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS : THIS DOCUMENT PRESENTS THE METHODS, ASSUMPTIONS AND PROCEDURES USED TO COLLECT THE BASELINE INFORMATION. THE DOCUMENTATION OF SYSTEMS ...
DOT National Transportation Integrated Search
2018-02-02
Traffic congestion at arterial intersections and freeway bottlenecks degrades the air quality and threatens the public health. Conventionally, air pollutants are monitored by sparsely-distributed Quality Assurance Air Monitoring Sites. Sparse mobile ...
Evaluation of the ADAPTIR System for Work Zone Traffic Control
DOT National Transportation Integrated Search
1999-11-01
The ADAPTIR system (Automated Data Acquisition and Processing of Traffic Information in Real Time) uses variable message signs (VMS) equipped with radar units, along with a software program to interpret the data, to display appropriate warning and ad...
Theofilatos, Athanasios; Yannis, George
2017-04-03
Understanding the various factors that affect accident risk is of particular concern to decision makers and researchers. The incorporation of real-time traffic and weather data constitutes a fruitful approach when analyzing accident risk. However, the vast majority of relevant research has no specific focus on vulnerable road users such as powered 2-wheelers (PTWs). Moreover, studies using data from urban roads and arterials are scarce. This study aims to add to the current knowledge by considering real-time traffic and weather data from 2 major urban arterials in the city of Athens, Greece, in order to estimate the effect of traffic, weather, and other characteristics on PTW accident involvement. Because of the high number of candidate variables, a random forest model was applied to reveal the most important variables. Then, the potentially significant variables were used as input to a Bayesian logistic regression model in order to reveal the magnitude of their effect on PTW accident involvement. The results of the analysis suggest that PTWs are more likely to be involved in multivehicle accidents than in single-vehicle accidents. It was also indicated that increased traffic flow and variations in speed have a significant influence on PTW accident involvement. On the other hand, weather characteristics were found to have no effect. The findings of this study can contribute to the understanding of accident mechanisms of PTWs and reduce PTW accident risk in urban arterials.
Managed lane operations--adjusted time of day pricing vs. near-real time dynamic pricing : summary.
DOT National Transportation Integrated Search
2012-01-01
In 2008, the Florida Department of Transportation began implementing the 95 Express, a segment of I-95 in Miami with high occupancy toll (HOT) lanes. Some vehicles use HOT lanes free, but most vehicles pay a toll based on real-time traffic conditions...
There are adverse health effects in populations living, working or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily-traveled highway. Several real-time and time-integrated sampling d...
Do alcohol excise taxes affect traffic accidents? Evidence from Estonia.
Saar, Indrek
2015-01-01
This article examines the association between alcohol excise tax rates and alcohol-related traffic accidents in Estonia. Monthly time series of traffic accidents involving drunken motor vehicle drivers from 1998 through 2013 were regressed on real average alcohol excise tax rates while controlling for changes in economic conditions and the traffic environment. Specifically, regression models with autoregressive integrated moving average (ARIMA) errors were estimated in order to deal with serial correlation in residuals. Counterfactual models were also estimated in order to check the robustness of the results, using the level of non-alcohol-related traffic accidents as a dependent variable. A statistically significant (P <.01) strong negative relationship between the real average alcohol excise tax rate and alcohol-related traffic accidents was disclosed under alternative model specifications. For instance, the regression model with ARIMA (0, 1, 1)(0, 1, 1) errors revealed that a 1-unit increase in the tax rate is associated with a 1.6% decrease in the level of accidents per 100,000 population involving drunk motor vehicle drivers. No similar association was found in the cases of counterfactual models for non-alcohol-related traffic accidents. This article indicates that the level of alcohol-related traffic accidents in Estonia has been affected by changes in real average alcohol excise taxes during the period 1998-2013. Therefore, in addition to other measures, the use of alcohol taxation is warranted as a policy instrument in tackling alcohol-related traffic accidents.
Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.
Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush
2016-08-01
This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.
A new simulation system of traffic flow based on cellular automata principle
NASA Astrophysics Data System (ADS)
Shan, Junru
2017-05-01
Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.
NASA Research on an Integrated Concept for Airport Surface Operations Management
NASA Technical Reports Server (NTRS)
Gupta, Gautam
2012-01-01
Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. There have been attempts to address the resulting inefficiencies with both strategic and tactical tools for metering departure aircraft. This presentation gives an overview of Spot And Runway Departure Advisor with Collaborative Decision Making (SARDA-CDM): an integrated strategic and tactical system for improving surface operations by metering departure aircraft. SARDA-CDM is the augmentation of ground and local controller advisories through sharing of flight movement and related operations information between airport operators, flight operators and air traffic control at the airport. The goal is to enhance the efficiency of airport surface operations by exchanging information between air traffic control and airline operators, while minimizing adverse effects on stakeholders and passengers. The presentation motivates the need for departure metering, and provides a brief background on the previous work on SARDA. Then, the concept of operations for SARDA-CDM is described. Then the preliminary results from testing the concept in a real-time automated simulation environment are described. Results indicate benefits such as reduction in taxiing delay and fuel consumption. Further, the preliminary implementation of SARDA-CDM seems robust for two minutes delay in gate push-back times.
Investigating the Effects of Traffic on Air Pollution.
ERIC Educational Resources Information Center
Taylor, Sharon
2001-01-01
Discusses the benefits of bringing scientists into the classroom to collaborate with children on environmental research projects. Describes one collaborative project that focused on the effects of traffic on air pollution. (DDR)
Crash risk analysis during fog conditions using real-time traffic data.
Wu, Yina; Abdel-Aty, Mohamed; Lee, Jaeyoung
2018-05-01
This research investigates the changes of traffic characteristics and crash risks during fog conditions. Using real-time traffic flow and weather data at two regions in Florida, the traffic patterns at the fog duration were compared to the traffic patterns at the clear duration. It was found that the average 5-min speed and the average 5-min volume were prone to decreasing during fog. Based on previous studies, a "Crash Risk Increase Indicator (CRII)" was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash risks with traffic flow characteristics. The results suggested that the proposed indicator worked well in evaluating the increase of crash risk under fog condition. It was indicated that the crash risk was prone to increase at ramp vicinities in fog conditions. Also, the average 5-min volume during fog and the lane position are important factors for crash risk increase. The differences between the regions were also explored in this study. The results indicated that the locations with heavier traffic or locations at the lanes that were closest to the median in Region 2 were more likely to observe an increase in crash risks in fog conditions. It is expected that the proposed indicator can help identify the dangerous traffic status under fog conditions and then proper ITS technologies can be implemented to enhance traffic safety when the visibility declines. Copyright © 2017 Elsevier Ltd. All rights reserved.
Research on moving target defense based on SDN
NASA Astrophysics Data System (ADS)
Chen, Mingyong; Wu, Weimin
2017-08-01
An address mutation strategy was proposed. This strategy provided an unpredictable change in address, replacing the real address of the packet forwarding process and path mutation, thus hiding the real address of the host and path. a mobile object defense technology based on Spatio-temporal Mutation on this basis is proposed, Using the software Defined Network centralized control architecture advantage combines sFlow traffic monitoring technology and Moving Target Defense. A mutated time period which can be changed in real time according to the network traffic is changed, and the destination address is changed while the controller abruptly changes the address while the data packet is transferred between the switches to construct a moving target, confusing the host within the network, thereby protecting the host and network.
DOT National Transportation Integrated Search
2007-05-01
VISUM Online is a traffic management system for processing online traffic data. The system implements both a road network model and a traffic demand model. VISUM Online uses all available real-time and historic data to calculate current and forecaste...
Methods and measurements in real-time air traffic control system simulation.
DOT National Transportation Integrated Search
1983-04-01
The major purpose of this work was to asses dynamic simulation of air traffic control systems as a technique for evaluating such systems in a statistically sound and objective manner. A large set of customarily used measures based on the system missi...
DOT National Transportation Integrated Search
2014-10-01
Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of : Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive : mainten...
Performance Evaluation of the Approaches and Algorithms Using Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Okuniek, Nikolai; Gerdes, Ingrid; Schier, Sebastian; Lee, Hanbong; Jung, Yoon
2016-01-01
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted; one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.
Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Okuniek, Nikolai; Gerdes, Ingrid; Schier, Sebastian; Lee, Hanbong; Jung, Yoon
2016-01-01
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.
Performance Evaluation of the Approaches and Algorithms using Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Lee, Hanbong; Jung, Yoon; Okuniek, Nikolai; Gerdes, Ingrid; Schier, Sebastian
2016-01-01
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft58; Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.
Faro, Alberto; Giordano, Daniela; Spampinato, Concetto
2008-06-01
This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.
Transforming GIS data into functional road models for large-scale traffic simulation.
Wilkie, David; Sewall, Jason; Lin, Ming C
2012-06-01
There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.
MIMO channel estimation and evaluation for airborne traffic surveillance in cellular networks
NASA Astrophysics Data System (ADS)
Vahidi, Vahid; Saberinia, Ebrahim
2018-01-01
A channel estimation (CE) procedure based on compressed sensing is proposed to estimate the multiple-input multiple-output sparse channel for traffic data transmission from drones to ground stations. The proposed procedure consists of an offline phase and a real-time phase. In the offline phase, a pilot arrangement method, which considers the interblock and block mutual coherence simultaneously, is proposed. The real-time phase contains three steps. At the first step, it obtains the priori estimate of the channel by block orthogonal matching pursuit; afterward, it utilizes that estimated channel to calculate the linear minimum mean square error of the received pilots. Finally, the block compressive sampling matching pursuit utilizes the enhanced received pilots to estimate the channel more accurately. The performance of the CE procedure is evaluated by simulating the transmission of traffic data through the communication channel and evaluating its fidelity for car detection after demodulation. Simulation results indicate that the proposed CE technique enhances the performance of the car detection in a traffic image considerably.
LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.
Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less
NASA Astrophysics Data System (ADS)
Jiang, Zhong-Yuan; Ma, Jian-Feng
Existing routing strategies such as the global dynamic routing [X. Ling, M. B. Hu, R. Jiang and Q. S. Wu, Phys. Rev. E 81, 016113 (2010)] can achieve very high traffic capacity at the cost of extremely long packet traveling delay. In many real complex networks, especially for real-time applications such as the instant communication software, extremely long packet traveling time is unacceptable. In this work, we propose to assign a finite Time-to-Live (TTL) parameter for each packet. To guarantee every packet to arrive at its destination within its TTL, we assume that a packet is retransmitted by its source once its TTL expires. We employ source routing mechanisms in the traffic model to avoid the routing-flaps induced by the global dynamic routing. We compose extensive simulations to verify our proposed mechanisms. With small TTL, the effects of packet retransmission on network traffic capacity are obvious, and the phase transition from flow free state to congested state occurs. For the purpose of reducing the computation frequency of the routing table, we employ a computing cycle Tc within which the routing table is recomputed once. The simulation results show that the traffic capacity decreases with increasing Tc. Our work provides a good insight into the understanding of effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks.
NASA Astrophysics Data System (ADS)
Wang, H. T.; Chen, T. T.; Yan, C.; Pan, H.
2018-05-01
For App recommended areas of mobile phone software, made while using conduct App application recommended combined weighted Slope One algorithm collaborative filtering algorithm items based on further improvement of the traditional collaborative filtering algorithm in cold start, data matrix sparseness and other issues, will recommend Spark stasis parallel algorithm platform, the introduction of real-time streaming streaming real-time computing framework to improve real-time software applications recommended.
Real-time distributed scheduling algorithm for supporting QoS over WDM networks
NASA Astrophysics Data System (ADS)
Kam, Anthony C.; Siu, Kai-Yeung
1998-10-01
Most existing or proposed WDM networks employ circuit switching, typically with one session having exclusive use of one entire wavelength. Consequently they are not suitable for data applications involving bursty traffic patterns. The MIT AON Consortium has developed an all-optical LAN/MAN testbed which provides time-slotted WDM service and employs fast-tunable transceivers in each optical terminal. In this paper, we explore extensions of this service to achieve fine-grained statistical multiplexing with different virtual circuits time-sharing the wavelengths in a fair manner. In particular, we develop a real-time distributed protocol for best-effort traffic over this time-slotted WDM service with near-optical fairness and throughput characteristics. As an additional design feature, our protocol supports the allocation of guaranteed bandwidths to selected connections. This feature acts as a first step towards supporting integrated services and quality-of-service guarantees over WDM networks. To achieve high throughput, our approach is based on scheduling transmissions, as opposed to collision- based schemes. Our distributed protocol involves one MAN scheduler and several LAN schedulers (one per LAN) in a master-slave arrangement. Because of propagation delays and limits on control channel capacities, all schedulers are designed to work with partial, delayed traffic information. Our distributed protocol is of the `greedy' type to ensure fast execution in real-time in response to dynamic traffic changes. It employs a hybrid form of rate and credit control for resource allocation. We have performed extensive simulations, which show that our protocol allocates resources (transmitters, receivers, wavelengths) fairly with high throughput, and supports bandwidth guarantees.
NASA Astrophysics Data System (ADS)
Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian
2008-04-01
Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.
Video-based real-time on-street parking occupancy detection system
NASA Astrophysics Data System (ADS)
Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang
2013-10-01
Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.
Theofilatos, Athanasios; Yannis, George; Kopelias, Pantelis; Papadimitriou, Fanis
2018-01-04
Considerable efforts have been made from researchers and policy makers in order to explain road crash occurrence and improve road safety performance of highways. However, there are cases when crashes are so few that they could be considered as rare events. In such cases, the binary dependent variable is characterized by dozens to thousands of times fewer events (crashes) than non-events (non-crashes). This paper attempts to add to the current knowledge by investigating crash likelihood by utilizing real-time traffic data and by proposing a framework driven by appropriate statistical models (Bias Correction and Firth method) in order to overcome the problems that arise when the number of crashes is very low. Under this approach instead of using traditional logistic regression methods, crashes are considered as rare events In order to demonstrate this approach, traffic data were collected from three random loop detectors in the Attica Tollway ("Attiki Odos") located in Greater Athens Area in Greece for the 2008-2011 period. The traffic dataset consists of hourly aggregated traffic data such as flow, occupancy, mean time speed and percentage of trucks in traffic. This study demonstrates the application and findings of our approach and revealed a negative relationship between crash occurrence and speed in crash locations. The method and findings of the study attempt to provide insights on the mechanism of crash occurrence and also to overcome data considerations for the first time in safety evaluation of motorways. Copyright © 2017 Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
2014-10-01
Winter weather in Iowa is often unpredictable and can have a large : impact on traffic flow. The Iowa Department of Transportation (DOT) : attempts to lessen the impact of winter weather events on traffic speeds : with various maintenance operations....
DOT National Transportation Integrated Search
2008-08-01
Freeway congestion is a major problem in many urban areas. It has been estimated that freeway incidents (events that impede the flow of traffic: accidents, disabled vehicles, etc.) account for one-half to three-fourths of the total congestion on metr...
Scalability Issues for Remote Sensing Infrastructure: A Case Study
Liu, Yang; Picard, Sean; Williamson, Carey
2017-01-01
For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure. PMID:28468262
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-04-10
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-01-01
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270
Learning and Design with Online Real-Time Collaboration
ERIC Educational Resources Information Center
Stevenson, Michael; Hedberg, John G.
2013-01-01
This paper explores the use of emerging Cloud technologies that support real-time online collaboration. It considers the extent to which these technologies can be leveraged to develop complex skillsets supporting interaction between multiple learners in online spaces. In a pilot study that closely examines how groups of learners translate two…
Continuation of the interoperable coordinated signal system deployment in White Plains, New York.
DOT National Transportation Integrated Search
2015-12-01
The City of White Plains, NY owns and operates an advanced traffic control system (TCS) that monitors : and controls over 130 intersections in real time. Its Traffic Department facility is not staffed 24 hours a : day, 7 days a week, but two other ce...
DOT National Transportation Integrated Search
2016-12-25
The key objectives of this study were to: 1. Develop advanced analytical techniques that make use of a dynamically configurable connected vehicle message protocol to predict traffic flow regimes in near-real time in a virtual environment and examine ...
DOT National Transportation Integrated Search
2012-02-12
In 2008, the Florida Department of Transportation began implementing the 95 Express, a segment of I-95 in Miami with high occupancy toll (HOT) lanes. Some vehicles use HOT lanes free, but most vehicles pay a toll based on real-time traffic conditions...
DOT National Transportation Integrated Search
2012-02-12
In 2008, the Florida Department of Transportation began implementing the 95 Express, a segment of I-95 in Miami with high occupancy toll (HOT) lanes. Some vehicles use HOT lanes free, but most vehicles pay a toll based on real-time traffic conditions...
A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.
Seo, Jung Woo; Lee, Sang Jin
2016-01-01
Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.
Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah
Tian, Le; Latré, Steven
2017-01-01
IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617
Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.
Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen
2017-07-04
IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.
A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.
Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing
2015-01-01
Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.
Airport Remote Tower Sensor Systems
NASA Technical Reports Server (NTRS)
Maluf, David A.; Gawdiak, Yuri; Leidichj, Christopher; Papasin, Richard; Tran, Peter B.; Bass, Kevin
2006-01-01
Networks of video cameras, meteorological sensors, and ancillary electronic equipment are under development in collaboration among NASA Ames Research Center, the Federal Aviation Administration (FAA), and the National Oceanic Atmospheric Administration (NOAA). These networks are to be established at and near airports to provide real-time information on local weather conditions that affect aircraft approaches and landings. The prototype network is an airport-approach-zone camera system (AAZCS), which has been deployed at San Francisco International Airport (SFO) and San Carlos Airport (SQL). The AAZCS includes remotely controlled color video cameras located on top of SFO and SQL air-traffic control towers. The cameras are controlled by the NOAA Center Weather Service Unit located at the Oakland Air Route Traffic Control Center and are accessible via a secure Web site. The AAZCS cameras can be zoomed and can be panned and tilted to cover a field of view 220 wide. The NOAA observer can see the sky condition as it is changing, thereby making possible a real-time evaluation of the conditions along the approach zones of SFO and SQL. The next-generation network, denoted a remote tower sensor system (RTSS), will soon be deployed at the Half Moon Bay Airport and a version of it will eventually be deployed at Los Angeles International Airport. In addition to remote control of video cameras via secure Web links, the RTSS offers realtime weather observations, remote sensing, portability, and a capability for deployment at remote and uninhabited sites. The RTSS can be used at airports that lack control towers, as well as at major airport hubs, to provide synthetic augmentation of vision for both local and remote operations under what would otherwise be conditions of low or even zero visibility.
A DICOM Based Collaborative Platform for Real-Time Medical Teleconsultation on Medical Images.
Maglogiannis, Ilias; Andrikos, Christos; Rassias, Georgios; Tsanakas, Panayiotis
2017-01-01
The paper deals with the design of a Web-based platform for real-time medical teleconsultation on medical images. The proposed platform combines the principles of heterogeneous Workflow Management Systems (WfMSs), the peer-to-peer networking architecture and the SPA (Single-Page Application) concept, to facilitate medical collaboration among healthcare professionals geographically distributed. The presented work leverages state-of-the-art features of the web to support peer-to-peer communication using the WebRTC (Web Real Time Communication) protocol and client-side data processing for creating an integrated collaboration environment. The paper discusses the technical details of implementation and presents the operation of the platform in practice along with some initial results.
Ntasis, Efthymios; Maniatis, Theofanis A; Nikita, Konstantina S
2003-01-01
A secure framework is described for real-time tele-collaboration on Virtual Simulation procedure of Radiation Treatment Planning. An integrated approach is followed clustering the security issues faced by the system into organizational issues, security issues over the LAN and security issues over the LAN-to-LAN connection. The design and the implementation of the security services are performed according to the identified security requirements, along with the need for real time communication between the collaborating health care professionals. A detailed description of the implementation is given, presenting a solution, which can directly be tailored to other tele-collaboration services in the field of health care. The pilot study of the proposed security components proves the feasibility of the secure environment, and the consistency with the high performance demands of the application.
[Dynamic road vehicle emission inventory simulation study based on real time traffic information].
Huang, Cheng; Liu, Juan; Chen, Chang-Hong; Zhang, Jian; Liu, Deng-Guo; Zhu, Jing-Yu; Huang, Wei-Ming; Chao, Yuan
2012-11-01
The vehicle activity survey, including traffic flow distribution, driving condition, and vehicle technologies, were conducted in Shanghai. The databases of vehicle flow, VSP distribution and vehicle categories were established according to the surveyed data. Based on this, a dynamic vehicle emission inventory simulation method was designed by using the real time traffic information data, such as traffic flow and average speed. Some roads in Shanghai city were selected to conduct the hourly vehicle emission simulation as a case study. The survey results show that light duty passenger car and taxi are major vehicles on the roads of Shanghai city, accounting for 48% - 72% and 15% - 43% of the total flow in each hour, respectively. VSP distribution has a good relationship with the average speed. The peak of VSP distribution tends to move to high load section and become lower with the increase of average speed. Vehicles achieved Euro 2 and Euro 3 standards are majorities of current vehicle population in Shanghai. Based on the calibration of vehicle travel mileage data, the proportions of Euro 2 and Euro 3 standard vehicles take up 11% - 70% and 17% - 51% in the real-world situation, respectively. The emission simulation results indicate that the ratios of emission peak and valley for the pollutants of CO, VOC, NO(x) and PM are 3.7, 4.6, 9.6 and 19.8, respectively. CO and VOC emissions mainly come from light-duty passenger car and taxi, which has a good relationship with the traffic flow. NO(x) and PM emissions are mainly from heavy-duty bus and public buses and mainly concentrate in the morning and evening peak hours. The established dynamic vehicle emission simulation method can reflect the change of actual road emission and output high emission road sectors and hours in real time. The method can provide an important technical means and decision-making basis for transportation environment management.
Vehicular camera pedestrian detection research
NASA Astrophysics Data System (ADS)
Liu, Jiahui
2018-03-01
With the rapid development of science and technology, it has made great development, but at the same time of highway traffic more convenient in highway traffic and transportation. However, in the meantime, traffic safety accidents occur more and more frequently in China. In order to deal with the increasingly heavy traffic safety. So, protecting the safety of people's personal property and facilitating travel has become a top priority. The real-time accurate pedestrian and driving environment are obtained through a vehicular camera which are used to detection and track the preceding moving targets. It is popular in the domain of intelligent vehicle safety driving, autonomous navigation and traffic system research. Based on the pedestrian video obtained by the Vehicular Camera, this paper studies the trajectory of pedestrian detection and its algorithm.
A GPS-based Real-time Road Traffic Monitoring System
NASA Astrophysics Data System (ADS)
Tanti, Kamal Kumar
In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.
Explaining How to Play Real-Time Strategy Games
NASA Astrophysics Data System (ADS)
Metoyer, Ronald; Stumpf, Simone; Neumann, Christoph; Dodge, Jonathan; Cao, Jill; Schnabel, Aaron
Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.
NASA Technical Reports Server (NTRS)
Arneson, Heather; Evans, Antony D.; Li, Jinhua; Wei, Mei Yueh
2017-01-01
Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, while automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies to be carried out that can inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. The paper describes the initial validation of the automated simulation capability against results from previous IDM HITL experiments, quantifying the differences. The simulator is then used to explore the performance of the IDM concept under the simple scenario of a capacity constrained airport under a wide range of wind conditions.
3D Markov Process for Traffic Flow Prediction in Real-Time.
Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi
2016-01-25
Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.
3D Markov Process for Traffic Flow Prediction in Real-Time
Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi
2016-01-01
Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025
Richmond-Bryant, Jennifer; Hahn, Intaek; Fortune, Christopher R; Rodes, Charles E; Portzer, Jeffrey W; Lee, Sangdon; Wiener, Russell W; Smith, Luther A; Wheeler, Michael; Seagraves, Jeremy; Stein, Mark; Eisner, Alfred D; Brixey, Laurie A; Drake-Richman, Zora E; Brouwer, Lydia H; Ellenson, William D; Baldauf, Richard
2009-12-01
The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) field study examined indoor and outdoor exposure to traffic-generated air pollution by studying the individual processes of generation of traffic emissions, transport and dispersion of air contaminants along a roadway, and infiltration of the contaminants into a residence. Real-time instrumentation was used to obtain highly resolved time-series concentration profiles for a number of air pollutants. The B-TRAPPED field study was conducted in the residential Sunset Park neighborhood of Brooklyn, NY, USA, in May 2005. The neighborhood contained the Gowanus Expressway (Interstate 278), a major arterial road (4(th) Avenue), and residential side streets running perpendicular to the Gowanus Expressway and 4(th) Avenue. Synchronized measurements were obtained inside a test house, just outside the test house façade, and along the urban residential street canyon on which the house was located. A trailer containing Federal Reference Method (FRM) and real-time monitors was located next to the Gowanus Expressway to assess the source. Ultrafine particulate matter (PM), PM(2.5), nitrogen oxides (NO(x)), sulfur dioxide (SO(2)), carbon monoxide (CO), carbon dioxide (CO(2)), temperature, relative humidity, and wind speed and direction were monitored. Different sampling schemes were devised to focus on dispersion along the street canyon or infiltration into the test house. Results were obtained for ultrafine PM, PM(2.5), criteria gases, and wind conditions from sampling schemes focused on street canyon dispersion and infiltration. For comparison, the ultrafine PM and PM(2.5) results were compared with an existing data set from the Los Angeles area, and the criteria gas data were compared with measurements from a Vancouver epidemiologic study. Measured ultrafine PM and PM(2.5) concentration levels along the residential urban street canyon and at the test house façade in Sunset Park were demonstrated to be comparable to traffic levels at an arterial road and slightly higher than those in a residential area of Los Angeles. Indoor ultrafine PM levels were roughly 3-10 times lower than outdoor levels, depending on the monitor location. CO, NO(2), and SO(2) levels were shown to be similar to values that produced increased risk of chronic obstructive pulmonary disease hospitalizations in the Vancouver studies.
NY TBO Research: Integrated Demand Management (IDM): IDM Concept, Tools, and Training Package
NASA Technical Reports Server (NTRS)
Smith, Nancy
2016-01-01
A series of human-in-the-loop simulation sessions were conducted in the Airspace Operations Laboratory (AOL) to evaluate a new traffic management concept called Integrated Demand Management (IDM). The simulation explored how to address chronic equity, throughput and delay issues associated with New Yorks high-volume airports by operationally integrating three current and NextGen capabilities the Collaborative Trajectory Options Program (CTOP), Time-Based Flow Management (TBFM) and Required Time of Arrival (RTA) in order to better manage traffic demand within the National Air Traffic System. A package of presentation slides was developed to describe the concept, tools, and training materials used in the simulation sessions. The package will be used to outbrief our stakeholders by both presenting orally and disseminating of the materials via email.
NASA Astrophysics Data System (ADS)
Gunawan, Fergyanto E.; Abbas, Bahtiar S.; Atmadja, Wiedjaja; Yoseph Chandra, Fajar; Agung, Alexander AS; Kusnandar, Erwin
2014-03-01
Traffic congestion in Asian megacities has become extremely worse, and any means to lessen the congestion level is urgently needed. Building an efficient mass transportation system is clearly necessary. However, implementing Intelligent Transportation Systems (ITS) have also been demonstrated effective in various advanced countries. Recently, the floating vehicle technique (FVT), an ITS implementation, has become cost effective to provide real-time traffic information with proliferation of the smartphones. Although many publications have discussed various issues related to the technique, none of them elaborates the discrepancy of a single floating car data (FCD) and the associated fleet data. This work addresses the issue based on an analysis of Sugiyama et al's experimental data. The results indicate that there is an optimum averaging time interval such that the estimated velocity by the FVT reasonably representing the traffic velocity.
Gheorghiu, Razvan Andrei; Iordache, Valentin
2018-06-03
As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors placed near road junctions, thus providing no information on the conditions in between. A large-scale sensor network using detectors on the majority of vehicles would certainly be capable of providing useful data, but has two major impediments: the equipment installed on the vehicles should be cheap enough (assuming the willingness of private car owners to be a part of the network) and be capable of transferring the required amount of data in due time, as the vehicle passes by the road side unit that acts as interface with the traffic management system. These restrictions reduce the number of technologies that can be used. In this article a series of comprehensive tests have been performed to evaluate the Bluetooth and ZigBee protocols for this purpose from many points of view: handshake time, static and dynamic data transfer (in laboratory conditions and in real traffic conditions). An assessment of the environmental conditions (during tests and probable to be encountered in real conditions) was also provided.
DOT National Transportation Integrated Search
2015-10-01
Visibility is one of the most important impacts weather can have on road systems; weather-related visibility reduction is most often due to fog. Florida is among the top-rated states in the United States with regards to traffic safety problems result...
Traffic Sign Inventory from Google Street View Images
NASA Astrophysics Data System (ADS)
Tsai, Victor J. D.; Chen, Jyun-Han; Huang, Hsun-Sheng
2016-06-01
Traffic sign detection and recognition (TSDR) has drawn considerable attention on developing intelligent transportation systems (ITS) and autonomous vehicle driving systems (AVDS) since 1980's. Unlikely to the general TSDR systems that deal with real-time images captured by the in-vehicle cameras, this research aims on developing techniques for detecting, extracting, and positioning of traffic signs from Google Street View (GSV) images along user-selected routes for low-cost, volumetric and quick establishment of the traffic sign infrastructural database that may be associated with Google Maps. The framework and techniques employed in the proposed system are described.
Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.
Islam, Kh Tohidul; Raj, Ram Gopal
2017-04-13
Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.
Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network
Islam, Kh Tohidul; Raj, Ram Gopal
2017-01-01
Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471
Real-time video analysis for retail stores
NASA Astrophysics Data System (ADS)
Hassan, Ehtesham; Maurya, Avinash K.
2015-03-01
With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.
A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks.
Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il
2017-11-09
Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new ( m , k )-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the ( m , k )-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured ( m , k )-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.
GENERAL: A modified weighted probabilistic cellular automaton traffic flow model
NASA Astrophysics Data System (ADS)
Zhuang, Qian; Jia, Bin; Li, Xin-Gang
2009-08-01
This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.
Real-time human collaboration monitoring and intervention
Merkle, Peter B.; Johnson, Curtis M.; Jones, Wendell B.; Yonas, Gerold; Doser, Adele B.; Warner, David J.
2010-07-13
A method of and apparatus for monitoring and intervening in, in real time, a collaboration between a plurality of subjects comprising measuring indicia of physiological and cognitive states of each of the plurality of subjects, communicating the indicia to a monitoring computer system, with the monitoring computer system, comparing the indicia with one or more models of previous collaborative performance of one or more of the plurality of subjects, and with the monitoring computer system, employing the results of the comparison to communicate commands or suggestions to one or more of the plurality of subjects.
A Proposed Framework for Collaborative Design in a Virtual Environment
NASA Astrophysics Data System (ADS)
Breland, Jason S.; Shiratuddin, Mohd Fairuz
This paper describes a proposed framework for a collaborative design in a virtual environment. The framework consists of components that support a true collaborative design in a real-time 3D virtual environment. In support of the proposed framework, a prototype application is being developed. The authors envision the framework will have, but not limited to the following features: (1) real-time manipulation of 3D objects across the network, (2) support for multi-designer activities and information access, (3) co-existence within same virtual space, etc. This paper also discusses a proposed testing to determine the possible benefits of a collaborative design in a virtual environment over other forms of collaboration, and results from a pilot test.
Integrated Service Provisioning in an Ipv6 over ATM Research Network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eli Dart; Helen Chen; Jerry Friesen
1999-02-01
During the past few years, the worldwide Internet has grown at a phenomenal rate, which has spurred the proposal of innovative network technologies to support the fast, efficient and low-latency transport of a wide spectrum of multimedia traffic types. Existing network infrastructures have been plagued by their inability to provide for real-time application traffic as well as their general lack of resources and resilience to congestion. This work proposes to address these issues by implementing a prototype high-speed network infrastructure consisting of Internet Protocol Version 6 (IPv6) on top of an Asynchronous Transfer Mode (ATM) transport medium. Since ATM ismore » connection-oriented whereas IP uses a connection-less paradigm, the efficient integration of IPv6 over ATM is especially challenging and has generated much interest in the research community. We propose, in collaboration with an industry partner, to implement IPv6 over ATM using a unique approach that integrates IP over fast A TM hardware while still preserving IP's connection-less paradigm. This is achieved by replacing ATM's control software with IP's routing code and by caching IP's forwarding decisions in ATM's VPI/VCI translation tables. Prototype ''VR'' and distributed-parallel-computing applications will also be developed to exercise the realtime capability of our IPv6 over ATM network.« less
Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications
Jang, Jeong Ah; Kim, Hyun Suk; Cho, Han Byeog
2011-01-01
The use of newly emerging sensor technologies in traditional roadway systems can provide real-time traffic services to drivers through Telematics and Intelligent Transport Systems (ITSs). This paper introduces a smart roadside system that utilizes various sensors for driver assistance and traffic safety warnings. This paper shows two road application models for a smart roadside system and sensors: a red-light violation warning system for signalized intersections, and a speed advisory system for highways. Evaluation results for the two services are then shown using a micro-simulation method. In the given real-time applications for drivers, the framework and certain algorithms produce a very efficient solution with respect to the roadway type features and sensor type use. PMID:22164025
Real-time estimation of incident delay in dynamic and stochastic networks
DOT National Transportation Integrated Search
1997-01-01
The ability to predict the link travel times is a necessary requirement for most intelligent transportation systems (ITS) applications such as route guidance systems. In an urban traffic environment, these travel times are dynamic and stochastic and ...
Framing the Progress of Collaborative Teacher Education
ERIC Educational Resources Information Center
Griffin, Cynthia C.; Pugach, Marlene C.
2007-01-01
In this article, the authors advance 10 postulates describing what they believe to be true about collaboration in special education: (1) Collaboration in teacher education is possible; (2) Collaborative programs can be initiated from many departure points; (3) Collaboration requires real time for communication; (4) Supportive leadership is…
Wireless data collection system for travel time estimation and traffic performance evaluation.
DOT National Transportation Integrated Search
2010-09-01
Having accurate and continually updated travel time and other performance data for the road and highway system has many benefits. From the perspective of the road users, having real-time updates on travel times will permit better travel and route pla...
NASA Astrophysics Data System (ADS)
Ryu, B. Y.; Jung, H. J.; Bae, S. H.; Choi, C. U.
2013-12-01
CO2 emissions on roads in urban centers substantially affect global warming. It is important to quantify CO2 emissions in terms of the link unit in order to reduce these emissions on the roads. Therefore, in this study, we utilized real-time traffic data and attempted to develop a methodology for estimating CO2 emissions per link unit. Because of the recent development of the vehicle-to-infrastructure (V2I) communication technology, data from probe vehicles (PVs) can be collected and speed per link unit can be calculated. Among the existing emission calculation methodologies, mesoscale modeling, which is a representative modeling measurement technique, requires speed and traffic data per link unit. As it is not feasible to install fixed detectors at every link for traffic data collection, in this study, we developed a model for traffic volume estimation by utilizing the number of PVs that can be additionally collected when the PV data are collected. Multiple linear regression and an artificial neural network (ANN) were used for estimating the traffic volume. The independent variables and input data for each model are the number of PVs, travel time index (TTI), the number of lanes, and time slots. The result from the traffic volume estimate model shows that the mean absolute percentage error (MAPE) of the ANN is 18.67%, thus proving that it is more effective. The ANN-based traffic volume estimation served as the basis for the calculation of emissions per link unit. The daily average emissions for Daejeon, where this study was based, were 2210.19 ton/day. By vehicle type, passenger cars accounted for 71.28% of the total emissions. By road, Gyeryongro emitted 125.48 ton/day, accounting for 5.68% of the total emission, the highest percentage of all roads. In terms of emissions per kilometer, Hanbatdaero had the highest emission volume, with 7.26 ton/day/km on average. This study proves that real-time traffic data allow an emissions estimate in terms of the link unit. Furthermore, an analysis of CO2 emissions can support traffic management to make decisions related to the reduction of carbon emissions.
Geomagnetic Observatory Data for Real-Time Applications
NASA Astrophysics Data System (ADS)
Love, J. J.; Finn, C. A.; Rigler, E. J.; Kelbert, A.; Bedrosian, P.
2015-12-01
The global network of magnetic observatories represents a unique collective asset for the scientific community. Historically, magnetic observatories have supported global magnetic-field mapping projects and fundamental research of the Earth's interior and surrounding space environment. More recently, real-time data streams from magnetic observatories have become an important contributor to multi-sensor, operational monitoring of evolving space weather conditions, especially during magnetic storms. In this context, the U.S. Geological Survey (1) provides real-time observatory data to allied space weather monitoring projects, including those of NOAA, the U.S. Air Force, NASA, several international agencies, and private industry, (2) collaborates with Schlumberger to provide real-time geomagnetic data needed for directional drilling for oil and gas in Alaska, (3) develops products for real-time evaluation of hazards for the electric-power grid industry that are associated with the storm-time induction of geoelectric fields in the Earth's conducting lithosphere. In order to implement strategic priorities established by the USGS Natural Hazards Mission Area and the National Science and Technology Council, and with a focus on developing new real-time products, the USGS is (1) leveraging data management protocols already developed by the USGS Earthquake Program, (2) developing algorithms for mapping geomagnetic activity, a collaboration with NASA and NOAA, (3) supporting magnetotelluric surveys and developing Earth conductivity models, a collaboration with Oregon State University and the NSF's EarthScope Program, (4) studying the use of geomagnetic activity maps and Earth conductivity models for real-time estimation of geoelectric fields, (5) initiating geoelectric monitoring at several observatories, (6) validating real-time estimation algorithms against historical geomagnetic and geoelectric data. The success of these long-term projects is subject to funding constraints and will require coordination with partners in government, academia, and private industry.
Air Traffic Management Research at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Lee, Katharine
2005-01-01
Since the late 1980's, NASA Ames researchers have been investigating ways to improve the air transportation system through the development of decision support automation. These software advances, such as the Center-TRACON Automation System (eTAS) have been developed with teams of engineers, software developers, human factors experts, and air traffic controllers; some ASA Ames decision support tools are currently operational in Federal Aviation Administration (FAA) facilities and some are in use by the airlines. These tools have provided air traffic controllers and traffic managers the capabilities to help reduce overall delays and holding, and provide significant cost savings to the airlines as well as more manageable workload levels for air traffic service providers. NASA is continuing to collaborate with the FAA, as well as other government agencies, to plan and develop the next generation of decision support tools that will support anticipated changes in the air transportation system, including a projected increase to three times today's air-traffic levels by 2025. The presentation will review some of NASA Ames' recent achievements in air traffic management research, and discuss future tool developments and concepts currently under consideration.
Considerations for Isochronous Data Services over the Proximity-1 Space Link
NASA Technical Reports Server (NTRS)
Gao, Jay L.
2006-01-01
Future mission concepts for robotic and human explorations will involve a high level of real time control/monitoring operations such as tele-operation for spacecraft rendezvous and surface mobile platforms carrying life-support equipments. The timely dissemination of voice, command, and real-time telemetry for monitoring and coordination purposes is critical for mission success. It is envisioned that future missions will require a network infrastructure capable of supporting isochronous data services. The CCSDS Proximity-1 Space Link Protocol1 could be used to provide isochronous service over the surface-to-Earth relay as well as "beyond-the-horizon" communications between distant Lunar or Mars surface elements. This paper will analyze the latency, jitter, and throughput performance of the Proximity-1 protocol for isochronous applications. In particular we will focus on constrained scenarios where the protocol operates in full-duplex mode, carrying isochronous traffic in one direction and error-controlled traffic in the other direction. We analyze the impact of the strict priority scheme in Proximity-1 on delay jitter and the impact of the isochronous traffic on the efficiency of the reliable data transfer in the other direction, and discuss methods for performance optimization. In general, jitter performance is driving by relative loading of isochronous traffic on the forward link compared to the acknowledgement traffic. Under light loading condition, the upper-bound of the delay jitter is the transmission duration of an acknowledgement frame on the forward link; for higher loading scenarios, the maximum jitter is scaled up by the inverse of the residual bandwidth, i.e., the spare capacity available in the forward link to carry isochronous traffic.
Improving traffic safety culture in Iowa : phase II.
DOT National Transportation Integrated Search
2013-07-01
Phase II of Improving Traffic Safety Culture in Iowa focuses on producing actions that will improve the traffic safety culture across the state, and involves collaboration among the three large public universities in Iowa: Iowa State University, Univ...
Impacts of high resolution data on traveler compliance levels in emergency evacuation simulations
Lu, Wei; Han, Lee D.; Liu, Cheng; ...
2016-05-05
In this article, we conducted a comparison study of evacuation assignment based on Traffic Analysis Zones (TAZ) and high resolution LandScan USA Population Cells (LPC) with detailed real world roads network. A platform for evacuation modeling built on high resolution population distribution data and activity-based microscopic traffic simulation was proposed. This platform can be extended to any cities in the world. The results indicated that evacuee compliance behavior affects evacuation efficiency with traditional TAZ assignment, but it did not significantly compromise the performance with high resolution LPC assignment. The TAZ assignment also underestimated the real travel time during evacuation. Thismore » suggests that high data resolution can improve the accuracy of traffic modeling and simulation. The evacuation manager should consider more diverse assignment during emergency evacuation to avoid congestions.« less
Traffic flow collection wireless sensor network node for intersection light control
NASA Astrophysics Data System (ADS)
Li, Xu; Li, Xue
2011-10-01
Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.
Piloted simulation of a ground-based time-control concept for air traffic control
NASA Technical Reports Server (NTRS)
Davis, Thomas J.; Green, Steven M.
1989-01-01
A concept for aiding air traffic controllers in efficiently spacing traffic and meeting scheduled arrival times at a metering fix was developed and tested in a real time simulation. The automation aid, referred to as the ground based 4-D descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent-point and speed-profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is used by the air traffic controller to resolve conflicts and issue advisories to arrival aircraft. A joint simulation was conducted using a piloted simulator and an advanced concept air traffic control simulation to study the acceptability and accuracy of the DA automation aid from both the pilot's and the air traffic controller's perspectives. The results of the piloted simulation are examined. In the piloted simulation, airline crews executed controller issued descent advisories along standard curved path arrival routes, and were able to achieve an arrival time precision of + or - 20 sec at the metering fix. An analysis of errors generated in turns resulted in further enhancements of the algorithm to improve the predictive accuracy. Evaluations by pilots indicate general support for the concept and provide specific recommendations for improvement.
NASA Astrophysics Data System (ADS)
Radev, Dimitar; Lokshina, Izabella
2010-11-01
The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
NASA Astrophysics Data System (ADS)
Lin, Y. H.; Bai, R.; Qian, Z. H.
2018-03-01
Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.
NASA Astrophysics Data System (ADS)
Merkisz, Jerzy; Lijewski, Piotr; Fuć, Paweł
2011-06-01
The tests performed under real traffic conditions provide invaluable information on the relations between the engine parameters, vehicle parameters and traffic conditions (traffic congestion) on one side and the exhaust emissions on the other. The paper presents the result of road tests obtained in an urban and extra-urban cycles for vehicles fitted with different engines, spark ignition engine and compression ignition engine. For the tests a portable emission analyzer SEMTECH DS. by SENSORS was used. This analyzer provides online measurement of the concentrations of exhaust emission components on a vehicle in motion under real traffic conditions. The tests were performed in city traffic. A comparative analysis has been presented of the obtained results for vehicles with individual powertrains.
NASA Technical Reports Server (NTRS)
Lee, Alan G.; Robinson, John E.; Lai, Chok Fung
2017-01-01
This paper will describe the purpose, architecture, and implementation of a gate-to-gate, high-fidelity air traffic simulation environment called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed.The overarching purpose of the SMART-NAS Test Bed (SNTB) is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the Next Generation Air Transportation System of the United States, called NextGen. SNTB is intended to enable simulations that are currently impractical or impossible for three major areas of NextGen research and development: Concepts across multiple operational domains such as the gate-to-gate trajectory-based operations concept; Concepts related to revolutionary operations such as the seamless and widespread integration of large and small Unmanned Aerial System (UAS) vehicles throughout U.S. airspace; Real-time system-wide safety assurance technologies to allow safe, increasingly autonomous aviation operations. SNTB is primarily accessed through a web browser. A set of secure support services are provided to simplify all aspects of real-time, human-in-the-loop and automation-in-the-loop simulations from design (i.e., prior to execution) through analysis (i.e., after execution). These services include simulation architecture and asset configuration; scenario generation; command, control and monitoring; and analysis support.
MacNeill, M; Dobbin, N; St-Jean, M; Wallace, L; Marro, L; Shin, T; You, H; Kulka, R; Allen, R W; Wheeler, A J
2016-10-01
Traffic emissions have been associated with a wide range of adverse health effects. Many schools are situated close to major roads, and as children spend much of their day in school, methods to reduce traffic-related air pollutant concentrations in the school environment are warranted. One promising method to reduce pollutant concentrations in schools is to alter the timing of the ventilation so that high ventilation time periods do not correspond to rush hour traffic. Health Canada, in collaboration with the Ottawa-Carleton District School Board, tested the effect of this action by collecting traffic-related air pollution data from four schools in Ottawa, Canada, during October and November 2013. A baseline and intervention period was assessed in each school. There were statistically significant (P < 0.05) reductions in concentrations of most of the pollutants measured at the two late-start (9 AM start) schools, after adjusting for outdoor concentrations and the absolute indoor-outdoor temperature difference. The intervention at the early-start (8 AM start) schools did not have significant reductions in pollutant concentrations. Based on these findings, changing the timing of the ventilation may be a cost-effective mechanism of reducing traffic-related pollutants in late-start schools located near major roads. © 2015 Her Majesty the Queen in Right of Canada. Indoor Air published by John Wiley & Sons Ltd. Reproduced with the permission of the Minister of Health Canada.
Freeway travel-time estimation and forecasting.
DOT National Transportation Integrated Search
2013-03-01
Real-time traffic information provided by GDOT has proven invaluable for commuters in the : Georgia freeway network. The increasing number of Variable Message Signs, addition of : services such as My-NaviGAtor, NaviGAtor-to-go etc. and the advancemen...
Traffic flow forecasting using approximate nearest neighbor nonparametric regression
DOT National Transportation Integrated Search
2000-12-01
The purpose of this research is to enhance nonparametric regression (NPR) for use in real-time systems by first reducing execution time using advanced data structures and imprecise computations and then developing a methodology for applying NPR. Due ...
A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks
Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il
2017-01-01
Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new (m, k)-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the (m, k)-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured (m, k)-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption. PMID:29120404
Agents in real-time collaborative systems
NASA Astrophysics Data System (ADS)
Mitchell, David
1996-01-01
Desktop conferencing systems, providing voice- or video-conferencing with some form of data sharing, have become increasingly popular. Unlike asynchronous collaborative systems such as email, little attention has been devoted to the place of agents in such real-time systems. This paper examines some of the ways in which agents can be used to support such apparently simple tasks as the setting up and answering of calls. Three agent categories, locators, routers and responders, are defined and some simple examples discussed. Several ways in which such agents can collaborate, providing the basis of an intelligent network, are identified.
Street Viewer: An Autonomous Vision Based Traffic Tracking System.
Bottino, Andrea; Garbo, Alessandro; Loiacono, Carmelo; Quer, Stefano
2016-06-03
The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.
Automated Traffic Management System and Method
NASA Technical Reports Server (NTRS)
Glass, Brian J. (Inventor); Spirkovska, Liljana (Inventor); McDermott, William J. (Inventor); Reisman, Ronald J. (Inventor); Gibson, James (Inventor); Iverson, David L. (Inventor)
2000-01-01
A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.
Two Phase Admission Control for QoS Mobile Ad Hoc Networks
NASA Astrophysics Data System (ADS)
Chen, Chien-Sheng; Su, Yi-Wen; Liu, Wen-Hsiung; Chi, Ching-Lung
In this paper a novel and effective two phase admission control (TPAC) for QoS mobile ad hoc networks is proposed that satisfies the real-time traffic requirements in mobile ad hoc networks. With a limited amount of extra overhead, TPAC can avoid network congestions by a simple and precise admission control which blocks most of the overloading flow-requests in the route discovery process. When compared with previous QoS routing schemes such as QoS-aware routing protocol and CACP protocols, it is shown from system simulations that the proposed scheme can increase the system throughput and reduce both the dropping rate and the end-to-end delay. Therefore, TPAC is surely an effective QoS-guarantee protocol to provide for real-time traffic.
Istepanian, R S H; Philip, N
2005-01-01
In this paper we describe some of the optimisation issues relevant to the requirements of high throughput of medical data and video streaming traffic in 3G wireless environments. In particular we present a challenging 3G mobile health care application that requires a demanding 3G medical data throughput. We also describe the 3G QoS requirement of mObile Tele-Echography ultra-Light rObot system (OTELO that is designed to provide seamless 3G connectivity for real-time ultrasound medical video streams and diagnosis from a remote site (robotic and patient station) manipulated by an expert side (specialists) that is controlling the robotic scanning operation and presenting a real-time feedback diagnosis using 3G wireless communication links.
Bie, Yiming; Wang, Yinhai
2017-01-01
To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios. PMID:28531198
Bie, Yiming; Liu, Zhiyuan; Wang, Yinhai
2017-01-01
To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.
Evaluation of Improved Pushback Forecasts Derived from Airline Ground Operations Data
NASA Technical Reports Server (NTRS)
Carr, Francis; Theis, Georg; Feron, Eric; Clarke, John-Paul
2003-01-01
Accurate and timely predictions of airline pushbacks can potentially lead to improved performance of automated decision-support tools for airport surface traffic, thus reducing the variability and average duration of costly airline delays. One factor which affects the realization of these benefits is the level of uncertainty inherent in the turn processes. To characterize this inherent uncertainty, three techniques are developed for predicting time-to-go until pushback as a function of available ground-time; elapsed ground-time; and the status (not-started/in-progress/completed) of individual turn processes (cleaning, fueling, etc.). These techniques are tested against a large and detailed dataset covering approximately l0(exp 4) real-world turn operations obtained through collaboration with Deutsche Lufthansa AG. Even after the dataset is filtered to obtain a sample of turn operations with minimal uncertainty, the standard deviation of forecast error for all three techniques is lower-bounded away from zero, indicating that turn operations have a significant stochastic component. This lower-bound result shows that decision-support tools must be designed to incorporate robust mechanisms for coping with pushback demand stochasticity, rather than treating the pushback demand process as a known deterministic input.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, David G.; Cook, Marvin A.
This report summarizes collaborative efforts between Secure Scalable Microgrid and Korean Institute of Energy Research team members . The efforts aim to advance microgrid research and development towards the efficient utilization of networked microgrids . The collaboration resulted in the identification of experimental and real time simulation capabilities that may be leveraged for networked microgrids research, development, and demonstration . Additional research was performed to support the demonstration of control techniques within real time simulation and with hardware in the loop for DC microgrids .
Khatri, Chetan; Chapman, Stephen J; Glasbey, James; Kelly, Michael; Nepogodiev, Dmitri; Bhangu, Aneel; Fitzgerald, J Edward
2015-01-01
A substantial challenge facing multicentre audit and research projects is timely recruitment of collaborators and their study centres. Cost-effective strategies are required and fee-free social media has previously been identified as a potential conduit. We investigated and evaluated the effectiveness of a novel multi-format social media and Internet strategy for targeted recruitment to a national multicentre cohort study. Interventions involved a new Twitter account, including weekly live question-and-answer sessions, a new Facebook group page, online YouTube presentations and an information page on a national association website. Link tracking analysis was undertaken using Google Analytics, which was then related to subsequent registration. Social influence was calculated using the proprietary Klout score. Internet traffic analysis identified a total of 1562 unique registration site views, of which 285 originated from social media (18.2%). Some 528 unique registrations were received, with 96 via social media platforms (18.2%). Traffic source analysis identified a separate national association webpage as resulting in the majority of registration page views (15.8%), followed by Facebook (11.9%), Twitter (4.8%) and YouTube (1.5%). A combination of publicity through Facebook, Twitter and the dedicated national association webpage contributed to the greatest rise in registration traffic and accounted for 312 (48%) of the total registrations within a 2-week period. A Twitter 'social influence' (Klout) score of 42/100 was obtained during this period. Targeted social media substantially aided study dissemination and collaborator recruitment. It acted as an adjunct to traditional methods, accounting for 18.2% of collaborator registration in a short time period with no associated financial costs. We provide a practical model for designing future recruitment campaigns, and recommend Facebook, Twitter and targeted websites as the most effective adjuncts for maximising cost-effective study recruitment.
Khatri, Chetan; Chapman, Stephen J.; Glasbey, James; Kelly, Michael; Nepogodiev, Dmitri; Bhangu, Aneel; Fitzgerald, J. Edward
2015-01-01
Aims A substantial challenge facing multicentre audit and research projects is timely recruitment of collaborators and their study centres. Cost-effective strategies are required and fee-free social media has previously been identified as a potential conduit. We investigated and evaluated the effectiveness of a novel multi-format social media and Internet strategy for targeted recruitment to a national multicentre cohort study. Methods Interventions involved a new Twitter account, including weekly live question-and-answer sessions, a new Facebook group page, online YouTube presentations and an information page on a national association website. Link tracking analysis was undertaken using Google Analytics, which was then related to subsequent registration. Social influence was calculated using the proprietary Klout score. Results Internet traffic analysis identified a total of 1562 unique registration site views, of which 285 originated from social media (18.2%). Some 528 unique registrations were received, with 96 via social media platforms (18.2%). Traffic source analysis identified a separate national association webpage as resulting in the majority of registration page views (15.8%), followed by Facebook (11.9%), Twitter (4.8%) and YouTube (1.5%). A combination of publicity through Facebook, Twitter and the dedicated national association webpage contributed to the greatest rise in registration traffic and accounted for 312 (48%) of the total registrations within a 2-week period. A Twitter ‘social influence’ (Klout) score of 42/100 was obtained during this period. Conclusions Targeted social media substantially aided study dissemination and collaborator recruitment. It acted as an adjunct to traditional methods, accounting for 18.2% of collaborator registration in a short time period with no associated financial costs. We provide a practical model for designing future recruitment campaigns, and recommend Facebook, Twitter and targeted websites as the most effective adjuncts for maximising cost-effective study recruitment. PMID:25775005
NASA Astrophysics Data System (ADS)
Zhang, Ka; Sheng, Yehua; Gong, Zhijun; Ye, Chun; Li, Yongqiang; Liang, Cheng
2007-06-01
As an important sub-system in intelligent transportation system (ITS), the detection and recognition of traffic signs from mobile images is becoming one of the hot spots in the international research field of ITS. Considering the problem of traffic sign automatic detection in motion images, a new self-adaptive algorithm for traffic sign detection based on color and shape features is proposed in this paper. Firstly, global statistical color features of different images are computed based on statistics theory. Secondly, some self-adaptive thresholds and special segmentation rules for image segmentation are designed according to these global color features. Then, for red, yellow and blue traffic signs, the color image is segmented to three binary images by these thresholds and rules. Thirdly, if the number of white pixels in the segmented binary image exceeds the filtering threshold, the binary image should be further filtered. Fourthly, the method of gray-value projection is used to confirm top, bottom, left and right boundaries for candidate regions of traffic signs in the segmented binary image. Lastly, if the shape feature of candidate region satisfies the need of real traffic sign, this candidate region is confirmed as the detected traffic sign region. The new algorithm is applied to actual motion images of natural scenes taken by a CCD camera of the mobile photogrammetry system in Nanjing at different time. The experimental results show that the algorithm is not only simple, robust and more adaptive to natural scene images, but also reliable and high-speed on real traffic sign detection.
NASA Astrophysics Data System (ADS)
Andronico, Daniele; Ferrari, Ferruccio; Merenda, Riccardo; Reitano, Danilo; Scollo, Simona; Cristaldi, Antonio; Lodato, Luigi; Mangiagli, Salvatore
2016-04-01
During early December 2015, Mt. Etna (Italy) produced 4 paroxysmal events from the Voragine crater in just 3 days. This activity caused ash and lapilli fallout over a wide area extending from the volcanic slopes up to ~100 km from the volcano, affecting numerous villages and the cities of Messina and Reggio Calabria. Monitoring this kind of volcanic activity in order to know the dispersal of tephra fallout in quasi-real time can prove challenging, especially when several paroxysmal events follow each other as during these latest eruptions in December. To tackle similar recurring periods of frequent activity, which have occurred a number of times at Etna over recent years, we devised a collaborative system named Tefranet. The system is easy to use but at the same time designed to rapidly retrieve useful georeferenced information on tephra fallouts from Etna's explosive activity. Tefranet includes a mobile application and a web site, with particular attention to an administration backend tool, making owners of smartphones or other mobile devices participants. The system aims to involve citizens living not only in eastern Sicily (i.e. the area most affected by fallout based on the prevailing winds blowing on Etna), but also those resident at some distance, in areas potentially covered by tephra (more than 60-80 km from the volcano) and that are difficult to reach before the original amounts of tephra on the ground may become altered by anthropic (e.g. car traffic) and atmospheric (wind and rain) factors. The Tefranet community will be informed by the INGV specialists via mobile device in case explosive activity resumes, with users able to visualize all the tephra signals on a map in real time. All kinds of information concerning start/end of the tephra fallout, estimation of the clast dimensions, thickness of the deposit, level of tephra cover on the ground, will be welcomed, especially if accompanied by photos of the deposit and of the eruption plume. Here, we present a simulation of a real eruption case in order to show the potential of the system on improving the mapping of the fallout deposits, reducing the time needed to collect tephra samples and extending the sampling area, and finally helping effectively the study of fallout deposits and explosive eruptions also for research purposes.
Research on architecture of intelligent transportation cloud platform for Guangxi expressway
NASA Astrophysics Data System (ADS)
Hua, Pan; Huang, Zhongxiang; He, Zengzhen
2017-04-01
In view of the practical needs of the intelligent transportation business collaboration, a model on intelligent traffic business collaboration is established. Aarchitecture of intelligent traffic cloud platformfor high speed road is proposed which realizes the loose coupling of each intelligent traffic business module. Based on custom technology in database design, it realizes the dynamic customization of business function which means that different roles can dynamically added business functions according to the needs. Through its application in the development and implementation of the actual business system, the architecture is proved to be effective and feasible.
Knowledge-Based Scheduling of Arrival Aircraft in the Terminal Area
NASA Technical Reports Server (NTRS)
Krzeczowski, K. J.; Davis, T.; Erzberger, H.; Lev-Ram, Israel; Bergh, Christopher P.
1995-01-01
A knowledge based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real time simulation. The scheduling system automatically sequences, assigns landing times, and assign runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithm is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reductions, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithm is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper describes the scheduling algorithms, gives examples of their use, and presents data regarding their potential benefits to the air traffic system.
Knowledge-based scheduling of arrival aircraft
NASA Technical Reports Server (NTRS)
Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.
1995-01-01
A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.
Scheduling Policies for an Antiterrorist Surveillance System
2008-06-27
times; for example, see Reiman and Wein [17] and Olsen [15]. For real-time scheduling problems involving impatient customers, see Gaver et al. [2...heavy traffic with throughput time constraints: Asymptotically optimal dynamic controls. Queueing Systems 39, 23–54. 30 [17] Reiman , M. I. and Wein
NASA Technical Reports Server (NTRS)
Lozito, Sandy; Mackintosh, Margaret-Anne; DiMeo, Karen; Kopardekar, Parimal
2002-01-01
A simulation was conducted to examine the effect of shared air/ground authority when each is equipped with enhanced traffic- and conflict-alerting systems. The potential benefits of an advanced air traffic management (ATM) concept referred to as "free flight" include improved safety through enhanced conflict detection and resolution capabilities, increased flight-operations management, and better decision-making tools for air traffic controllers and flight crews. One element of the free-flight concept suggests shifting aircraft separation responsibility from air traffic controllers to flight crews, thereby creating an environment with "shared-separation" authority. During FY00. NASA, the Federal Aviation Administration (FAA), and the Volpe National Transportation Systems Center completed the first integrated, high-fidelity, real-time, human-in-the-loop simulation.
Grayscale image segmentation for real-time traffic sign recognition: the hardware point of view
NASA Astrophysics Data System (ADS)
Cao, Tam P.; Deng, Guang; Elton, Darrell
2009-02-01
In this paper, we study several grayscale-based image segmentation methods for real-time road sign recognition applications on an FPGA hardware platform. The performance of different image segmentation algorithms in different lighting conditions are initially compared using PC simulation. Based on these results and analysis, suitable algorithms are implemented and tested on a real-time FPGA speed sign detection system. Experimental results show that the system using segmented images uses significantly less hardware resources on an FPGA while maintaining comparable system's performance. The system is capable of processing 60 live video frames per second.
The Changeable Block Distance System Analysis
NASA Astrophysics Data System (ADS)
Lewiński, Andrzej; Toruń, Andrzej
The paper treats about efficiency analysis in Changeable Block Distance (CBD) System connected with wireless positioning and control of train. The analysis is based on modeling of typical ERTMS line and comparison with actual and future traffic. The calculations are related to assumed parameters of railway traffic corresponding to real time - table of distance Psary - Góra Włodowska from CMK line equipped in classic, ETCS Level 1 and ETCS with CBD systems.
Remotely Accessed Vehicle Traffic Management System
NASA Astrophysics Data System (ADS)
Al-Alawi, Raida
2010-06-01
The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.
NASA Technical Reports Server (NTRS)
Arneson, Heather; Evans, Antony D.; Li, Jinhua; Wei, Mei Yueh
2017-01-01
Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.
Distributed Traffic Complexity Management by Preserving Trajectory Flexibility
NASA Technical Reports Server (NTRS)
Idris, Husni; Vivona, Robert A.; Garcia-Chico, Jose-Luis; Wing, David J.
2007-01-01
In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which groundbased service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory-oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.
Progress in Near Real-Time Volcanic Cloud Observations Using Satellite UV Instruments
NASA Astrophysics Data System (ADS)
Krotkov, N. A.; Yang, K.; Vicente, G.; Hughes, E. J.; Carn, S. A.; Krueger, A. J.
2011-12-01
Volcanic clouds from explosive eruptions can wreak havoc in many parts of the world, as exemplified by the 2010 eruption at the Eyjafjöll volcano in Iceland, which caused widespread disruption to air traffic and resulted in economic impacts across the globe. A suite of satellite-based systems offer the most effective means to monitor active volcanoes and to track the movement of volcanic clouds globally, providing critical information for aviation hazard mitigation. Satellite UV sensors, as part of this suite, have a long history of making unique near-real time (NRT) measurements of sulfur dioxide (SO2) and ash (aerosol Index) in volcanic clouds to supplement operational volcanic ash monitoring. Recently a NASA application project has shown that the use of near real-time (NRT,i.e., not older than 3 h) Aura/OMI satellite data produces a marked improvement in volcanic cloud detection using SO2 combined with Aerosol Index (AI) as a marker for ash. An operational online NRT OMI AI and SO2 image and data product distribution system was developed in collaboration with the NOAA Office of Satellite Data Processing and Distribution. Automated volcanic eruption alarms, and the production of volcanic cloud subsets for multiple regions are provided through the NOAA website. The data provide valuable information in support of the U.S. Federal Aviation Administration goal of a safe and efficient National Air Space. In this presentation, we will highlight the advantages of UV techniques and describe the advances in volcanic SO2 plume height estimation and enhanced volcanic ash detection using hyper-spectral UV measurements, illustrated with Aura/OMI observations of recent eruptions. We will share our plan to provide near-real-time volcanic cloud monitoring service using the Ozone Mapping and Profiler Suite (OMPS) on the Joint Polar Satellite System (JPSS).
Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory
NASA Astrophysics Data System (ADS)
Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo
The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.
Switching performance of OBS network model under prefetched real traffic
NASA Astrophysics Data System (ADS)
Huang, Zhenhua; Xu, Du; Lei, Wen
2005-11-01
Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Airborne Camera System for Real-Time Applications - Support of a National Civil Protection Exercise
NASA Astrophysics Data System (ADS)
Gstaiger, V.; Romer, H.; Rosenbaum, D.; Henkel, F.
2015-04-01
In the VABENE++ project of the German Aerospace Center (DLR), powerful tools are being developed to aid public authorities and organizations with security responsibilities as well as traffic authorities when dealing with disasters and large public events. One focus lies on the acquisition of high resolution aerial imagery, its fully automatic processing, analysis and near real-time provision to decision makers in emergency situations. For this purpose a camera system was developed to be operated from a helicopter with light-weight processing units and microwave link for fast data transfer. In order to meet end-users' requirements DLR works close together with the German Federal Office of Civil Protection and Disaster Assistance (BBK) within this project. One task of BBK is to establish, maintain and train the German Medical Task Force (MTF), which gets deployed nationwide in case of large-scale disasters. In October 2014, several units of the MTF were deployed for the first time in the framework of a national civil protection exercise in Brandenburg. The VABENE++ team joined the exercise and provided near real-time aerial imagery, videos and derived traffic information to support the direction of the MTF and to identify needs for further improvements and developments. In this contribution the authors introduce the new airborne camera system together with its near real-time processing components and share experiences gained during the national civil protection exercise.
Software for Simulating Air Traffic
NASA Technical Reports Server (NTRS)
Sridhar, Banavar; Bilimoria, Karl; Grabbe, Shon; Chatterji, Gano; Sheth, Kapil; Mulfinger, Daniel
2006-01-01
Future Air Traffic Management Concepts Evaluation Tool (FACET) is a system of software for performing computational simulations for evaluating advanced concepts of advanced air-traffic management. FACET includes a program that generates a graphical user interface plus programs and databases that implement computational models of weather, airspace, airports, navigation aids, aircraft performance, and aircraft trajectories. Examples of concepts studied by use of FACET include aircraft self-separation for free flight; prediction of air-traffic-controller workload; decision support for direct routing; integration of spacecraft-launch operations into the U.S. national airspace system; and traffic- flow-management using rerouting, metering, and ground delays. Aircraft can be modeled as flying along either flight-plan routes or great-circle routes as they climb, cruise, and descend according to their individual performance models. The FACET software is modular and is written in the Java and C programming languages. The architecture of FACET strikes a balance between flexibility and fidelity; as a consequence, FACET can be used to model systemwide airspace operations over the contiguous U.S., involving as many as 10,000 aircraft, all on a single desktop or laptop computer running any of a variety of operating systems. Two notable applications of FACET include: (1) reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administration s nationally deployed, real-time, operational systems; and (2) the licensing and integration of FACET with the commercially available Flight Explorer, which is an Internet- based, real-time flight-tracking system.
Real-time detection and classification of anomalous events in streaming data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.
2016-04-19
A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.
Real-Time Research: An Experiment in the Design of Scholarship
ERIC Educational Resources Information Center
Zimmerman, Eric; Squire, Kurt; Steinkuehler, Constance; Dikkers, Seann
2009-01-01
This article reports on an unconventional collaborative event called Real-Time Research, a project that brought 25 participants together from radically divergent fields for a playful and somewhat improvisational investigation of what it means to do games and learning research. Real-Time Research took the form of a two-part workshop session at the…
Optimization of ramp area aircraft push back time windows in the presence of uncertainty
NASA Astrophysics Data System (ADS)
Coupe, William Jeremy
It is well known that airport surface traffic congestion at major airports is responsible for increased taxi-out times, fuel burn and excess emissions and there is potential to mitigate these negative consequences through optimizing airport surface traffic operations. Due to a highly congested voice communication channel between pilots and air traffic controllers and a data communication channel that is used only for limited functions, one of the most viable near-term strategies for improvement of the surface traffic is issuing a push back advisory to each departing aircraft. This dissertation focuses on the optimization of a push back time window for each departing aircraft. The optimization takes into account both spatial and temporal uncertainties of ramp area aircraft trajectories. The uncertainties are described by a stochastic kinematic model of aircraft trajectories, which is used to infer distributions of combinations of push back times that lead to conflict among trajectories from different gates. The model is validated and the distributions are included in the push back time window optimization. Under the assumption of a fixed taxiway spot schedule, the computed push back time windows can be integrated with a higher level taxiway scheduler to optimize the flow of traffic from the gate to the departure runway queue. To enable real-time decision making the computational time of the push back time window optimization is critical and is analyzed throughout.
Study of air traffic over KLFIR
NASA Astrophysics Data System (ADS)
Nusyirwan, I. F.; Rohani, J. Mohd
2017-12-01
This paper shares the overview of the work currently being conducted with the Department of Civil Aviation Malaysia related to the air traffic. The aim is to study air traffic performance over KL and KK FIR, and the area of interest in this paper is the Kuala Lumpur Flight Information Region (KLFIR). The air traffic performance parameters includes general air traffic movement such as level allocation, number of movements, sector load analysis and also more specific parameters such as airborne delays, effects of weather to the air movements as well as ground delays. To achieve this, a huge effort has been undertaken that includes live data collection algorithm development and real time statistical analysis algorithm development. The main outcome from this multi-disciplinary work is the long-term analysis on the air traffic performance in Malaysia, which will put the country at par in the aviation community, namely the International Civil Aviation Organization (ICAO).
A USA Commercial Flight Track Database for Upper Tropospheric Aircraft Emission Studies
NASA Technical Reports Server (NTRS)
Garber, Donald P.; Minnis, Patrick; Costulis, Kay P.
2003-01-01
A new air traffic database over the contiguous United States of America (USA) has been developed from a commercially available real-time product for 2001-2003 for all non-military flights above 25,000 ft. Both individual flight tracks and gridded spatially integrated flight legs are available. On average, approximately 24,000 high-altitude flights were recorded each day. The diurnal cycle of air traffic over the USA is characterized by a broad daytime maximum with a 0130-LT minimum and a mean day-night air traffic ratio of 2.4. Each week, the air traffic typically peaks on Thursday and drops to a low Saturday with a range of 18%. Flight density is greatest during late summer and least during winter. The database records the disruption of air traffic after the air traffic shutdown during September 2001. The dataset should be valuable for realistically simulating the atmospheric effects of aircraft in the upper troposphere.
ATC simulation of helicopter IFR approaches into major terminal areas using RNAV, MLS, and CDTI
NASA Technical Reports Server (NTRS)
Tobias, L.; Lee, H. Q.; Peach, L. L.; Willett, F. M., Jr.; Obrien, P. J.
1981-01-01
The introduction of independent helicopter IFR routes at hub airports was investigated in a real time air traffic control system simulation involving a piloted helicopter simulator, computer generated air traffic, and air traffic controllers. The helicopter simulator was equipped to fly area navigation (RNAV) routes and microwave landing system approaches. Problems studied included: (1) pilot acceptance of the approach procedure and tracking accuracy; (2) ATC procedures for handling a mix of helicopter and fixed wing traffic; and (3) utility of the cockpit display of traffic information (CDTI) for the helicopter in the hub airport environment. Results indicate that the helicopter routes were acceptable to the subject pilots and were noninterfering with fixed wing traffic. Merging and spacing maneuvers using CDTI were successfully carried out by the pilots, but controllers had some reservations concerning the acceptability of the CDTI procedures.
NASA Astrophysics Data System (ADS)
Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan
2016-02-01
With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.
Expanding the Operational Use of Total Lightning Ahead of GOES-R
NASA Technical Reports Server (NTRS)
Stano, Geoffrey T.; Wood, Lance; Garner, Tim; Nunez, Roland; Kann, Deirdre; Reynolds, James; Rydell, Nezette; Cox, Rob; Bobb, William R.
2015-01-01
NASA's Short-term Prediction Research and Transition Center (SPoRT) has been transitioning real-time total lightning observations from ground-based lightning mapping arrays since 2003. This initial effort was with the local Weather Forecast Offices (WFO) that could use the North Alabama Lightning Mapping Array (NALMA). These early collaborations established a strong interest in the use of total lightning for WFO operations. In particular the focus started with warning decision support, but has since expanded to include impact-based decision support and lightning safety. SPoRT has used its experience to establish connections with new lightning mapping arrays as they become available. The GOES-R / JPSS Visiting Scientist Program has enabled SPoRT to conduct visits to new partners and expand the number of operational users with access to total lightning observations. In early 2014, SPoRT conducted the most recent visiting scientist trips to meet with forecast offices that will used the Colorado, Houston, and Langmuir Lab (New Mexico) lightning mapping arrays. In addition, SPoRT met with the corresponding Center Weather Service Units (CWSUs) to expand collaborations with the aviation community. These visits were an opportunity to learn about the forecast needs of each office visited as well as to provide on-site training for the use of total lightning, setting the stage for a real-time assessment during May-July 2014. With five lightning mapping arrays covering multiple geographic locations, the 2014 assessment has demonstrated numerous uses of total lightning in varying situations. Several highlights include a much broader use of total lightning for impact-based decision support ranging from airport weather warnings, supporting fire crews, and protecting large outdoor events. The inclusion of the CWSUs has broadened the operational scope of total lightning, demonstrating how these data can support air traffic management, particularly in the Terminal Radar Approach Control Facilities (TRACON) region around an airport. These collaborations continue to demonstrate, from the operational perspective, the utility of total lightning and the importance of continued training and preparation in advance of the Geostationary Lightning Mapper.
DOT National Transportation Integrated Search
1999-03-15
In 1996, the National Highway Traffic Safety Administration (NHTSA) embarked on a congressionally mandated effort to develop educational countermeasures to the effects of fatigue, sleep disorders, and inattention on highway safety. In collaboration w...
Code of Federal Regulations, 2014 CFR
2014-04-01
... traffic lanes for the safety of road users and workers), and crash attenuators. (18) The addition or... systems, and to exchange voice, data, or video with one another on demand, in real time, as necessary...
Code of Federal Regulations, 2011 CFR
2011-04-01
... traffic lanes for the safety of road users and workers), and crash attenuators. (18) The addition or... systems, and to exchange voice, data, or video with one another on demand, in real time, as necessary...
Code of Federal Regulations, 2013 CFR
2013-04-01
... traffic lanes for the safety of road users and workers), and crash attenuators. (18) The addition or... systems, and to exchange voice, data, or video with one another on demand, in real time, as necessary...
Code of Federal Regulations, 2012 CFR
2012-04-01
... traffic lanes for the safety of road users and workers), and crash attenuators. (18) The addition or... systems, and to exchange voice, data, or video with one another on demand, in real time, as necessary...
Percolation transition in dynamical traffic network with evolving critical bottlenecks.
Li, Daqing; Fu, Bowen; Wang, Yunpeng; Lu, Guangquan; Berezin, Yehiel; Stanley, H Eugene; Havlin, Shlomo
2015-01-20
A critical phenomenon is an intrinsic feature of traffic dynamics, during which transition between isolated local flows and global flows occurs. However, very little attention has been given to the question of how the local flows in the roads are organized collectively into a global city flow. Here we characterize this organization process of traffic as "traffic percolation," where the giant cluster of local flows disintegrates when the second largest cluster reaches its maximum. We find in real-time data of city road traffic that global traffic is dynamically composed of clusters of local flows, which are connected by bottleneck links. This organization evolves during a day with different bottleneck links appearing in different hours, but similar in the same hours in different days. A small improvement of critical bottleneck roads is found to benefit significantly the global traffic, providing a method to improve city traffic with low cost. Our results may provide insights on the relation between traffic dynamics and percolation, which can be useful for efficient transportation, epidemic control, and emergency evacuation.
Performances and recent evolutions of EMSC Real Time Information services
NASA Astrophysics Data System (ADS)
Mazet-Roux, G.; Godey, S.; Bossu, R.
2009-04-01
The EMSC (http://www.emsc-csem.org) operates Real Time Earthquake Information services for the public and the scientific community which aim at providing rapid and reliable information on the seismic-ity of the Euro-Mediterranean region and on significant earthquakes worldwide. These services are based on parametric data rapidly provided by 66 seismological networks which are automatically merged and processed at EMSC. A web page which is updated every minute displays a list and a map of the latest earthquakes as well as additional information like location maps, moment tensors solutions or past regional seismicity. Since 2004, the performances and the popularity of these services have dramatically increased. The number of messages received from the contributors and the number of published events have been multiplied by 2 since 2004 and by 1.6 since 2005 respectively. The web traffic and the numbers of users of the Earthquake Notification Service (ENS) have been multiplied by 15 and 7 respectively. In terms of performances of the ENS, the median dissemination time for Euro-Med events is minutes in 2008. In order to further improve its performances and especially the speed and robustness of the reception of real time data, EMSC has recently implemented a software named QWIDS (Quake Watch Information Distribution System) which provides a quick and robust data exchange system through permanent TCP connections. At the difference with emails that can sometimes be delayed or lost, QWIDS is an actual real time communication system that ensures the data delivery. In terms of hardware, EMSC imple-mented a high availability, dynamic load balancing, redundant and scalable web servers infrastructure, composed of two SUN T2000 and one F5 BIG-IP switch. This will allow coping with constantly increas-ing web traffic and the occurrence of huge peaks of traffic after widely felt earthquakes.
Global Simulation of Aviation Operations
NASA Technical Reports Server (NTRS)
Sridhar, Banavar; Sheth, Kapil; Ng, Hok Kwan; Morando, Alex; Li, Jinhua
2016-01-01
The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.
Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition
NASA Astrophysics Data System (ADS)
Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa
A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.
Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.
Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe
2017-10-01
Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.
Maritime transport in the Gulf of Bothnia 2030.
Pekkarinen, Annukka; Repka, Sari
2014-10-01
Scenarios for shipping traffic in the Gulf of Bothnia (GoB) by 2030 are described in order to identify the main factors that should be taken into account when preparing a Maritime Spatial Plan (MSP) for the area. The application of future research methodology to planning of marine areas was also assessed. The methods include applying existing large scale quantitative scenarios for maritime traffic in the GoB and using real-time Delphi in which an expert group discussed different factors contributing to future maritime traffic in the GoB to find out the probability and significance of the factors having an impact on maritime traffic. MSP was tested on transnational scale in the Bothnian sea area as a pilot project.
Enhanced TCAS 2/CDTI traffic Sensor digital simulation model and program description
NASA Technical Reports Server (NTRS)
Goka, T.
1984-01-01
Digital simulation models of enhanced TCAS 2/CDTI traffic sensors are developed, based on actual or projected operational and performance characteristics. Two enhanced Traffic (or Threat) Alert and Collision Avoidance Systems are considered. A digital simulation program is developed in FORTRAN. The program contains an executive with a semireal time batch processing capability. The simulation program can be interfaced with other modules with a minimum requirement. Both the traffic sensor and CAS logic modules are validated by means of extensive simulation runs. Selected validation cases are discussed in detail, and capabilities and limitations of the actual and simulated systems are noted. The TCAS systems are not specifically intended for Cockpit Display of Traffic Information (CDTI) applications. These systems are sufficiently general to allow implementation of CDTI functions within the real systems' constraints.
Stability analysis of dynamic collaboration model with control signals on two lanes
NASA Astrophysics Data System (ADS)
Li, Zhipeng; Zhang, Run; Xu, Shangzhi; Qian, Yeqing; Xu, Juan
2014-12-01
In this paper, the influence of control signals on the stability of two-lane traffic flow is mainly studied by applying control theory with lane changing behaviors. We present the two-lane dynamic collaboration model with lateral friction and the expressions of feedback control signals. What is more, utilizing the delayed feedback control theory to the two-lane dynamic collaboration model with control signals, we investigate the stability of traffic flow theoretically and the stability conditions for both lanes are derived with finding that the forward and lateral feedback signals can improve the stability of traffic flow while the backward feedback signals cannot achieve it. Besides, direct simulations are conducted to verify the results of theoretical analysis, which shows that the feedback signals have a significant effect on the running state of two vehicle groups, and the results are same with the theoretical analysis.
A Survey on Urban Traffic Management System Using Wireless Sensor Networks.
Nellore, Kapileswar; Hancke, Gerhard P
2016-01-27
Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.
A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Lee; Chin, Shih-Miao; Hwang, Ho-Ling
Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because themore » degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.« less
A Survey on Urban Traffic Management System Using Wireless Sensor Networks
Nellore, Kapileswar; Hancke, Gerhard P.
2016-01-01
Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research. PMID:26828489
Sandy Hook Traveler Information System
DOT National Transportation Integrated Search
2010-09-01
This report focuses on equipment and procedural solutions for gathering and disseminating a wide range of visitor information, including real-time traveler information data relating to traffic and parking at the Sandy Hook Unit of the Gateway Recreat...
Tiramisu: Information from Live Data Streams.
DOT National Transportation Integrated Search
2016-01-01
The primary source of information for rider safety with respect to dynamic events such as : cancelled buses, detours, traffic conditions and other factors is the transit system website. : Although technological enhancements, such as real-time trackin...
Improved traffic operations through real-time data collection and control.
DOT National Transportation Integrated Search
2016-05-01
Intersections are a major source of delay in urban networks, and reservation-based intersection control for : autonomous vehicles has great potential to improve intersection throughput. However, despite the high : flexibility in reservations, existin...
Providing Advanced and Real-Time Travel/Traffic Information to Tourists
DOT National Transportation Integrated Search
1998-10-01
Advanced traveler information systems (ATIS) analyze and communicate information that can enhance travel efficiency, alleviate congestion, and increase safety. In Texas, tourists (i.e., tripmakers unacquainted with the state) constitute an important ...
ITS data quality : assessment procedure for freeway point detectors.
DOT National Transportation Integrated Search
2003-01-01
The Virginia Department of Transportation (VDOT) has made significant investments in the traffic-monitoring infrastructure that supports intelligent transportation systems (ITS). The purpose of this infrastructure is to provide accurate, real-time in...
Congestion-based emergency vehicle preemption.
DOT National Transportation Integrated Search
2010-08-01
This research analyzed and evaluated a new strategy for preemption of emergency vehicles along a corridor, which is : route-based and adaptive to real-time traffic conditions. The method uses dynamic offsets which are adjusted using : congestion-leve...
Traffic-aware energy saving scheme with modularization supporting in TWDM-PON
NASA Astrophysics Data System (ADS)
Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun
2017-01-01
Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.
NASA Astrophysics Data System (ADS)
Liu, Xiliang; Lu, Feng; Zhang, Hengcai; Qiu, Peiyuan
2013-06-01
It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modern cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals (from 0: 00 to 23: 59). All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy (about 10%-15% higher in RMSE), as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersections, we analyzed the spatio-temporal distribution of turn delays in three time scenarios (0: 00-0: 15, 8: 15-8: 30 and 12: 00-12: 15). It indicates that during one's single trip in Beijing, average 60% of the travel time on the road networks is wasted on the intersections, and this situation is even worse in daytime. Although the 400 main intersections take only 2.7% of all the intersections, they occupy about 18% travel time.
The NASA Exploration Design Team; Blueprint for a New Design Paradigm
NASA Technical Reports Server (NTRS)
Oberto, Robert E.; Nilsen, Erik; Cohen, Ron; Wheeler, Rebecca; DeFlorio, Paul
2005-01-01
NASA has chosen JPL to deliver a NASA-wide rapid-response real-time collaborative design team to perform rapid execution of program, system, mission, and technology trade studies. This team will draw on the expertise of all NASA centers and external partners necessary. The NASA Exploration Design Team (NEDT) will be led by NASA Headquarters, with field centers and partners added according to the needs of each study. Through real-time distributed collaboration we will effectively bring all NASA field centers directly inside Headquarters. JPL's Team X pioneered the technique of real time collaborative design 8 years ago. Since its inception, Team X has performed over 600 mission studies and has reduced per-study cost by a factor of 5 and per-study duration by a factor of 10 compared to conventional design processes. The Team X concept has spread to other NASA centers, industry, academia, and international partners. In this paper, we discuss the extension of the JPL Team X process to the NASA-wide collaborative design team. We discuss the architecture for such a process and elaborate on the implementation challenges of this process. We further discuss our current ideas on how to address these challenges.
NASA Astrophysics Data System (ADS)
Schwehr, K.; Hatch, L.; Thompson, M.; Wiley, D.
2007-12-01
The Automatic Identification System (AIS) is a new technology that provides ship position reports with location, time, and identity information without human intervention from ships carrying the transponders to any receiver listening to the broadcasts. In collaboration with the USCG's Research and Development Center, NOAA's Stellwagen Bank National Marine Sanctuary (SBNMS) has installed 3 AIS receivers around Massachusetts Bay to monitor ship traffic transiting the sanctuary and surrounding waters. The SBNMS and the USCG also worked together propose the shifting the shipping lanes (termed the traffic separation scheme; TSS) that transit the sanctuary slightly to the north to reduce the probability of ship strikes of whales that frequent the sanctuary. Following approval by the United Nation's International Maritime Organization, AIS provided a means for NOAA to assess changes in the distribution of shipping traffic caused by formal change in the TSS effective July 1, 2007. However, there was no easy way to visualize this type of time series data. We have created a software package called noaadata-py to process the AIS ship reports and produce KML files for viewing in Google Earth. Ship tracks can be shown changing over time to allow the viewer to feel the motion of traffic through the sanctuary. The ship tracks can also be gridded to create ship traffic density reports for specified periods of time. The density is displayed as map draped on the sea surface or as vertical histogram columns. Additional visualizations such as bathymetry images, S57 nautical charts, and USCG Marine Information for Safety and Law Enforcement (MISLE) can be combined with the ship traffic visualizations to give a more complete picture of the maritime environment. AIS traffic analyses have the potential to give managers throughout NOAA's National Marine Sanctuaries an improved ability to assess the impacts of ship traffic on the marine resources they seek to protect. Viewing ship traffic data through Google Earth provides ease and efficiency for people not trained in GIS data processing.
Multi-resolution model-based traffic sign detection and tracking
NASA Astrophysics Data System (ADS)
Marinas, Javier; Salgado, Luis; Camplani, Massimo
2012-06-01
In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.
Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...
2015-01-31
Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less
On resilience studies of system detection and recovery techniques against stealthy insider attacks
NASA Astrophysics Data System (ADS)
Wei, Sixiao; Zhang, Hanlin; Chen, Genshe; Shen, Dan; Yu, Wei; Pham, Khanh D.; Blasch, Erik P.; Cruz, Jose B.
2016-05-01
With the explosive growth of network technologies, insider attacks have become a major concern to business operations that largely rely on computer networks. To better detect insider attacks that marginally manipulate network traffic over time, and to recover the system from attacks, in this paper we implement a temporal-based detection scheme using the sequential hypothesis testing technique. Two hypothetical states are considered: the null hypothesis that the collected information is from benign historical traffic and the alternative hypothesis that the network is under attack. The objective of such a detection scheme is to recognize the change within the shortest time by comparing the two defined hypotheses. In addition, once the attack is detected, a server migration-based system recovery scheme can be triggered to recover the system to the state prior to the attack. To understand mitigation of insider attacks, a multi-functional web display of the detection analysis was developed for real-time analytic. Experiments using real-world traffic traces evaluate the effectiveness of Detection System and Recovery (DeSyAR) scheme. The evaluation data validates the detection scheme based on sequential hypothesis testing and the server migration-based system recovery scheme can perform well in effectively detecting insider attacks and recovering the system under attack.
An Energy-Efficient MAC Protocol for Medical Emergency Monitoring Body Sensor Networks
Zhang, Chongqing; Wang, Yinglong; Liang, Yongquan; Shu, Minglei; Chen, Changfang
2016-01-01
Medical emergency monitoring body sensor networks (BSNs) monitor the occurrence of medical emergencies and are helpful for the daily care of the elderly and chronically ill people. Such BSNs are characterized by rare traffic when there is no emergency occurring, high real-time and reliable requirements of emergency data and demand for a fast wake-up mechanism for waking up all nodes when an emergency happens. A beacon-enabled MAC protocol is specially designed to meet the demands of medical emergency monitoring BSNs. The rarity of traffic is exploited to improve energy efficiency. By adopting a long superframe structure to avoid unnecessary beacons and allocating most of the superframe to be inactive periods, the duty cycle is reduced to an extremely low level to save energy. Short active time slots are interposed into the superframe and shared by all of the nodes to deliver the emergency data in a low-delay and reliable way to meet the real-time and reliable requirements. The interposition slots can also be used by the coordinator to broadcast network demands to wake-up all nodes in a low-delay and energy-efficient way. Experiments display that the proposed MAC protocol works well in BSNs with low emergency data traffic. PMID:26999145
Twenty-Five Years of Applications of the Modified Allan Variance in Telecommunications.
Bregni, Stefano
2016-04-01
The Modified Allan Variance (MAVAR) was originally defined in 1981 for measuring frequency stability in precision oscillators. Due to its outstanding accuracy in discriminating power-law noise, it attracted significant interest among telecommunications engineers since the early 1990s, when it was approved as a standard measure in international standards, redressed as Time Variance (TVAR), for specifying the time stability of network synchronization signals and of equipment clocks. A dozen years later, the usage of MAVAR was also introduced for Internet traffic analysis to estimate self-similarity and long-range dependence. Further, in this field, it demonstrated superior accuracy and sensitivity, better than most popular tools already in use. This paper surveys the last 25 years of progress in extending the field of application of the MAVAR in telecommunications. First, the rationale and principles of the MAVAR are briefly summarized. Its adaptation as TVAR for specification of timing stability is presented. The usage of MAVAR/TVAR in telecommunications standards is reviewed. Examples of measurements on real telecommunications equipment clocks are presented, providing an overview on their actual performance in terms of MAVAR. Moreover, applications of MAVAR to network traffic analysis are surveyed. The superior accuracy of MAVAR in estimating long-range dependence is emphasized by highlighting some remarkable practical examples of real network traffic analysis.
Real-time bicycle detection at signalized intersections using thermal imaging technology
NASA Astrophysics Data System (ADS)
Collaert, Robin
2013-02-01
More and more governments and authorities around the world are promoting the use of bicycles in cities, as this is healthy for the bicyclist and improves the quality of life in general. Safety and efficiency of bicyclists has become a major focus. To achieve this, there is a need for a smarter approach towards the control of signalized intersections. Various traditional detection technologies, such as video, microwave radar and electromagnetic loops, can be used to detect vehicles at signalized intersections, but none of these can consistently separate bikes from other traffic, day and night and in various weather conditions. As bikes should get a higher priority and also require longer green time to safely cross the signalized intersection, traffic managers are looking for alternative detection systems that can make the distinction between bicycles and other vehicles near the stop bar. In this paper, the drawbacks of a video-based approach are presented, next to the benefits of a thermal-video-based approach for vehicle presence detection with separation of bicycles. Also, the specific technical challenges are highlighted in developing a system that combines thermal image capturing, image processing and output triggering to the traffic light controller in near real-time and in a single housing.
NASA Runway Incursion Prevention System (RIPS) Dallas-Fort Worth Demonstration Performance Analysis
NASA Technical Reports Server (NTRS)
Cassell, Rick; Evers, Carl; Esche, Jeff; Sleep, Benjamin; Jones, Denise R. (Technical Monitor)
2002-01-01
NASA's Aviation Safety Program Synthetic Vision System project conducted a Runway Incursion Prevention System (RIPS) flight test at the Dallas-Fort Worth International Airport in October 2000. The RIPS research system includes advanced displays, airport surveillance system, data links, positioning system, and alerting algorithms to provide pilots with enhanced situational awareness, supplemental guidance cues, a real-time display of traffic information, and warnings of runway incursions. This report describes the aircraft and ground based runway incursion alerting systems and traffic positioning systems (Automatic Dependent Surveillance - Broadcast (ADS-B) and Traffic Information Service - Broadcast (TIS-B)). A performance analysis of these systems is also presented.
Comparative analysis of dynamic pricing strategies for managed lanes.
DOT National Transportation Integrated Search
2015-06-01
The objective of this research is to investigate and compare the performances of different : dynamic pricing strategies for managed lanes facilities. These pricing strategies include real-time : traffic responsive methods, as well as refund options a...
Dynamic Stochastic Control of Freeway Corridor Systems : Summary and Project Overview
DOT National Transportation Integrated Search
1978-12-01
Systematic methodological approaches to overall traffic management from both short-term (real-time) and long-term (planning) perspectives have been developed. The approach embodies formulation and solution of interrelated mathematical problems from o...
Real-time communication architecture for connected-vehicle eco-traffic signal system applications.
DOT National Transportation Integrated Search
2014-02-01
Transportation Systems, and thus Intelligent Transportation Systems (ITS), are considered one of the most critical : infrastructures. For wireless communication ITS use communication links based on Dedicated Short Range Communication : (DSRC) in Wire...
Agent-based large-scale emergency evacuation using real-time open government data.
DOT National Transportation Integrated Search
2014-01-01
The open government initiatives have provided tremendous data resources for the : transportation system and emergency services in urban areas. This paper proposes : a traffic simulation framework using high temporal resolution demographic data : and ...
Effectiveness of work zone intelligent transportation systems.
DOT National Transportation Integrated Search
2013-12-01
In the last decade, Intelligent Transportation Systems (ITS) have increasingly been deployed in work zones by state departments of transportation. Also known as smart work zone systems they improve traffic operations and safety by providing real-time...
Priority, market-ready technologies and innovations list.
DOT National Transportation Integrated Search
2006-01-01
Telephone services for travelers provide real-time information about work zones, traffic incidents, and other causes of congestion. They allow travelers to make more informed decisions about their travel routes or modes and increase safety by helping...
Integrating Safety in Developing a Variable Speed Limit System
DOT National Transportation Integrated Search
2014-01-01
Disaggregate safety studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash....
Real-time monitoring of railway infrastructures using fibre Bragg grating sensors
NASA Astrophysics Data System (ADS)
Roveri, N.; Carcaterra, A.; Sestieri, A.
2015-08-01
In this work we present the results of a field trial with a FBG sensor array system for the real time monitoring of railway traffic and for the structural health monitoring of both the railway track and train wheels. The test campaign is performed on the 2nd line of Milan metropolitan underground, employing more than 50 FBG sensors along 1.5 km of the rail track, where the trains are tested during daily passenger rail transport, with a roughly maximum speeds of 90 km/h. The measurements were continuatively performed for over 6 months, with a sampling frequency of about 400 Hz. The large amount of data/sensors allows a rather accurate statistical treatment of the measurement data and permits, with dedicated algorithms, the estimation of rail and wheel wear, key traffic parameters such as the number of axles, the train speed and load, and, in the next future, the detection of localized imperfections.
NASA Technical Reports Server (NTRS)
Amonlirdviman, Keith; Farley, Todd C.; Hansman, R. John, Jr.; Ladik, John F.; Sherer, Dana Z.
1998-01-01
A distributed real-time simulation of the civil air traffic environment developed to support human factors research in advanced air transportation technology is presented. The distributed environment is based on a custom simulation architecture designed for simplicity and flexibility in human experiments. Standard Internet protocols are used to create the distributed environment, linking all advanced cockpit simulator, all Air Traffic Control simulator, and a pseudo-aircraft control and simulation management station. The pseudo-aircraft control station also functions as a scenario design tool for coordinating human factors experiments. This station incorporates a pseudo-pilot interface designed to reduce workload for human operators piloting multiple aircraft simultaneously in real time. The application of this distributed simulation facility to support a study of the effect of shared information (via air-ground datalink) on pilot/controller shared situation awareness and re-route negotiation is also presented.
JPL's Real-Time Weather Processor project (RWP) metrics and observations at system completion
NASA Technical Reports Server (NTRS)
Loesh, Robert E.; Conover, Robert A.; Malhotra, Shan
1990-01-01
As an integral part of the overall upgraded National Airspace System (NAS), the objective of the Real-Time Weather Processor (RWP) project is to improve the quality of weather information and the timeliness of its dissemination to system users. To accomplish this, an RWP will be installed in each of the Center Weather Service Units (CWSUs), located in 21 of the 23 Air Route Traffic Control Centers (ARTCCs). The RWP System is a prototype system. It is planned that the software will be GFE and that production hardware will be acquired via industry competitive procurement. The ARTCC is a facility established to provide air traffic control service to aircraft operating on Instrument Flight Rules (IFR) flight plans within controlled airspace, principally during the en route phase of the flight. Covered here are requirement metrics, Software Problem Failure Reports (SPFRs), and Ada portability metrics and observations.
ERIC Educational Resources Information Center
Burris, Justin T.
2013-01-01
Technology permeates every aspect of daily life, from the sensors that control the traffic signals to the cameras that allow real-time video chats with family around the world. At times, technology may make life easier, faster, and more productive. However, does technology do the same in schools and classrooms? Will the benefits of technology…
NASA Astrophysics Data System (ADS)
Chen, Jie; Li, Ming; Jiang, Rui; Hu, Mao-Bin
2017-09-01
In a real traffic system, information feedback has already been proven to be a good way to alleviate traffic jams. However, due to the massive traffic information of real system, the procedure is often difficult in practice. In this paper, we study the effects of the amount of feedback information based on a cellular automaton model of urban traffic. What we found most interesting is that when providing the traffic information of a part of a road to travelers, the performance of the system will be better than that providing the road's full traffic information. From this basis, we can provide more effective routing strategy with less information. We demonstrate that only providing the traffic information of about first half road from upstream to downstream can maximize the traffic capacity of the system. We also give an explanation for these phenomena by studying the distribution pattern of vehicles and the detailed turning environment at the intersections. The effects of the traffic light period are also provided.
Evaluation of the impacts of traffic states on crash risks on freeways.
Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin
2012-07-01
The primary objective of this study is to divide freeway traffic flow into different states, and to evaluate the safety performance associated with each state. Using traffic flow data and crash data collected from a northbound segment of the I-880 freeway in the state of California, United States, K-means clustering analysis was conducted to classify traffic flow into five different states. Conditional logistic regression models using case-controlled data were then developed to study the relationship between crash risks and traffic states. Traffic flow characteristics in each traffic state were compared to identify the underlying phenomena that made certain traffic states more hazardous than others. Crash risk models were also developed for different traffic states to identify how traffic flow characteristics such as speed and speed variance affected crash risks in different traffic states. The findings of this study demonstrate that the operations of freeway traffic can be divided into different states using traffic occupancy measured from nearby loop detector stations, and each traffic state can be assigned with a certain safety level. The impacts of traffic flow parameters on crash risks are different across different traffic flow states. A method based on discriminant analysis was further developed to identify traffic states given real-time freeway traffic flow data. Validation results showed that the method was of reasonably high accuracy for identifying freeway traffic states. Copyright © 2012 Elsevier Ltd. All rights reserved.
Throughput analysis of the IEEE 802.4 token bus standard under heavy load
NASA Technical Reports Server (NTRS)
Pang, Joseph; Tobagi, Fouad
1987-01-01
It has become clear in the last few years that there is a trend towards integrated digital services. Parallel to the development of public Integrated Services Digital Network (ISDN) is service integration in the local area (e.g., a campus, a building, an aircraft). The types of services to be integrated depend very much on the specific local environment. However, applications tend to generate data traffic belonging to one of two classes. According to IEEE 802.4 terminology, the first major class of traffic is termed synchronous, such as packetized voice and data generated from other applications with real-time constraints, and the second class is called asynchronous which includes most computer data traffic such as file transfer or facsimile. The IEEE 802.4 token bus protocol which was designed to support both synchronous and asynchronous traffic is examined. The protocol is basically a timer-controlled token bus access scheme. By a suitable choice of the design parameters, it can be shown that access delay is bounded for synchronous traffic. As well, the bandwidth allocated to asynchronous traffic can be controlled. A throughput analysis of the protocol under heavy load with constant channel occupation of synchronous traffic and constant token-passing times is presented.
An improved car-following model with multiple preceding cars' velocity fluctuation feedback
NASA Astrophysics Data System (ADS)
Guo, Lantian; Zhao, Xiangmo; Yu, Shaowei; Li, Xiuhai; Shi, Zhongke
2017-04-01
In order to explore and evaluate the effects of velocity variation trend of multiple preceding cars used in the Cooperative Adaptive Cruise Control (CACC) strategy on the dynamic characteristic, fuel economy and emission of the corresponding traffic flow, we conduct a study as follows: firstly, with the real-time car-following (CF) data, the close relationship between multiple preceding cars' velocity fluctuation feedback and the host car's behaviors is explored, the evaluation results clearly show that multiple preceding cars' velocity fluctuation with different time window-width are highly correlated to the host car's acceleration/deceleration. Then, a microscopic traffic flow model is proposed to evaluate the effects of multiple preceding cars' velocity fluctuation feedback in the CACC strategy on the traffic flow evolution process. Finally, numerical simulations on fuel economy and exhaust emission of the traffic flow are also implemented by utilizing VT-micro model. Simulation results prove that considering multiple preceding cars' velocity fluctuation feedback in the control strategy of the CACC system can improve roadway traffic mobility, fuel economy and exhaust emission performance.
ERIC Educational Resources Information Center
Bente, Gary; Ruggenberg, Sabine; Kramer, Nicole C.; Eschenburg, Felix
2008-01-01
This study analyzes the influence of avatars on social presence, interpersonal trust, perceived communication quality, nonverbal behavior, and visual attention in Net-based collaborations using a comparative approach. A real-time communication window including a special avatar interface was integrated into a shared collaborative workspace.…
Development of Universal Controller Architecture for SiC Based Power Electronic Building Blocks
2017-10-30
time control and control network routing and the other for non -real time instrumentation and monitoring. The two subsystems are isolated and share...directly to the processor without any software intervention. We use a non -real time I Gb/s Ethernet interface for monitoring and control of the module...NOTC1 802.lW Spanning tree Prot. 76.96 184.0 107.04 Multiple point Private Line l NOTC1 203.2 382.3 179.1 N/ A Non applicable 1 No traffic control at
REAL-TIME WATER QUALITY MONITORING AND MODELING FOR EQUITABLE RECREATION ON THE MYSTIC RIVER
City of Somerville, Massachusetts, in collaboration with Tufts University and the Mystic River Watershed Association, proposes this project that combines advanced technology for real-time water quality and meteorological monitoring with sampling of bacterial levels...
A microcomputer based traffic evacuation modeling system for emergency planning application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rathi, A.K.
1994-12-01
Vehicular evacuation is one of the major and often preferred protective action options available for emergency management in a real or anticipated disaster. Computer simulation models of evacuation traffic flow are used to estimate the time required for the affected populations to evacuate to safer areas, to evaluate effectiveness of vehicular evacuations as a protective action option. and to develop comprehensive evacuation plans when required. Following a review of the past efforts to simulate traffic flow during emergency evacuations, an overview of the key features in Version 2.0 of the Oak Ridge Evacuation Modeling System (OREMS) are presented in thismore » paper. OREMS is a microcomputer-based model developed to simulate traffic flow during regional emergency evacuations. OREMS integrates a state-of-the-art dynamic traffic flow and simulation model with advanced data editing and output display programs operating under a MS-Windows environment.« less
Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting
Ming-jun, Deng; Shi-ru, Qu
2015-01-01
Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting. PMID:26779258
Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting.
Deng, Ming-jun; Qu, Shi-ru
2015-01-01
Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting.
EEG alpha spindle measures as indicators of driver fatigue under real traffic conditions.
Simon, Michael; Schmidt, Eike A; Kincses, Wilhelm E; Fritzsche, Martin; Bruns, Andreas; Aufmuth, Claus; Bogdan, Martin; Rosenstiel, Wolfgang; Schrauf, Michael
2011-06-01
The purpose of this study is to show the effectiveness of EEG alpha spindles, defined by short narrowband bursts in the alpha band, as an objective measure for assessing driver fatigue under real driving conditions. An algorithm for the identification of alpha spindles is described. The performance of the algorithm is tested based on simulated data. The method is applied to real data recorded under real traffic conditions and compared with the performance of traditional EEG fatigue measures, i.e. alpha-band power. As a highly valid fatigue reference, the last 20 min of driving from participants who aborted the drive due to heavy fatigue were used in contrast to the initial 20 min of driving. Statistical analysis revealed significant increases from the first to the last driving section of several alpha spindle parameters and among all traditional EEG frequency bands, only of alpha-band power; with larger effect sizes for the alpha spindle based measures. An increased level of fatigue over the same time periods for drop-outs, as compared to participants who did not abort the drive, was observed only by means of alpha spindle parameters. EEG alpha spindle parameters increase both fatigue detection sensitivity and specificity as compared to EEG alpha-band power. It is demonstrated that alpha spindles are superior to EEG band power measures for assessing driver fatigue under real traffic conditions. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Real-Time Mutual Gaze Perception Enhances Collaborative Learning and Collaboration Quality
ERIC Educational Resources Information Center
Schneider, Bertrand; Pea, Roy
2013-01-01
In this paper we present the results of an eye-tracking study on collaborative problem-solving dyads. Dyads remotely collaborated to learn from contrasting cases involving basic concepts about how the human brain processes visual information. In one condition, dyads saw the eye gazes of their partner on the screen; in a control group, they did not…
Software Tools to Support Research on Airport Departure Planning
NASA Technical Reports Server (NTRS)
Carr, Francis; Evans, Antony; Feron, Eric; Clarke, John-Paul
2003-01-01
A simple, portable and useful collection of software tools has been developed for the analysis of airport surface traffic. The tools are based on a flexible and robust traffic-flow model, and include calibration, validation and simulation functionality for this model. Several different interfaces have been developed to help promote usage of these tools, including a portable Matlab(TM) implementation of the basic algorithms; a web-based interface which provides online access to automated analyses of airport traffic based on a database of real-world operations data which covers over 250 U.S. airports over a 5-year period; and an interactive simulation-based tool currently in use as part of a college-level educational module. More advanced applications for airport departure traffic include taxi-time prediction and evaluation of "windowing" congestion control.
Long-Term Tracking of a Specific Vehicle Using Airborne Optical Camera Systems
NASA Astrophysics Data System (ADS)
Kurz, F.; Rosenbaum, D.; Runge, H.; Cerra, D.; Mattyus, G.; Reinartz, P.
2016-06-01
In this paper we present two low cost, airborne sensor systems capable of long-term vehicle tracking. Based on the properties of the sensors, a method for automatic real-time, long-term tracking of individual vehicles is presented. This combines the detection and tracking of the vehicle in low frame rate image sequences and applies the lagged Cell Transmission Model (CTM) to handle longer tracking outages occurring in complex traffic situations, e.g. tunnels. The CTM model uses the traffic conditions in the proximities of the target vehicle and estimates its motion to predict the position where it reappears. The method is validated on an airborne image sequence acquired from a helicopter. Several reference vehicles are tracked within a range of 500m in a complex urban traffic situation. An artificial tracking outage of 240m is simulated, which is handled by the CTM. For this, all the vehicles in the close proximity are automatically detected and tracked to estimate the basic density-flow relations of the CTM model. Finally, the real and simulated trajectories of the reference vehicles in the outage are compared showing good correspondence also in congested traffic situations.
Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System
García-Garrido, Miguel A.; Ocaña, Manuel; Llorca, David F.; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel
2012-01-01
This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance. PMID:22438704
Complete vision-based traffic sign recognition supported by an I2V communication system.
García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel
2012-01-01
This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.
DOT National Transportation Integrated Search
2014-10-01
The overarching goal of this research project was to investigate the potential for the NCDOT Central Office Signal Timing : (COST) Section to monitor and assess the quality of field deployed closed-loop signal system plans using the data inherent in ...
Predicting commuter flows in spatial networks using a radiation model based on temporal ranges
NASA Astrophysics Data System (ADS)
Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán
2014-11-01
Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.
Spatial Analysis of Traffic and Routing Path Methods for Tsunami Evacuation
NASA Astrophysics Data System (ADS)
Fakhrurrozi, A.; Sari, A. M.
2018-02-01
Tsunami disaster occurred relatively very fast. Thus, it has a very large-scale impact on both non-material and material aspects. Community evacuation caused mass panic, crowds, and traffic congestion. A further research in spatial based modelling, traffic engineering and splitting zone evacuation simulation is very crucial as an effort to reduce higher losses. This topic covers some information from the previous research. Complex parameters include route selection, destination selection, the spontaneous timing of both the departure of the source and the arrival time to destination and other aspects of the result parameter in various methods. The simulation process and its results, traffic modelling, and routing analysis emphasized discussion which is the closest to real conditions in the tsunami evacuation process. The method that we should highlight is Clearance Time Estimate based on Location Priority in which the computation result is superior to others despite many drawbacks. The study is expected to have input to improve and invent a new method that will be a part of decision support systems for disaster risk reduction of tsunamis disaster.
Development of a transportation real-time technology readiness framework.
DOT National Transportation Integrated Search
2017-03-01
The purpose of this study was to develop a proof-of-concept carrier technology readiness framework. While substantial investment has been made into the Iowa Department of Transportation (DOT) Traffic Operations Center, scant attention has been paid t...
Historical development of the Travel Shenandoah pilot service
DOT National Transportation Integrated Search
2002-05-01
The purpose of this report is to document the historical development of the Travel Shenandoah pilot project, a real-time traffic, travel condition, and tourism information service for Virginia's Shenandoah Valley. This report does not attempt to desc...
GNSS real time performance monitoring and CNS/ATM implementation
DOT National Transportation Integrated Search
2006-07-01
The global transition to communications, navigation, surveillance / air traffic management (CNS/ATM) technology is moving forward at an increasing pace. A critical part of the CNS/ATM concept is the ability to monitor, analyze, and distribute aeronau...
Satellite-aided coastal zone monitoring and vessel traffic system
NASA Technical Reports Server (NTRS)
Baker, J. L.
1981-01-01
The development and demonstration of a coastal zone monitoring and vessel traffic system is described. This technique uses a LORAN-C navigational system and relays signals via the ATS-3 satellite to a computer driven color video display for real time control. Multi-use applications of the system to search and rescue operations, coastal zone management and marine safety are described. It is emphasized that among the advantages of the system are: its unlimited range; compatibility with existing navigation systems; and relatively inexpensive cost.
Oscillations in interconnected complex networks under intentional attack
NASA Astrophysics Data System (ADS)
Zhang, Wen-Ping; Xia, Yongxiang; Tan, Fei
2016-01-01
Many real-world networks are interconnected with each other. In this paper, we study the traffic dynamics in interconnected complex networks under an intentional attack. We find that with the shortest time delay routing strategy, the traffic dynamics can show the stable state, periodic, quasi-periodic and chaotic oscillations, when the capacity redundancy parameter changes. Moreover, compared with isolated complex networks, oscillations always take place in interconnected networks more easily. Thirdly, in interconnected networks, oscillations are affected strongly by the coupling probability and coupling preference.
Methods and Measurements in Real-Time Air Traffic Control System Simulation
1983-04-01
Percent of Variance Consumed by Factors 28 7 Correlations Between ABM II Factor Scores and SE14 1 30 Sector-Density Cell -Based Facter Scores 8 SEX I Cell ...runs for each of 31 subjects under each of 6 sector geometry-traffic density combinations ( cells ). Initial analyses, involving correlations between the...two runs in each cell , indicated very low correlations between the replicates. It was decided that before going further it would be best to conduct a
Using temporal detrending to observe the spatial correlation of traffic.
Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David
2017-01-01
This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.
Using temporal detrending to observe the spatial correlation of traffic
2017-01-01
This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093
NASA Technical Reports Server (NTRS)
Wong, Gregory L.; Denery, Dallas (Technical Monitor)
2000-01-01
The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.
ERIC Educational Resources Information Center
Dreamson, Neal
2017-01-01
The features of collaboration in design education include effective and efficient communication and reflection, and feasible manipulation of design objects. For collaborative design, information and communication technology offers educators the possibility to change design pedagogy. However, there is a paucity of literature on relative advantages…
AMOEBA: Designing for Collaboration in Computer Science Classrooms through Live Learning Analytics
ERIC Educational Resources Information Center
Berland, Matthew; Davis, Don; Smith, Carmen Petrick
2015-01-01
AMOEBA is a unique tool to support teachers' orchestration of collaboration among novice programmers in a non-traditional programming environment. The AMOEBA tool was designed and utilized to facilitate collaboration in a classroom setting in real time among novice middle school and high school programmers utilizing the IPRO programming…
Methodology for Calculating Latency of GPS Probe Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Zhongxiang; Hamedi, Masoud; Young, Stanley
Crowdsourced GPS probe data, such as travel time on changeable-message signs and incident detection, have been gaining popularity in recent years as a source for real-time traffic information to driver operations and transportation systems management and operations. Efforts have been made to evaluate the quality of such data from different perspectives. Although such crowdsourced data are already in widespread use in many states, particularly the high traffic areas on the Eastern seaboard, concerns about latency - the time between traffic being perturbed as a result of an incident and reflection of the disturbance in the outsourced data feed - havemore » escalated in importance. Latency is critical for the accuracy of real-time operations, emergency response, and traveler information systems. This paper offers a methodology for measuring probe data latency regarding a selected reference source. Although Bluetooth reidentification data are used as the reference source, the methodology can be applied to any other ground truth data source of choice. The core of the methodology is an algorithm for maximum pattern matching that works with three fitness objectives. To test the methodology, sample field reference data were collected on multiple freeway segments for a 2-week period by using portable Bluetooth sensors as ground truth. Equivalent GPS probe data were obtained from a private vendor, and their latency was evaluated. Latency at different times of the day, impact of road segmentation scheme on latency, and sensitivity of the latency to both speed-slowdown and recovery-from-slowdown episodes are also discussed.« less
Weather-responsive traffic management : real solutions for serious traffic problems.
DOT National Transportation Integrated Search
2009-04-01
This flyer describes how weather responsive traffic management (WRTM) can prevent or mitigate the effects of weather on traffic operations and reduce congestion. The three types of WRTM described in the flyer include 1) Advisory strategies that provi...
An evolutionary outlook of air traffic flow management techniques
NASA Astrophysics Data System (ADS)
Kistan, Trevor; Gardi, Alessandro; Sabatini, Roberto; Ramasamy, Subramanian; Batuwangala, Eranga
2017-01-01
In recent years Air Traffic Flow Management (ATFM) has become pertinent even in regions without sustained overload conditions caused by dense traffic operations. Increasing traffic volumes in the face of constrained resources has created peak congestion at specific locations and times in many areas of the world. Increased environmental awareness and economic drivers have combined to create a resurgent interest in ATFM as evidenced by a spate of recent ATFM conferences and workshops mediated by official bodies such as ICAO, IATA, CANSO the FAA and Eurocontrol. Significant ATFM acquisitions in the last 5 years include South Africa, Australia and India. Singapore, Thailand and Korea are all expected to procure ATFM systems within a year while China is expected to develop a bespoke system. Asia-Pacific nations are particularly pro-active given the traffic growth projections for the region (by 2050 half of all air traffic will be to, from or within the Asia-Pacific region). National authorities now have access to recently published international standards to guide the development of national and regional operational concepts for ATFM, geared to Communications, Navigation, Surveillance/Air Traffic Management and Avionics (CNS+A) evolutions. This paper critically reviews the field to determine which ATFM research and development efforts hold the best promise for practical technological implementations, offering clear benefits both in terms of enhanced safety and efficiency in times of growing air traffic. An evolutionary approach is adopted starting from an ontology of current ATFM techniques and proceeding to identify the technological and regulatory evolutions required in the future CNS+A context, as the aviation industry moves forward with a clearer understanding of emerging operational needs, the geo-political realities of regional collaboration and the impending needs of global harmonisation.
Active Queue Management Mechanisms for Real-Time Traffic in MANETs
2001-12-01
characteristics do not change much over a short period of time, substituting indices and/or gains is possible. This study aims to provide general guidelines about... bpf for FEC and 1 bpf to provide future expansion(s) of the coder. Table 6. Federal Standard 1016 characteristics (After Ref. [37]). a...
Decision dynamics of departure times: Experiments and modeling
NASA Astrophysics Data System (ADS)
Sun, Xiaoyan; Han, Xiao; Bao, Jian-Zhang; Jiang, Rui; Jia, Bin; Yan, Xiaoyong; Zhang, Boyu; Wang, Wen-Xu; Gao, Zi-You
2017-10-01
A fundamental problem in traffic science is to understand user-choice behaviors that account for the emergence of complex traffic phenomena. Despite much effort devoted to theoretically exploring departure time choice behaviors, relatively large-scale and systematic experimental tests of theoretical predictions are still lacking. In this paper, we aim to offer a more comprehensive understanding of departure time choice behaviors in terms of a series of laboratory experiments under different traffic conditions and feedback information provided to commuters. In the experiment, the number of recruited players is much larger than the number of choices to better mimic the real scenario, in which a large number of commuters will depart simultaneously in a relatively small time window. Sufficient numbers of rounds are conducted to ensure the convergence of collective behavior. Experimental results demonstrate that collective behavior is close to the user equilibrium, regardless of different scales and traffic conditions. Moreover, the amount of feedback information has a negligible influence on collective behavior but has a relatively stronger effect on individual choice behaviors. Reinforcement learning and Fermi learning models are built to reproduce the experimental results and uncover the underlying mechanism. Simulation results are in good agreement with the experimentally observed collective behaviors.
NASA Astrophysics Data System (ADS)
Parracino, Stefano; Richetta, Maria; Gelfusa, Michela; Malizia, Andrea; Bellecci, Carlo; De Leo, Leonardo; Perrimezzi, Carlo; Fin, Alessandro; Forin, Marco; Giappicucci, Francesca; Grion, Massimo; Marchese, Giuseppe; Gaudio, Pasquale
2016-10-01
Urban air pollution causes deleterious effects on human health and the environment. To meet stringent standards imposed by the European Commission, advanced measurement methods are required. Remote sensing techniques, such as light detection and ranging (LiDAR), can be a valuable option for evaluating particulate matter (PM), emitted by vehicles in urban traffic, with high sensitivity and in shorter time intervals. Since air quality problems persist not only in large urban areas, a measuring campaign was specifically performed in a suburban area of Crotone, Italy, using both a compact LiDAR system and conventional instruments for real-time vehicle emissions monitoring along a congested road. First results reported in this paper show a strong dependence between variations of LiDAR backscattering signals and traffic-related air pollution levels. Moreover, time-resolved LiDAR data averaged in limited regions, directly above conventional monitoring stations at the border of an intersection, were found to be linearly correlated to the PM concentration levels with a correlation coefficient between 0.75 and 0.84.
Making the connection: advancing traffic incident management in transportation planning : a primer.
DOT National Transportation Integrated Search
2013-07-01
"The intent of this primer is to inform and guide traffic incident management (TIM) professionals and transportation planners to initiate and develop collaborative relationships and advance TIM programs through the metropolitan planning process. The ...
Traffic flow visualization and control (TFVC) : final report
DOT National Transportation Integrated Search
1998-11-01
The TFVC system was developed in collaboration with the New York State Department of Transportation, the Federal Highway Administration, and the US Air Force Research Laboratory. It is a video-camera-based, wide-area, traffic surveillance and detecti...
Hossain, Moinul; Muromachi, Yasunori
2012-03-01
The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.
Supportive data and methods for the evaluation of AIRPOL-4
DOT National Transportation Integrated Search
1975-05-01
CHART (Chesapeake Highway Advisories Routing Traffic) is a joint effort of the Maryland Department of Transportation and the Maryland State Police, in cooperation with other federal, state and local agencies. CHART's mission is to improve real time o...
Real time assessment of dynamic loads on bridges.
DOT National Transportation Integrated Search
2013-05-01
Highway bridges are an important class of civil structures that are subject to continuously : acting and varying dynamic loads due to traffic. A large number of highway bridges in the US : (bridges on interstate highways or state highways which have ...
TxDOT uses of real-time commercial traffic data : opportunity matrix.
DOT National Transportation Integrated Search
2012-01-01
Based on a TxDOT survey, a review of other state DOTs, and researcher understanding of Intelligent Transportation System (ITS) needs, the Texas Transportation Institute (TTI) team developed a comprehensive list of opportunities for TxDOT to consider ...
Improving truck and speed data using paired video and single-loop sensors
DOT National Transportation Integrated Search
2006-12-01
Real-time speed and truck data are important inputs for modern freeway traffic control and : management systems. However, these data are not directly measurable by single-loop detectors. : Although dual-loop detectors provide speeds and classified ve...
Shendell, Derek G; Ana, Godson R E E
2011-01-01
Globally, urbanization has been occurring more rapidly in small-to-medium-sized cities in less-developed countries of Africa and Asia. Studies have suggested associations between traffic and industry-related air pollutants and adverse health outcomes. These chemical and physical exposure agents have also received increased attention for environmental quality concerns like global climate change. Most research to date, however, was conducted in larger industrialized country urban centers. Ibadan, Nigeria, is a historic city characterized by urban sprawl and increasing modernization as an academic and medical training center but is lacking in the implementation of environmental laws. The authors conducted their first training in Ibadan, Nigeria, May 19-23, 2008, based on initial collaborative work during 2006-2008 as well as a trip in mid-March 2007. They describe the rationale for and components of the training, likely one of the first of its kind in Africa. The title of the training was "Advances in Community Outdoor and Indoor Air and Environmental Quality Monitoring and Exposure Assessment." Content was multimedia and interdisciplinary. The authors included lectures, group discussions, field experiences at community and industrial sites with cross-sectional environmental monitoring, and planned pilot studies including master's thesis projects based on real-time, grant-funded monitoring equipment provided to the University of Ibadan, including protocol development demonstrations.
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing
Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin
2016-01-01
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.
Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin
2016-04-07
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.
Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Jung, Yoon; Lee, Hanbong; Schier, Sebastian; Okuniek, Nikolai; Gerdes, Ingrid
2016-01-01
In this work, fast-time simulations have been conducted using SARDA tools at Hamburg airport by NASA and real-time simulations using CADEO and TRACC with the NLR ATM Research Simulator (NARSIM) by DLR. The outputs are analyzed using a set of common metrics collaborated between DLR and NASA. The proposed metrics are derived from International Civil Aviation Organization (ICAO)s Key Performance Areas (KPAs) in capability, efficiency, predictability and environment, and adapted to simulation studies. The results are examined to explore and compare the merits and shortcomings of the two approaches using the common performance metrics. Particular attention is paid to the concept of the close-loop, trajectory-based taxi as well as the application of US concept to the European airport. Both teams consider the trajectory-based surface operation concept a critical technology advance in not only addressing the current surface traffic management problems, but also having potential application in unmanned vehicle maneuver on airport surface, such as autonomous towing or TaxiBot [6][7] and even Remote Piloted Aircraft (RPA). Based on this work, a future integration of TRACC and SOSS is described aiming at bringing conflict-free trajectory-based operation concept to US airport.
Satellite ATM Networks: Architectures and Guidelines Developed
NASA Technical Reports Server (NTRS)
vonDeak, Thomas C.; Yegendu, Ferit
1999-01-01
An important element of satellite-supported asynchronous transfer mode (ATM) networking will involve support for the routing and rerouting of active connections. Work published under the auspices of the Telecommunications Industry Association (http://www.tiaonline.org), describes basic architectures and routing protocol issues for satellite ATM (SATATM) networks. The architectures and issues identified will serve as a basis for further development of technical specifications for these SATATM networks. Three ATM network architectures for bent pipe satellites and three ATM network architectures for satellites with onboard ATM switches were developed. The architectures differ from one another in terms of required level of mobility, supported data rates, supported terrestrial interfaces, and onboard processing and switching requirements. The documentation addresses low-, middle-, and geosynchronous-Earth-orbit satellite configurations. The satellite environment may require real-time routing to support the mobility of end devices and nodes of the ATM network itself. This requires the network to be able to reroute active circuits in real time. In addition to supporting mobility, rerouting can also be used to (1) optimize network routing, (2) respond to changing quality-of-service requirements, and (3) provide a fault tolerance mechanism. Traffic management and control functions are necessary in ATM to ensure that the quality-of-service requirements associated with each connection are not violated and also to provide flow and congestion control functions. Functions related to traffic management were identified and described. Most of these traffic management functions will be supported by on-ground ATM switches, but in a hybrid terrestrial-satellite ATM network, some of the traffic management functions may have to be supported by the onboard satellite ATM switch. Future work is planned to examine the tradeoffs of placing traffic management functions onboard a satellite as opposed to implementing those functions at the Earth station components.
ERIC Educational Resources Information Center
Nichols, Maria
2014-01-01
What happens in classrooms when we create the time and space for authentic talk about texts? Extended, collaborative conversations that allow understanding to unfold over time can be messy and dynamic. As students wrestle with complex texts and ideas, talk can become lively--and predictable problems can arise. In this article, Marie Nichols uses…
Incidence of real-world automotive parent and halogenated PAH in urban atmosphere.
Gao, Pan-Pan; Zhao, Yi-Bo; Ni, Hong-Gang
2018-06-01
This study reports results from a tunnel experiment impact of real-world traffic-related particle and gas parent and halogenated polycyclic aromatic hydrocarbons (PAHs and HPAHs) on urban air. The traffic related emission characteristics and subsequent environmental behavior of these compounds were investigated. To understand the significance of real-world transport emissions to the urban air, traffic-related mass emissions of PAHs and HPAHs were estimated based on measured emission factors. According to our results, PAHs and HPAHs emissions via particulate phase were greater than those via gaseous phase; particles in 2.1-3.3 μm size fraction, have the major contribution to particulate PAHs and HPAHs emissions. Over all, contribution of traffic-related emission of PAHs (only ∼3% of the total PAHs emission in China) is an overstated source of PAHs pollution in China. Actually, exhaust pipe emission contributed much less than the total traffic-related emission of pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.
Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations
NASA Technical Reports Server (NTRS)
McNally, B. David; Love, John
2011-01-01
The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today's integrated FMS/datalink. Auxiliary(lat/long) waypoints define a minimum delay reroute between current position and a downstream capture fix beyond the weather. These auxiliary waypoints can be uplinked to equipped aircraft and auto-loaded into the FMS. Alternatively, for unequipped aircraft, auxiliary waypoints can be replaced by nearby named fixes, but this could reduce potential savings. The presentation includes an overview of the automation approach and focuses on several cases in terms of potential savings, reroute complexity, best auxiliary waypoint solution vs. named fix solution, and other metrics.
Classification of Automated Search Traffic
NASA Astrophysics Data System (ADS)
Buehrer, Greg; Stokes, Jack W.; Chellapilla, Kumar; Platt, John C.
As web search providers seek to improve both relevance and response times, they are challenged by the ever-increasing tax of automated search query traffic. Third party systems interact with search engines for a variety of reasons, such as monitoring a web site’s rank, augmenting online games, or possibly to maliciously alter click-through rates. In this paper, we investigate automated traffic (sometimes referred to as bot traffic) in the query stream of a large search engine provider. We define automated traffic as any search query not generated by a human in real time. We first provide examples of different categories of query logs generated by automated means. We then develop many different features that distinguish between queries generated by people searching for information, and those generated by automated processes. We categorize these features into two classes, either an interpretation of the physical model of human interactions, or as behavioral patterns of automated interactions. Using the these detection features, we next classify the query stream using multiple binary classifiers. In addition, a multiclass classifier is then developed to identify subclasses of both normal and automated traffic. An active learning algorithm is used to suggest which user sessions to label to improve the accuracy of the multiclass classifier, while also seeking to discover new classes of automated traffic. Performance analysis are then provided. Finally, the multiclass classifier is used to predict the subclass distribution for the search query stream.
Analysis of a Real-Time Separation Assurance System with Integrated Time-in-Trail Spacing
NASA Technical Reports Server (NTRS)
Aweiss, Arwa S.; Farrahi, Amir H.; Lauderdale, Todd A.; Thipphavong, Adam S.; Lee, Chu H.
2010-01-01
This paper describes the implementation and analysis of an integrated ground-based separation assurance and time-based metering prototype system into the Center-TRACON Automation System. The integration of this new capability accommodates constraints in four-dimensions: position (x-y), altitude, and meter-fix crossing time. Experiments were conducted to evaluate the performance of the integrated system and its ability to handle traffic levels up to twice that of today. Results suggest that the integrated system reduces the number and magnitude of time-in-trail spacing violations. This benefit was achieved without adversely affecting the resolution success rate of the system. Also, the data suggest that the integrated system is relatively insensitive to an increase in traffic of twice the current levels.
Oikawa, Shoko; Hirose, Toshiya; Aomura, Shigeru; Matsui, Yasuhiro
2016-11-01
The purpose of this study is to clarify the mechanism of traffic accidents involving cyclists. The focus is on the characteristics of cyclist accidents and scenarios, because the number of traffic accidents involving cyclists in Tokyo is the highest in Japan. First, dangerous situations in traffic incidents were investigated by collecting data from 304 cyclists in one city in Tokyo using a questionnaire survey. The survey indicated that cyclists used their bicycles generally while commuting to work or school in the morning. Second, the study investigated the characteristics of 250 accident situations involving cyclists that happened in the city using real-world bicycle accident data. The results revealed that the traffic accidents occurred at intersections of local streets, where cyclists collided most often with vehicles during commute time in the morning. Third, cyclists' behavior was observed at a local street intersection in the morning in the city using video pictures. In one hour during the morning commute period, 250 bicycles passed through the intersection. The results indicated that one of the reasons for traffic accidents involving cyclists might be the combined effect of low visibility, caused by the presence of box-like building structures close to the intersections, and the cyclists' behavior in terms of their velocity and no confirming safety. It was observed that, on average, bicycle velocity was 3.1 m/s at the initial line of an intersection. The findings from this study could be useful in developing new technologies to improve cyclist safety, such as alert devices for cyclists and vehicle drivers, wireless communication systems between cyclists and vehicle drivers, or advanced vehicles with bicycle detection and collision mitigation systems.
Guidelines for Evaluation of Ramp Signaling Deployments in a Real-Time Operations Environment
DOT National Transportation Integrated Search
2017-12-01
State agencies have developed warrants and guidelines for the identification of on-ramps for metering. However, these warrants only consider recurrent traffic conditions in the vicinity of each on-ramp without considering the need to meter multiple r...
Real-time data to improve en route decision making and reduce transportation demand.
DOT National Transportation Integrated Search
2009-07-01
One approach to mitigating traffic and strains on the transportation system is to shift focus from supply to demand. : When provided with good information and sufficient motivation, users of a transportation system can make : decisions that will resu...
Real-time optimization of passenger collection for commuter rail systems.
DOT National Transportation Integrated Search
2014-09-01
Commuter rail systems are being introduced into many urban areas as an alternative mode to automobiles : for commuting trips. The shift from the auto mode to rail mode is anticipated to greatly help alleviate : traffic congestion in urban road networ...
NASA Technical Reports Server (NTRS)
Yoo, Hyo-Sang; Brasil, Connie; Buckley, Nathan; Mohlenbrink, Christoph; Speridakos, Constantine; Parke, Bonny; Hodell, Gita; Lee, Paul U.; Smith, Nancy M.
2017-01-01
This paper introduces NASA's Integrated Demand Management (IDM) concept and presents the results from an early proof-of-concept evaluation and an exploratory experiment. An initial development of the concept was focused on integrating two systems - i.e. the FAA's newly deployed Traffic Flow Management System (TFMS) tool called the Collaborative Trajectory Options Program (CTOP) and the Time-Based Flow Management (TBFM) system with Extended Metering (XM) capabilities to manage projected heavy traffic demand into a capacity-constrained airport. A human-in-the-loop (HITL) simulation experiment was conducted to demonstrate the feasibility of the initial development of the concept by adapting it to an arrival traffic problem at Newark Liberty International Airport (EWR) during clear weather conditions. In this study, the CTOP was utilized to strategically plan the arrival traffic demand by controlling take-off times of both short- and long-haul flights (long-hauls specify aircraft outside TBFM regions and short-hauls specify aircraft within TBFM regions) in a way that results in equitable delays among the groups. Such strategic planning allows less airborne delay to occur within TBFM by feeding manageable long-haul traffic demand while reserving sufficient slots in the overhead streams for the short-haul departures. The manageable traffic demand indicates the TBFM scheduler assigns no more airborne delay than its assigned airspace is capable of absorbing. TBFM then uses its time-based metering capabilities to deliver the desirable throughput by tactically rescheduling the TBFM entered long-haul flights and short-haul departures. Additional research was also performed to explore use of Required Time of Arrival (RTA) capabilities as a potential control mechanism for the airborne flights to improve arrival traffic delivery accuracy of scheduled long-haul traffic demand. The study results show that both short- and long-haul flights received similar ground delays. In addition, there was a noticeable reduction in the total amount of excessive unanticipated last-minute ground delays, i.e. delays that are frequently imposed on the short-haul flight in current day operations due to saturation in the overhead stream, commonly referred to as 'double penalty'. Furthermore, the concept achieved the target throughput while minimizing the expected cost associated with overall delays in arrival traffic. Assessment of the RTA capabilities showed that there was indeed improvement of the scheduled entry times into TBFM regions by using RTA capabilities. However, with respect to reduction in delays incurred within TBFM, there was no observable benefit of improving the precision of long-haul flights entry times.
NASA Technical Reports Server (NTRS)
Aquilina, Rudolph A.
2015-01-01
The SMART-NAS Testbed for Safe Trajectory Based Operations Project will deliver an evaluation capability, critical to the ATM community, allowing full NextGen and beyond-NextGen concepts to be assessed and developed. To meet this objective a strong focus will be placed on concept integration and validation to enable a gate-to-gate trajectory-based system capability that satisfies a full vision for NextGen. The SMART-NAS for Safe TBO Project consists of six sub-projects. Three of the sub-projects are focused on exploring and developing technologies, concepts and models for evolving and transforming air traffic management operations in the ATM+2 time horizon, while the remaining three sub-projects are focused on developing the tools and capabilities needed for testing these advanced concepts. Function Allocation, Networked Air Traffic Management and Trajectory Based Operations are developing concepts and models. SMART-NAS Test-bed, System Assurance Technologies and Real-time Safety Modeling are developing the tools and capabilities to test these concepts. Simulation and modeling capabilities will include the ability to assess multiple operational scenarios of the national airspace system, accept data feeds, allowing shadowing of actual operations in either real-time, fast-time and/or hybrid modes of operations in distributed environments, and enable integrated examinations of concepts, algorithms, technologies, and NAS architectures. An important focus within this project is to enable the development of a real-time, system-wide safety assurance system. The basis of such a system is a continuum of information acquisition, analysis, and assessment that enables awareness and corrective action to detect and mitigate potential threats to continuous system-wide safety at all levels. This process, which currently can only be done post operations, will be driven towards "real-time" assessments in the 2035 time frame.
Designing Scenarios for Controller-in-the-Loop Air Traffic Simulations
NASA Technical Reports Server (NTRS)
Kupfer, Michael; Mercer, Joey S.; Cabrall, Christopher; Callantine, Todd
2013-01-01
Well prepared traffic scenarios contribute greatly to the success of controller-in-the-loop simulations. This paper describes each stage in the design process of realistic scenarios based on real-world traffic, to be used in the Airspace Operations Laboratory for simulations within the Air Traffic Management Technology Demonstration 1 effort. The steps from the initial analysis of real-world traffic, to the editing of individual aircraft records in the scenario file, until the final testing of the scenarios before the simulation conduct, are all described. The iterative nature of the design process and the various efforts necessary to reach the required fidelity, as well as the applied design strategies, challenges, and tools used during this process are also discussed.
QoS for Real Time Applications over Next Generation Data Networks
NASA Technical Reports Server (NTRS)
Ivancic, William; Atiquzzaman, Mohammed; Bai, Haowei; Su, Hongjun; Chitri, Jyotsna; Ahamed, Faruque
2001-01-01
Viewgraphs on Qualtity of Service (QOS) for real time applications over next generation data networks are presented. The progress to date include: Task 1: QoS in Integrated Services over DiffServ networks (UD); Task 2: Interconnecting ATN with the next generation Internet (UD); Task 3: QoS in DiffServ over ATM (UD); Task 4: Improving Explicit Congestion Notification with the Mark-Front Strategy (OSU); Task 5: Multiplexing VBR over VBR (OSU); and Task 6: Achieving QoS for TCP traffic in Satellite Networks with Differentiated Services (OSU).
Wang, Junhua; Sun, Shuaiyi; Fang, Shouen; Fu, Ting; Stipancic, Joshua
2017-02-01
This paper aims to both identify the factors affecting driver drowsiness and to develop a real-time drowsy driving probability model based on virtual Location-Based Services (LBS) data obtained using a driving simulator. A driving simulation experiment was designed and conducted using 32 participant drivers. Collected data included the continuous driving time before detection of drowsiness and virtual LBS data related to temperature, time of day, lane width, average travel speed, driving time in heavy traffic, and driving time on different roadway types. Demographic information, such as nap habit, age, gender, and driving experience was also collected through questionnaires distributed to the participants. An Accelerated Failure Time (AFT) model was developed to estimate the driving time before detection of drowsiness. The results of the AFT model showed driving time before drowsiness was longer during the day than at night, and was longer at lower temperatures. Additionally, drivers who identified as having a nap habit were more vulnerable to drowsiness. Generally, higher average travel speeds were correlated to a higher risk of drowsy driving, as were longer periods of low-speed driving in traffic jam conditions. Considering different road types, drivers felt drowsy more quickly on freeways compared to other facilities. The proposed model provides a better understanding of how driver drowsiness is influenced by different environmental and demographic factors. The model can be used to provide real-time data for the LBS-based drowsy driving warning system, improving past methods based only on a fixed driving. Copyright © 2016 Elsevier Ltd. All rights reserved.
Global Connections: Web Conferencing Tools Help Educators Collaborate Anytime, Anywhere
ERIC Educational Resources Information Center
Forrester, Dave
2009-01-01
Web conferencing tools help educators from around the world collaborate in real time. Teachers, school counselors, and administrators need only to put on their headsets, check the time zone, and log on to meet and learn from educators across the globe. In this article, the author discusses how educators can use Web conferencing at their schools.…
Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.
Zhou, Lizhen; Zhong, Shiquan; Ma, Shoufeng; Jia, Ning
2014-12-01
This paper applied prospect theory (PT) to describe drivers' route choice behavior under Variable Message Sign (VMS), which presented visual traffic information to assist them to make route choice decisions. A quite rich empirical data from questionnaire and field spot was used to estimate parameters of PT. In order to make the parameters more realistic with drivers' attitudes, they were classified into different types by significant factors influencing their behaviors. Based on the travel time distribution of alternative routes and route choice results from questionnaire, the parameterized value function of each category was figured out, which represented drivers' risk attitudes and choice characteristics. The empirical verification showed that the estimates were acceptable and effective. The result showed drivers' risk attitudes and route choice characteristics could be captured by PT under real-time information shown on VMS. For practical application, once drivers' route choice characteristics and parameters were identified, their route choice behavior under different road conditions could be predicted accurately, which was the basis of traffic guidance measures formulation and implementation for targeted traffic management. Moreover, the heterogeneous risk attitudes among drivers should be considered when releasing traffic information and regulating traffic flow. Copyright © 2014 Elsevier Ltd. All rights reserved.
2017-12-18
You’re on board an aircraft at the gate. Seat belts are all fastened and you’re ready to go. But then you wait. Finally you leave the gate and move out onto the tarmac. And wait. Why the delays? It’s all in the timing. Right now NASA is testing a software solution at Charlotte Douglas International Airport that coordinates the schedules between different “drivers” at the airport – the FAA controllers for traffic arriving and departing; the airline controllers for traffic on the airport’s surface. The goal? Get everyone to collaborate by sharing the same information about where an aircraft is, where it needs to be and when it needs to be there.
NASA Astrophysics Data System (ADS)
Manodham, Thavisak; Loyola, Luis; Miki, Tetsuya
IEEE 802.11 wirelesses LANs (WLANs) have been rapidly deployed in enterprises, public areas, and households. Voice-over-IP (VoIP) and similar applications are now commonly used in mobile devices over wireless networks. Recent works have improved the quality of service (QoS) offering higher data rates to support various kinds of real-time applications. However, besides the need for higher data rates, seamless handoff and load balancing among APs are key issues that must be addressed in order to continue supporting real-time services across wireless LANs and providing fair services to all users. In this paper, we introduce a novel access point (AP) with two transceivers that improves network efficiency by supporting seamless handoff and traffic load balancing in a wireless network. In our proposed scheme, the novel AP uses the second transceiver to scan and find neighboring STAs in the transmission range and then sends the results to neighboring APs, which compare and analyze whether or not the STA should perform a handoff. The initial results from our simulations show that the novel AP module is more effective than the conventional scheme and a related work in terms of providing a handoff process with low latency and sharing traffic load with neighbor APs.
Design of real-time voice over internet protocol system under bandwidth network
NASA Astrophysics Data System (ADS)
Zhang, Li; Gong, Lina
2017-04-01
With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.
DOT National Transportation Integrated Search
2011-09-01
The United States and Canada share the largest bi-national trading relationship in the world. An efficient and cost-effective border crossing system for both freight and passenger vehicle traffic is thus vital to the economic well-being and security ...
An Intelligent Cooperative Visual Sensor Network for Urban Mobility
Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea
2017-01-01
Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535
An Intelligent Cooperative Visual Sensor Network for Urban Mobility.
Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco
2017-11-10
Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.
Emergency vehicle traffic signal preemption system
NASA Technical Reports Server (NTRS)
Bachelder, Aaron D. (Inventor); Foster, Conrad F. (Inventor)
2011-01-01
An emergency vehicle traffic light preemption system for preemption of traffic lights at an intersection to allow safe passage of emergency vehicles. The system includes a real-time status monitor of an intersection which is relayed to a control module for transmission to emergency vehicles as well as to a central dispatch office. The system also provides for audio warnings at an intersection to protect pedestrians who may not be in a position to see visual warnings or for various reasons cannot hear the approach of emergency vehicles. A transponder mounted on an emergency vehicle provides autonomous control so the vehicle operator can attend to getting to an emergency and not be concerned with the operation of the system. Activation of a priority-code (i.e. Code-3) situation provides communications with each intersection being approached by an emergency vehicle and indicates whether the intersection is preempted or if there is any conflict with other approaching emergency vehicles. On-board diagnostics handle various information including heading, speed, and acceleration sent to a control module which is transmitted to an intersection and which also simultaneously receives information regarding the status of an intersection. Real-time communications and operations software allow central and remote monitoring, logging, and command of intersections and vehicles.
Storer, Malina; Salmond, Jennifer; Dirks, Kim N; Kingham, Simon; Epton, Michael
2014-09-01
Studies of health effects of air pollution exposure are limited by inability to accurately determine dose and exposure of air pollution in field trials. We explored the feasibility of using a mobile selected ion flow tube mass spectrometry (SIFT-MS) device, housed in a van, to determine ambient air and breath levels of benzene, xylene and toluene following exercise in areas of high motor vehicle traffic. The breath toluene, xylene and benzene concentration of healthy subjects were measured before and after exercising close to a busy road. The concentration of the volatile organic compounds (VOCs), in ambient air were also analysed in real time. Exercise close to traffic pollution is associated with a two-fold increase in breath VOCs (benzene, xylene and toluene) with levels returning to baseline within 20 min. This effect is not seen when exercising away from traffic pollution sources. Situating the testing device 50 m from the road reduced any confounding due to VOCs in the inspired air prior to the breath testing manoeuvre itself. Real-time field testing for air pollution exposure is possible using a mobile SIFT-MS device. This device is suitable for exploring exposure and dose relationships in a number of large scale field test scenarios.
Trajectory Specification for Terminal Air Traffic: Pairwise Conflict Detection and Resolution
NASA Technical Reports Server (NTRS)
Paielli, Russell A.; Erzberger, Heinz
2017-01-01
Trajectory Specification is the explicit bounding and control of aircraft trajectories such that the position at any point in time is constrained to a precisely defined volume of space. The bounding space is defined by cross-track, along-track, and vertical tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and will be based on the aircraft navigation capabilities and the current traffic situation. Assuming conformance, Trajectory Specification can guarantee safe separation for an arbitrary period of time even in the event of an air traffic control (ATC) system or datalink failure; hence it can help to achieve the high level of safety and reliability needed for ATC automation. It can also reduce the reliance on tactical backup systems during normal operation. This paper applies it to the terminal area around a major airport and presents algorithms and software for detecting and resolving conflicts. A representative set of pairwise conflicts was generated, and a fast-time simulation was run on them. All conflicts were successfully resolved in real time, demonstrating the computational feasibility of the concept.
Sharples, Sarah; Stedmon, Alex; Cox, Gemma; Nicholls, Alistair; Shuttleworth, Tracey; Wilson, John
2007-07-01
The challenge to anticipate the human factors impact of introducing new technologies into a safety critical environment can be addressed in a number of ways. This paper presents a research programme that utilised both laboratory- and field-based assessments to examine the way in which datalink and freeflight may affect the communication and collaboration between pilots, air traffic controllers, and other actors and artefacts in the flightdeck-air traffic control (ATC) joint cognitive system. An overview of the results from these studies is presented, and guidance is provided as to the likely situations in which this new technology is most likely to be successfully applied. In addition, the methodological approach of combining results from field and laboratory data is discussed.
Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju
2014-03-21
A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated.
Influence of Noise Barriers on Near-Road and On-Road Air Quality: Results from Phoenix
The presentation describes field study results quantifying the impact of roadside barriers under real-world conditions in Phoenix, Arizona. Public health concerns regarding adverse health effects for populations spending significant amounts of time near high traffic roadways has ...
Real-Time pedestrian detection : layered object recognition system for pedestrian collision sensing.
DOT National Transportation Integrated Search
2010-01-01
In 2005 alone, 64,000 pedestrians were injured and 4,882 were killed in the United States, with pedestrians accounting for 11 percent of all traffic fatalities and 2 percent of injuries. The focus of "Layered Object Recognition System for Pedestrian ...
Buffalo-Niagara Transportation Data-warehouse Prototype and Real-time Incident Detection
DOT National Transportation Integrated Search
2017-11-01
In the traffic engineering field, study and analysis often requires the use of multiple datasets. The nature of these data often makes them difficult to work with, especially in conjunction with one another. The overall goal of this study was to not ...
Augmenting the access grid using augmented reality
NASA Astrophysics Data System (ADS)
Li, Ying
2012-01-01
The Access Grid (AG) targets an advanced collaboration environment, with which multi-party group of people from remote sites can collaborate over high-performance networks. However, current AG still employs VIC (Video Conferencing Tool) to offer only pure video for remote communication, while most AG users expect to collaboratively refer and manipulate the 3D geometric models of grid services' results in live videos of AG session. Augmented Reality (AR) technique can overcome the deficiencies with its characteristics of combining virtual and real, real-time interaction and 3D registration, so it is necessary for AG to utilize AR to better assist the advanced collaboration environment. This paper introduces an effort to augment the AG by adding support for AR capability, which is encapsulated in the node service infrastructure, named as Augmented Reality Service (ARS). The ARS can merge the 3D geometric models of grid services' results and real video scene of AG into one AR environment, and provide the opportunity for distributed AG users to interactively and collaboratively participate in the AR environment with better experience.
Handover Control Method Using Resource Reservation in Mobile Multimedia Networks
NASA Astrophysics Data System (ADS)
Lee, Dong Chun; Lee, Jong Chan
When handover events occur during the transmission of multimedia traffic, efficient handover control procedures and radio resource allocation are necessary to maintain the same QoS of transmitted multimedia traffic because the QoS may be degraded by additional delay and information loss. In this paper we propose a new handover control method for the next generation mobile multimedia networks, in which the handover setup process is done in advance of a handover request by predicting the handover cell from mobile terminal's current position. The handover procedures for real-time sessions are performed based on the handover cell information and the resource reservation condition. The radio resources in the estimated adjacent cells should be reserved and allocated to guarantee the continuity of the real-time sessions. We conduct a simulation model that is focused on the handover failure rate and packet loss rate. The simulation results show that our proposed method provides better performance than the previous methods.
Microwave landing system modeling with application to air traffic control
NASA Technical Reports Server (NTRS)
Poulose, M. M.
1991-01-01
Compared to the current instrument landing system, the microwave landing system (MLS), which is in the advanced stage of implementation, can potentially provide significant fuel and time savings as well as more flexibility in approach and landing functions. However, the expanded coverage and increased accuracy requirements of the MLS make it more susceptible to the features of the site in which it is located. An analytical approach is presented for evaluating the multipath effects of scatterers that are commonly found in airport environments. The approach combines a multiplane model with a ray-tracing technique and a formulation for estimating the electromagnetic fields caused by the antenna array in the presence of scatterers. The model is applied to several airport scenarios. The reduced computational burden enables the scattering effects on MLS position information to be evaluated in near real time. Evaluation in near real time would permit the incorporation of the modeling scheme into air traffic control automation; it would adaptively delineate zones of reduced accuracy within the MLS coverage volume, and help establish safe approach and takeoff trajectories in the presence of uneven terrain and other scatterers.
Design and evaluation of an air traffic control Final Approach Spacing Tool
NASA Technical Reports Server (NTRS)
Davis, Thomas J.; Erzberger, Heinz; Green, Steven M.; Nedell, William
1991-01-01
This paper describes the design and simulator evaluation of an automation tool for assisting terminal radar approach controllers in sequencing and spacing traffic onto the final approach course. The automation tool, referred to as the Final Approach Spacing Tool (FAST), displays speed and heading advisories for arriving aircraft as well as sequencing information on the controller's radar display. The main functional elements of FAST are a scheduler that schedules and sequences the traffic, a four-dimensional trajectory synthesizer that generates the advisories, and a graphical interface that displays the information to the controller. FAST has been implemented on a high-performance workstation. It can be operated as a stand-alone in the terminal radar approach control facility or as an element of a system integrated with automation tools in the air route traffic control center. FAST was evaluated by experienced air traffic controllers in a real-time air traffic control simulation. simulation results summarized in the paper show that the automation tools significantly reduced controller work load and demonstrated a potential for an increase in landing rate.
ERIC Educational Resources Information Center
Hamalainen, Raija; Oksanen, Kimmo
2012-01-01
Along with the development of new technologies, orchestrating computer-supported collaborative learning (CSCL) has become a topic of discussion because new learning spaces challenge teacher to support collaborative learning in new ways. However, despite the optimistic notions of teachers' orchestration in CSCL situations, there are still no…
C-ME: A 3D Community-Based, Real-Time Collaboration Tool for Scientific Research and Training
Kolatkar, Anand; Kennedy, Kevin; Halabuk, Dan; Kunken, Josh; Marrinucci, Dena; Bethel, Kelly; Guzman, Rodney; Huckaby, Tim; Kuhn, Peter
2008-01-01
The need for effective collaboration tools is growing as multidisciplinary proteome-wide projects and distributed research teams become more common. The resulting data is often quite disparate, stored in separate locations, and not contextually related. Collaborative Molecular Modeling Environment (C-ME) is an interactive community-based collaboration system that allows researchers to organize information, visualize data on a two-dimensional (2-D) or three-dimensional (3-D) basis, and share and manage that information with collaborators in real time. C-ME stores the information in industry-standard databases that are immediately accessible by appropriate permission within the computer network directory service or anonymously across the internet through the C-ME application or through a web browser. The system addresses two important aspects of collaboration: context and information management. C-ME allows a researcher to use a 3-D atomic structure model or a 2-D image as a contextual basis on which to attach and share annotations to specific atoms or molecules or to specific regions of a 2-D image. These annotations provide additional information about the atomic structure or image data that can then be evaluated, amended or added to by other project members. PMID:18286178
Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles.
Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V; Imran, Muhammad; Zhou, Keliang
2016-01-11
The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.
Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles
Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V.; Imran, Muhammad; Zhou, Keliang
2016-01-01
The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction. PMID:26761013
Convergence of Vehicle and Infrastructure Data for Traffic and Demand Management
DOE Office of Scientific and Technical Information (OSTI.GOV)
Young, Stanley E.
The increasing availability of highly granular, vehicle trajectory data combined with ever increasing stores of roadway sensor data has provided unparalleled observability into the operation of our urban roadway networks. These data sources are quickly moving from research and prototype environments into full-scale commercial deployment and data offerings. The observability gained allows for increased control opportunities to enhance transportation mobility, safety and energy efficiency. The National Renewable Energy Laboratory (NREL) is involved in three initiatives to leverage these data for positive outcomes: 1) In 2015 NREL, in cooperation with industry and university partners, was awarded an ARPA-E research grant tomore » research a control architecture to incentivize individual travelers toward more sustainable travel behavior. Based on real-time data on the traveler's destination and state of the system, the traveler is presented with route and/or mode choices and offered incentives to accept sustainable alternatives over less-sustainable ones. The project tests the extent to which small incentives can influence, or tip the balance toward more sustainable travel behavior. 2) Although commercial sources of travel time and speed have emerged in recent years based on vehicle probe data, volume estimates continue to rely primarily on historical count data factored for the time of day, day of week, and season of year. Real-time volume flows would enable better tools, simulation in the loop, and ultimately more effective control outcomes. NREL in cooperation with the University of Maryland and industry traffic data providers (INRIX, HERE and TomTom), are attempting to accelerate the timeframe to a viable real-time vehicle volume data feed based on probe data. 3) Signal control on urban arterials for years has had to rely on models rather than measured data to assess performance. High-resolution controller data and low-cost re-identification data now allows for direct measurement of the quality of progression along a corridor. Though still requiring an investment in equipment and communications, these data sources are transforming traffic signal management to a data driven, performance management basis. Ever increasing availability of granular GPS trace data from automobiles may allow for assessment of traffic signal performance, allowing for signal optimization while minimizing the investment in additional sensors and communication infrastructure.« less
Testing simple deceptive honeypot tools
NASA Astrophysics Data System (ADS)
Yahyaoui, Aymen; Rowe, Neil C.
2015-05-01
Deception can be a useful defensive technique against cyber-attacks; it has the advantage of unexpectedness to attackers and offers a variety of tactics. Honeypots are a good tool for deception. They act as decoy computers to confuse attackers and exhaust their time and resources. This work tested the effectiveness of two free honeypot tools in real networks by varying their location and virtualization, and the effects of adding more deception to them. We tested a Web honeypot tool, Glastopf and an SSH honeypot tool Kippo. We deployed the Web honeypot in both a residential network and our organization's network and as both real and virtual machines; the organization honeypot attracted more attackers starting in the third week. Results also showed that the virtual honeypots received attacks from more unique IP addresses. They also showed that adding deception to the Web honeypot, in the form of additional linked Web pages and interactive features, generated more interest by attackers. For the purpose of comparison, we used examined log files of a legitimate Web-site www.cmand.org. The traffic distributions for the Web honeypot and the legitimate Web site showed similarities (with much malicious traffic from Brazil), but the SSH honeypot was different (with much malicious traffic from China). Contrary to previous experiments where traffic to static honeypots decreased quickly, our honeypots received increasing traffic over a period of three months. It appears that both honeypot tools are useful for providing intelligence about cyber-attack methods, and that additional deception is helpful.
Pachón, Jorge E; Sarmiento, Hugo; Hoshiko, Tomomi
2013-01-01
Assessing the risk to health by inhaling particles and particle-bound PAH during daily commuting along a high traffic flow route/corridor in Bogotá. A van was equipped with a PAS2000 photo-electric sensor for real-time measurement of particle-bound PAH and a Dust Trakfor monitoring PM10 concentration; it drove along typical commuting routes in the city. Exposure to particles and particle-bound PAH was assessed by using an inhalation intake model. A similar trend was observed for both PM10 and PAH concentration, indicating that traffic was the same source for both contaminants. Extreme PM10 and PAH inhalation concentrations were recorded every time direct bus and microbus emissions were measured by the van. Inhalation model results indicated that exposure was significantly greater when using a venues having mixed traffic use (i.e. buses, microbuses, passenger vehicles, motorcycles) compared to using roads where the TransMilenio system (articulated buses) had been implemented. The results may support evaluating bus drivers, commuters and bike users' exposure to toxic compounds in the city.
Green supply chain: Simulating road traffic congestion
NASA Astrophysics Data System (ADS)
Jalal, Muhammad Zulqarnain Hakim Abd; Nawawi, Mohd Kamal Mohd; Laailatul Hanim Mat Desa, Wan; Khalid, Ruzelan; Khalid Abduljabbar, Waleed; Ramli, Razamin
2017-09-01
With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is present.
Comparative advantage between traditional and smart navigation systems
NASA Astrophysics Data System (ADS)
Shin, Jeongkyu; Kim, Pan-Jun; Kim, Seunghwan
2013-03-01
The smart navigation system that refers to real-time traffic data is believed to be superior to traditional navigation systems. To verify this belief, we created an agent-based traffic model and examined the effect of changing market share of the traditional shortest-travel-time algorithm based navigation and the smart navigation system. We tested our model on the grid and actual metropolitan road network structures. The result reveals that the traditional navigation system have better performance than the smart one as the market share of the smart navigation system exceeds a critical value, which is contrary to conventional expectation. We suggest that the superiority inversion between agent groups is strongly related to the traffic weight function form, and is general. We also found that the relationship of market share, traffic flow density and travel time is determined by the combination of congestion avoidance behavior of the smartly navigated agents and the inefficiency of shortest-travel-time based navigated agents. Our results can be interpreted with the minority game and extended to the diverse topics of opinion dynamics. This work was supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology(No. 2010-0018847).
A Fast MAC-Layer Handover for an IEEE 802.16e-Based WMAN
NASA Astrophysics Data System (ADS)
Ray, Sayan K.; Pawlikowski, Krzysztof; Sirisena, Harsha
We propose a modification of the IEEE 802.16e hard handover (HHO) procedure, which significantly reduces the handover latency constraint of the original HHO procedure in IEEE 802.16e networks. It allows a better handling of the delay-sensitive traffic by avoiding unnecessary time-consuming scanning and synchronization activity as well as simplifies the network re-entry procedure. With the help of the backhaul network, it reduces the number of control messages in the original handover policy, making the handover latency acceptable also for real-time streaming traffic. Preliminary performance evaluation studies show that the modified handover procedure is able to reduce the total handover latency by about 50%.
Contrail Tracking and ARM Data Product Development
NASA Technical Reports Server (NTRS)
Duda, David P.; Russell, James, III
2005-01-01
A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.
Automated feedback to foster safe driving in young drivers: phase 2 : traffic tech.
DOT National Transportation Integrated Search
2015-12-01
Intelligent Speed Adaptation (ISA) provides a promising approach to reduce speeding. A core principle of ISA is real-time feedback that lets drivers know when they are driving over the speed limit. The overall goal of the study was to provide insight...
DOT National Transportation Integrated Search
2000-01-01
A multi-year project was initiated to introduce autonomous vehicles in the University of Central Florida (UCF) Driving Simulator for real-time interaction with the simulator vehicle. This report describes the progress during the second year. In the f...
Impact of shutting down en route primary radars within CONUS interior
DOT National Transportation Integrated Search
1993-06-01
The Impact on the Air Traffic Control (ATC) operations resulting from the shutdown of alt en route primary radars : (except for ARSR-4s) within the CONUS interior will result in loss of real-time weather data and aircraft skin tracking, : over 33 per...
Cellular automata model for use with real freeway data
DOT National Transportation Integrated Search
2002-01-01
The exponential rate of increase in freeway traffic is expanding the need for accurate and : realistic methods to model and predict traffic flow. Traffic modeling and simulation facilitates an : examination of both microscopic and macroscopic views o...
Scripted drives: A robust protocol for generating exposures to traffic-related air pollution
NASA Astrophysics Data System (ADS)
Patton, Allison P.; Laumbach, Robert; Ohman-Strickland, Pamela; Black, Kathy; Alimokhtari, Shahnaz; Lioy, Paul J.; Kipen, Howard M.
2016-10-01
Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 μg/m3 PM2.5, 40 000 particles/cm3, 0.3 ppm CO, 4 μg/m3 BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used to generate reasonably consistent in-cabin increments of exposure to traffic-related air pollution.
Scripted drives: A robust protocol for generating exposures to traffic-related air pollution
Patton, Allison P.; Laumbach, Robert; Ohman-Strickland, Pamela; Black, Kathy; Alimokhtari, Shahnaz; Lioy, Paul; Kipen, Howard M.
2016-01-01
Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 μg/m3 PM2.5, 40 000 particles/cm3, 0.3 ppm CO, 4 μg/m3 BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used for generating reasonably consistent in-cabin increments of exposure to traffic-related air pollution. PMID:27642251
Automatic Recognition of Road Signs
NASA Astrophysics Data System (ADS)
Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato
2002-11-01
The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.
NASA Astrophysics Data System (ADS)
Davis, L. C.
2015-03-01
The Texas A&M Transportation Institute estimated that traffic congestion cost the United States 121 billion in 2011 (the latest data available). The cost is due to wasted time and fuel. In addition to accidents and road construction, factors contributing to congestion include large demand, instability of high-density free flow and selfish behavior of drivers, which produces self-organized traffic bottlenecks. Extensive data collected on instrumented highways in various countries have led to a better understanding of traffic dynamics. From these measurements, Boris Kerner and colleagues developed a new theory called three-phase theory. They identified three major phases of flow observed in the data: free flow, synchronous flow and wide moving jams. The intermediate phase is called synchronous because vehicles in different lanes tend to have similar velocities. This congested phase, characterized by lower velocities yet modestly high throughput, frequently occurs near on-ramps and lane reductions. At present there are only two widely used methods of congestion mitigation: ramp metering and the display of current travel-time information to drivers. To find more effective methods to reduce congestion, researchers perform large-scale simulations using models based on the new theories. An algorithm has been proposed to realize Wardrop equilibria with real-time route information. Such equilibria have equal travel time on alternative routes between a given origin and destination. An active area of current research is the dynamics of connected vehicles, which communicate wirelessly with other vehicles and the surrounding infrastructure. These systems show great promise for improving traffic flow and safety.
Neural networks for continuous online learning and control.
Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long
2006-11-01
This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.
Review of modelling air pollution from traffic at street-level - The state of the science.
Forehead, H; Huynh, N
2018-06-13
Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses. Copyright © 2018 Elsevier Ltd. All rights reserved.
A View from the Inside: Collaborating with Students to Flip the Classroom in Real Time
ERIC Educational Resources Information Center
Zavattaro, Staci M.; Kus, Kristina; Lademann, Jason; Peeple-Briggs, Elizabeth
2018-01-01
This article details decisions made to flip a small, public administration graduate-level course in real time. Interweaving student feedback with instructor notes and reflections gives a unique, personal look into a scenario-based course that changed weekly. We detail this dynamism, highlighting successes and failures in flipping the classroom.…
Up-Skilling through E-Collaboration
ERIC Educational Resources Information Center
Huc-Hepher, Saskia; Barros, Elsa Huertas
2016-01-01
This paper presents an e-collaboration project involving real-time videoconferencing exchanges between students from the University of Westminster and the Université Catholique de Lille. Students drew on diverse resources, including written quantitative data and first-hand qualitative data in French/English to complete weekly tasks. Follow-up work…
Watershed Central: Dynamic Collaboration for Improving Watershed Management (Philadelphia)
The Watershed Central web and wiki pages will be presented and demonstrated real-time as part of the overview of Web 2.0 collaboration tools for watershed management. The presentation portion will discuss how EPA worked with watershed practitioners and within the Agency to deter...
Collaborative Resource Allocation
NASA Technical Reports Server (NTRS)
Wang, Yeou-Fang; Wax, Allan; Lam, Raymond; Baldwin, John; Borden, Chester
2007-01-01
Collaborative Resource Allocation Networking Environment (CRANE) Version 0.5 is a prototype created to prove the newest concept of using a distributed environment to schedule Deep Space Network (DSN) antenna times in a collaborative fashion. This program is for all space-flight and terrestrial science project users and DSN schedulers to perform scheduling activities and conflict resolution, both synchronously and asynchronously. Project schedulers can, for the first time, participate directly in scheduling their tracking times into the official DSN schedule, and negotiate directly with other projects in an integrated scheduling system. A master schedule covers long-range, mid-range, near-real-time, and real-time scheduling time frames all in one, rather than the current method of separate functions that are supported by different processes and tools. CRANE also provides private workspaces (both dynamic and static), data sharing, scenario management, user control, rapid messaging (based on Java Message Service), data/time synchronization, workflow management, notification (including emails), conflict checking, and a linkage to a schedule generation engine. The data structure with corresponding database design combines object trees with multiple associated mortal instances and relational database to provide unprecedented traceability and simplify the existing DSN XML schedule representation. These technologies are used to provide traceability, schedule negotiation, conflict resolution, and load forecasting from real-time operations to long-range loading analysis up to 20 years in the future. CRANE includes a database, a stored procedure layer, an agent-based middle tier, a Web service wrapper, a Windows Integrated Analysis Environment (IAE), a Java application, and a Web page interface.
DOT National Transportation Integrated Search
2016-05-01
In phase two of this project, the UCF team further developed the DSS to automate selection of FYA left-turn modes based on traffic volumes at intersections acquired in real time from existing sensors.
DOT National Transportation Integrated Search
2017-04-01
Vianey Leos Barajas (orcid.org/0000-0001-8016-773X), Zhonglei Wang (orcid.org/0000-0001-6712-0750), Mark Kaiser (orcid.org/0000-0003-0449-0388), and Zhengyuan Zhu (orcid.org/0000-0002-2266-0646) : This report describes two related projects, the secon...
DOT National Transportation Integrated Search
2017-07-01
Instances of fog or fog enhanced with smoke (non-photochemical smog) routinely reduce driver visibility on roadways throughout Georgia. Georgia has the fifth highest reduced-visibilityassociated crash frequency of any state. This report provides a...
Mediated Communication as a Component of Distance Education.
ERIC Educational Resources Information Center
Holmberg, Borje, Ed.
The concern of this booklet is with "two-way traffic", or real communication, in distance education. Following an introduction by Holmberg, the following papers appear: "Some Thoughts on Delayed and Immediate Feedback" (Diehl); "The Effect of Field Scoring on Time to Completion in Career Development Courses" (Diehl);…
Real-time assessment of fog-related crashes using airport weather data: a feasibility analysis.
Ahmed, Mohamed M; Abdel-Aty, Mohamed; Lee, Jaeyoung; Yu, Rongjie
2014-11-01
The effect of reduction of visibility on crash occurrence has recently been a major concern. Although visibility detection systems can help to mitigate the increased hazard of limited-visibility, such systems are not widely implemented and many locations with no systems are experiencing considerable number of fatal crashes due to reduction in visibility caused by fog and inclement weather. On the other hand, airports' weather stations continuously monitor all climate parameters in real-time, and the gathered data may be utilized to mitigate the increased risk for the adjacent roadways. This study aims to examine the viability of using airport weather information in real-time road crash risk assessment in locations with recurrent fog problems. Bayesian logistic regression was utilized to link six years (2005-2010) of historical crash data to real-time weather information collected from eight airports in the State of Florida, roadway characteristics and aggregate traffic parameters. The results from this research indicate that real-time weather data collected from adjacent airports are good predictors to assess increased risk on highways. Copyright © 2014 Elsevier Ltd. All rights reserved.
Controlling factors of the parental safety perception on children's travel mode choice.
Nevelsteen, Kristof; Steenberghen, Thérèse; Van Rompaey, Anton; Uyttersprot, Liesbeth
2012-03-01
The travel mode of children changed significantly over the last 20 years, with a decrease of children travelling as pedestrians or cyclists. This study focuses on six to twelve year old children. Parents determine to a large extent the mode choice of children in this age category. Based on the analysis of an extensive survey, the research shows that traffic infrastructure has a significant impact on parental decision making concerning children's travel mode choice, by affecting both the real and the perceived traffic safety. Real traffic safety is quantified in terms of numbers of accidents and road infrastructure. For the perceived traffic safety a parental allowance probability is calculated per road type to show that infrastructure characteristics influence parental decision making on the children's mode choice. A binary logistic model shows that this allowance is determined by age, gender and traffic infrastructure near the child's home or near destinations frequently visited by children. Since both real and perceived traffic safety are influenced by infrastructure characteristics, a spatial analysis of parental perception and accident statistics can be used to indicate the locations where infrastructure improvements will be most effective to increase the number of children travelling - safely - as pedestrians or cyclists. Copyright © 2011 Elsevier Ltd. All rights reserved.
Airborne Four-Dimensional Flight Management in a Time-based Air Traffic Control Environment
NASA Technical Reports Server (NTRS)
Williams, David H.; Green, Steven M.
1991-01-01
Advanced Air Traffic Control (ATC) systems are being developed which contain time-based (4D) trajectory predictions of aircraft. Airborne flight management systems (FMS) exist or are being developed with similar 4D trajectory generation capabilities. Differences between the ATC generated profiles and those generated by the airborne 4D FMS may introduce system problems. A simulation experiment was conducted to explore integration of a 4D equipped aircraft into a 4D ATC system. The NASA Langley Transport Systems Research Vehicle cockpit simulator was linked in real time to the NASA Ames Descent Advisor ATC simulation for this effort. Candidate procedures for handling 4D equipped aircraft were devised and traffic scenarios established which required time delays absorbed through speed control alone or in combination with path stretching. Dissimilarities in 4D speed strategies between airborne and ATC generated trajectories were tested in these scenarios. The 4D procedures and FMS operation were well received by airline pilot test subjects, who achieved an arrival accuracy at the metering fix of 2.9 seconds standard deviation time error. The amount and nature of the information transmitted during a time clearance were found to be somewhat of a problem using the voice radio communication channel. Dissimilarities between airborne and ATC-generated speed strategies were found to be a problem when the traffic remained on established routes. It was more efficient for 4D equipped aircraft to fly trajectories with similar, though less fuel efficient, speeds which conform to the ATC strategy. Heavy traffic conditions, where time delays forced off-route path stretching, were found to produce a potential operational benefit of the airborne 4D FMS.
Study on Brain Injury Biomechanics Based on the Real Pedestrian Traffic Accidents
NASA Astrophysics Data System (ADS)
Feng, Chengjian; Yin, Zhiyong
This paper aimed to research the dynamic response and injury mechanisms of head based on real pedestrian traffic accidents with video. The kinematics of head contact with the vehicle was reconstructed by using multi-body dynamics models. These calculated parameters such as head impact velocity and impact location and head orientation were applied to the THUMS-4 FE head model as initial conditions. The intracranial pressure and stress of brain were calculated from simulations of head contact with the vehicle. These results were consistent with that of others. It was proved that real traffic accidents combined with simulation analysis can be used to study head injury biomechanics. Increasing in the number of cases, a tolerance limit of brain injury will be put forward.
NASA Technical Reports Server (NTRS)
Idris, Husni; Shen, Ni; Wing, David J.
2011-01-01
The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.
Decision-making tool for applying adaptive traffic control systems : final report.
DOT National Transportation Integrated Search
2016-03-01
Adaptive traffic signal control technologies have been increasingly deployed in real world situations. The objective of this project was to develop a decision-making tool to guide traffic engineers and decision-makers who must decide whether or not a...
A Comparison of Center/TRACON Automation System and Airline Time of Arrival Predictions
NASA Technical Reports Server (NTRS)
Heere, Karen R.; Zelenka, Richard E.
2000-01-01
Benefits from information sharing between an air traffic service provider and a major air carrier are evaluated. Aircraft arrival time schedules generated by the NASA/FAA Center/TRACON Automation System (CTAS) were provided to the American Airlines System Operations Control Center in Fort Worth, Texas, during a field trial of a specialized CTAS display. A statistical analysis indicates that the CTAS schedules, based on aircraft trajectories predicted from real-time radar and weather data, are substantially more accurate than the traditional airline arrival time estimates, constructed from flight plans and en route crew updates. The improvement offered by CTAS is especially advantageous during periods of heavy traffic and substantial terminal area delay, allowing the airline to avoid large predictive errors with serious impact on the efficiency and profitability of flight operations.
ERIC Educational Resources Information Center
Huang, Xi
2018-01-01
Computer-supported collaborative learning facilitates the extension of second language acquisition into social practice. Studies on its achievement effects speak directly to the pedagogical notion of treating communicative practice in synchronous computer-mediated communication (SCMC): real-time communication that takes place between human beings…
Correcting Spellings in Second Language Learners' Computer-Assisted Collaborative Writing
ERIC Educational Resources Information Center
Musk, Nigel
2016-01-01
The present study uses multimodal conversation analysis to examine how pupils studying English as a foreign language make spelling corrections in real time while doing collaborative computer-assisted project work. Unlike most previous related investigations, this study focuses on the "process" rather than evaluating the final…
Expanding Our Understanding of the Inquiry Process
ERIC Educational Resources Information Center
Stafford, Tish; Stemple, Jennifer
2011-01-01
School librarians know the importance of collaboration. They cannot run effective school library programs unless they work closely with classroom teachers. They have learned that deep collaboration is a fluid process that evolves over time. Only as connections are made and relationships are forged can real instructional progress occur. Yet it…
Real-Time Collaboration of Virtual Laboratories through the Internet
ERIC Educational Resources Information Center
Jara, Carlos A.; Candelas, Francisco A.; Torres, Fernando; Dormido, Sebastian; Esquembre, Francisco; Reinoso, Oscar
2009-01-01
Web-based learning environments are becoming increasingly popular in higher education. One of the most important web-learning resources is the virtual laboratory (VL), which gives students an easy way for training and learning through the Internet. Moreover, on-line collaborative communication represents a practical method to transmit the…
Whose Place Is This Anyway? Reflecting upon Hospitality and Higher Education
ERIC Educational Resources Information Center
Loewen, Nathan
2016-01-01
In this essay I propose that using online tools to connect geographically-separated classrooms for real-time collaborative learning experiences may effectively develop intercultural competency in the religious studies classroom. I explore personal examples from several international and inter-institutional collaborations with Jacques Derrida's…
A Flight Deck Decision Support Tool for Autonomous Airborne Operations
NASA Technical Reports Server (NTRS)
Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin
2002-01-01
NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.
Development of active traffic management strategies for Minnesota freeway corridors : final report.
DOT National Transportation Integrated Search
2015-06-01
In this study, the effectiveness of the I-35W variable advisory speed limit system on the improvement of the traffic : flow was evaluated with the real traffic data. The analysis results indicate there was significant reduction in the : average maxim...
Evaluation of a Traffic Sign Detector by Synthetic Image Data for Advanced Driver Assistance Systems
NASA Astrophysics Data System (ADS)
Hanel, A.; Kreuzpaintner, D.; Stilla, U.
2018-05-01
Recently, several synthetic image datasets of street scenes have been published. These datasets contain various traffic signs and can therefore be used to train and test machine learning-based traffic sign detectors. In this contribution, selected datasets are compared regarding ther applicability for traffic sign detection. The comparison covers the process to produce the synthetic images and addresses the virtual worlds, needed to produce the synthetic images, and their environmental conditions. The comparison covers variations in the appearance of traffic signs and the labeling strategies used for the datasets, as well. A deep learning traffic sign detector is trained with multiple training datasets with different ratios between synthetic and real training samples to evaluate the synthetic SYNTHIA dataset. A test of the detector on real samples only has shown that an overall accuracy and ROC AUC of more than 95 % can be achieved for both a small rate of synthetic samples and a large rate of synthetic samples in the training dataset.
ERIC Educational Resources Information Center
Capobianco, Stephen; Rubaii, Nadia; Líppez-De Castro, Sebastian
2016-01-01
In this paper, we outline the structure, goals, and lessons from our international teaching and learning collaboration in the spring 2015 semester. We took two public affairs courses with students in a U.S. and a Colombian university and combined them into a single hybrid course with the use of technology. The main goals of the course were to…
Transferability and robustness of real-time freeway crash risk assessment.
Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius
2013-09-01
This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomas, Kenneth; Oxstrand, Johanna
The Digital Architecture effort is a part of the Department of Energy (DOE) sponsored Light-Water Reactor Sustainability (LWRS) Program conducted at Idaho National Laboratory (INL). The LWRS program is performed in close collaboration with industry research and development (R&D) programs that provides the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants (NPPs). One of the primary missions of the LWRS program is to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. Therefore,more » a major objective of the LWRS program is the development of a seamless digital environment for plant operations and support by integrating information from plant systems with plant processes for nuclear workers through an array of interconnected technologies. In order to get the most benefits of the advanced technology suggested by the different research activities in the LWRS program, the nuclear utilities need a digital architecture in place to support the technology. A digital architecture can be defined as a collection of information technology (IT) capabilities needed to support and integrate a wide-spectrum of real-time digital capabilities for nuclear power plant performance improvements. It is not hard to imagine that many processes within the plant can be largely improved from both a system and human performance perspective by utilizing a plant wide (or near plant wide) wireless network. For example, a plant wide wireless network allows for real time plant status information to easily be accessed in the control room, field workers’ computer-based procedures can be updated based on the real time plant status, and status on ongoing procedures can be incorporated into smart schedules in the outage command center to allow for more accurate planning of critical tasks. The goal of the digital architecture project is to provide a long-term strategy to integrate plant systems, plant processes, and plant workers. This include technologies to improve nuclear worker efficiency and human performance; to offset a range of plant surveillance and testing activities with new on-line monitoring technologies; improve command, control, and collaboration in settings such as outage control centers and work execution centers; and finally to improve operator performance with new operator aid technologies for the control room. The requirements identified through the activities in the Digital Architecture project will be used to estimate the amount of traffic on the network and hence estimating the minimal bandwidth needed.« less
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-09
... Highways Action Response Team will provide real-time traffic information to motorists through dynamic... 400-mile radius of the city, with a large portion traveling the I-95 corridor. It is anticipated that... Interstate route in the region, will remain open during the time period of the event. There are five...
Does Seeing One Another's Gaze Affect Group Dialogue? A Computational Approach
ERIC Educational Resources Information Center
Schneider, Bertrand; Pea, Roy
2015-01-01
In a previous study, we found that real-time mutual gaze perception (i.e., being able to see the gaze of your partner in real time on a computer screen while solving a learning task) had a positive effect on student collaboration and learning (Schneider & Pea, 2013). The goals of this paper are (1) to explore a variety of computational…
ERIC Educational Resources Information Center
Corsello, Maryann; Sharma, Anu; Jerabek, Angela
2015-01-01
Building Assets Reducing Risks (BARR) is a social emotional model that achieves academic outcomes through combining use of real-time student data with proven relationship-building strategies and intensive teacher collaboration to prevent course failure. BARR is a recipient of US Department of Education "Investing in Innovation (i3)"…
Bernal-Rusiel, Jorge L; Rannou, Nicolas; Gollub, Randy L; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E; Pienaar, Rudolph
2017-01-01
In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView , a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.
Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju
2014-01-01
A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated. PMID:24662407
Real-time state estimation in a flight simulator using fNIRS.
Gateau, Thibault; Durantin, Gautier; Lancelot, Francois; Scannella, Sebastien; Dehais, Frederic
2015-01-01
Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot's instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot's mental state matched significantly better than chance with the pilot's real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development.
CTAS: Computer intelligence for air traffic control in the terminal area
NASA Technical Reports Server (NTRS)
Erzberger, Heinz
1992-01-01
A system for the automated management and control of arrival traffic, referred to as the Center-TRACON Automation System (CTAS), has been designed by the ATC research group at NASA Ames research center. In a cooperative program, NASA and the FAA have efforts underway to install and evaluate the system at the Denver and Dallas/Ft. Worth airports. CTAS consists of three types of integrated tools that provide computer-generated intelligence for both Center and TRACON controllers to guide them in managing and controlling arrival traffic efficiently. One tool, the Traffic Management Advisor (TMA), establishes optimized landing sequences and landing times for aircraft arriving in the center airspace several hundred miles from the airport. In TRACON, TMA frequencies missed approach aircraft and unanticipated arrivals. Another tool, the Descent Advisor (DA), generates clearances for the center controllers handling at crossing times provided by TMA. In the TRACON, the final approach spacing tool (FAST) provides heading and speed clearances that produce and accurately spaced flow of aircraft on the final approach course. A data base consisting of aircraft performance models, airline preferred operational procedures and real time wind measurements contribute to the effective operation of CTAS. Extensive simulator evaluations of CTAS have demonstrated controller acceptance, delay reductions, and fuel savings.
[Increasing Number of Road Traffic Fatalities in Germany - Turnaround or Snap-Shot].
Brand, S; Schmucker, U; Lob, G; Haasper, C; Juhra, C; Hell, W; Rieth, P; Matthes, G
2017-04-01
Introduction: For the first time since 20 years, the number of road accident fatalities in 2011 increased on German roads compared to earlier periods. Methods and Results: The presented paper submitted by the expert group for accident prevention investigates and discusses possible reasons for the observed increase in road traffic fatalities. Results: Climate changes as well as changes in economic environment, and technological progress in car and passenger safety are identified as possible reasons for the observed increase. Discussion: Mentioning the "Decade of Action for Road Safety" initiated by the UNO and coordinated by the WHO, the overall goal is a worldwide reduction of accident related road fatalities. But prognostic calculations predict an asymptotic approximation to a limit of road fatalities. To achieve a reduction by half until 2020 intense collaboration and disproportional expenditure are necessary. Conclusion: From the authors' point of view the current increase of traffic fatalities in Germany is rated as a snapshot rather than a turnaround. Georg Thieme Verlag KG Stuttgart · New York.
Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport
NASA Technical Reports Server (NTRS)
Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon C.; Zhu, Zhifan; Jeong, Myeongsook; Kim, Hyounkong; Oh, Eunmi; Hong, Sungkwon
2017-01-01
This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).
Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport
NASA Technical Reports Server (NTRS)
Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon Chul; Zhu, Zhifan; Jeong, Myeong-Sook; Kim, Hyoun Kyoung; Oh, Eunmi; Hong, Sungkwon
2017-01-01
This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).
Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions.
Zambrano-Martinez, Jorge Luis; Calafate, Carlos T; Soler, David; Cano, Juan-Carlos
2017-12-15
Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.
GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harshaw, Chris R; Bridges, Robert A; Iannacone, Michael D
This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called \\textit{GraphPrints}. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets\\textemdash small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84\\% at the time-interval level, and 0.05\\% at the IP-level with 100\\% truemore » positive rates at both.« less
Analysis of adaptive algorithms for an integrated communication network
NASA Technical Reports Server (NTRS)
Reed, Daniel A.; Barr, Matthew; Chong-Kwon, Kim
1985-01-01
Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.
Boele-Vos, M J; Commandeur, J J F; Twisk, D A M
2017-08-01
To improve cycling safety, insight is required into the factors that contribute to road safety of older cyclists. From the wide range of possible factors, this paper addresses the role of physical effort on mental workload of cyclists with the aim to investigate whether physical effort affects mental workload of cyclists in real traffic in a field experiment. Two instrumented bicycles, a conventional bicycle and a pedelec, were used. Mental workload of cyclists in two age groups - 30-45 years and 65 years and over - was measured by means of a secondary cognitive task requiring the detection and reaction to visual stimuli on a cycle route that varied in physical effort and task complexity. We expected physical effort to impair performance on the secondary task in complex traffic sections and not in simple sections, and that this impairment would be greater for older cyclists because of age related reduced muscle strength than for younger cyclists. We expected this impairment to be smaller if a pedelec was used. If such would be the case, this would indicate pedelecs to be beneficial for this older age group, because of a lower mental workload. Our study confirmed that increased physical effort in complex traffic sections deteriorated the detection of relevant stimuli in both age groups. Overall, older cyclists had longer reaction times and lower hit rates than younger cyclists. Mental workloads of cyclists are basically the same when cycling on a conventional bicycle or on a pedelec. In theory, pedelecs may be beneficial to reduce physical effort in cycling in order to maintain enough mental capacity to handle complex traffic situations. However, this study did not demonstrate these benefits. As pedelecs are often used for longer trips, by elderly with low muscle strength, future studies should also explore the effect of higher physical effort over longer periods of time, and also specifically in elderly with low muscle strength. Copyright © 2016 Elsevier Ltd. All rights reserved.
Coordinated traffic incident management using the I-Net embedded sensor architecture
NASA Astrophysics Data System (ADS)
Dudziak, Martin J.
1999-01-01
The I-Net intelligent embedded sensor architecture enables the reconfigurable construction of wide-area remote sensing and data collection networks employing diverse processing and data acquisition modules communicating over thin- server/thin-client protocols. Adaptive initially for operation using mobile remotely-piloted vehicle platforms such as small helicopter robots such as the Hornet and Ascend-I, the I-Net architecture lends itself to a critical problem in the management of both spontaneous and planned traffic congestion and rerouting over major interstate thoroughfares such as the I-95 Corridor. Pre-programmed flight plans and ad hoc operator-assisted navigation of the lightweight helicopter, using an auto-pilot and gyroscopic stabilization augmentation units, allows daytime or nighttime over-the-horizon flights of the unit to collect and transmit real-time video imagery that may be stored or transmitted to other locations. With on-board GPS and ground-based pattern recognition capabilities to augment the standard video collection process, this approach enables traffic management and emergency response teams to plan and assist real-time in the adjustment of traffic flows in high- density or congested areas or during dangerous road conditions such as during ice, snow, and hurricane storms. The I-Net architecture allows for integration of land-based and roadside sensors within a comprehensive automated traffic management system with communications to and form an airborne or other platform to devices in the network other than human-operated desktop computers, thereby allowing more rapid assimilation and response for critical data. Experiments have been conducted using several modified platforms and standard video and still photographic equipment. Current research and development is focused upon modification of the modular instrumentation units in order to accommodate faster loading and reloading of equipment onto the RPV, extension of the I-Net architecture to enable RPV-to-RPV signaling and control, and refinement of safety and emergency mechanisms to handle RPV mechanical failure during flight.
Ultra-Scale Computing for Emergency Evacuation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhaduri, Budhendra L; Nutaro, James J; Liu, Cheng
2010-01-01
Emergency evacuations are carried out in anticipation of a disaster such as hurricane landfall or flooding, and in response to a disaster that strikes without a warning. Existing emergency evacuation modeling and simulation tools are primarily designed for evacuation planning and are of limited value in operational support for real time evacuation management. In order to align with desktop computing, these models reduce the data and computational complexities through simple approximations and representations of real network conditions and traffic behaviors, which rarely represent real-world scenarios. With the emergence of high resolution physiographic, demographic, and socioeconomic data and supercomputing platforms, itmore » is possible to develop micro-simulation based emergency evacuation models that can foster development of novel algorithms for human behavior and traffic assignments, and can simulate evacuation of millions of people over a large geographic area. However, such advances in evacuation modeling and simulations demand computational capacity beyond the desktop scales and can be supported by high performance computing platforms. This paper explores the motivation and feasibility of ultra-scale computing for increasing the speed of high resolution emergency evacuation simulations.« less
a Collaborative Cyberinfrastructure for Earthquake Seismology
NASA Astrophysics Data System (ADS)
Bossu, R.; Roussel, F.; Mazet-Roux, G.; Lefebvre, S.; Steed, R.
2013-12-01
One of the challenges in real time seismology is the prediction of earthquake's impact. It is particularly true for moderate earthquake (around magnitude 6) located close to urbanised areas, where the slightest uncertainty in event location, depth, magnitude estimates, and/or misevaluation of propagation characteristics, site effects and buildings vulnerability can dramatically change impact scenario. The Euro-Med Seismological Centre (EMSC) has developed a cyberinfrastructure to collect observations from eyewitnesses in order to provide in-situ constraints on actual damages. This cyberinfrastructure takes benefit of the natural convergence of earthquake's eyewitnesses on EMSC website (www.emsc-csem.org), the second global earthquake information website within tens of seconds of the occurrence of a felt event. It includes classical crowdsourcing tools such as online questionnaires available in 39 languages, and tools to collect geolocated pics. It also comprises information derived from the real time analysis of the traffic on EMSC website, a method named flashsourcing; In case of a felt earthquake, eyewitnesses reach EMSC website within tens of seconds to find out the cause of the shaking they have just been through. By analysing their geographical origin through their IP address, we automatically detect felt earthquakes and in some cases map the damaged areas through the loss of Internet visitors. We recently implemented a Quake Catcher Network (QCN) server in collaboration with Stanford University and the USGS, to collect ground motion records performed by volunteers and are also involved in a project to detect earthquakes from ground motions sensors from smartphones. Strategies have been developed for several social media (Facebook, Twitter...) not only to distribute earthquake information, but also to engage with the Citizens and optimise data collection. A smartphone application is currently under development. We will present an overview of this cyberinfrastructure, as well as the way the classical reliability issue of crowdsourced data has been addressed in this specific case through recent examples. Finally, we will illustrate what can be learnt through these experiments on the way people react when facing the ground shaking and possible implication for efficient awareness initiatives.
Medical-Grade Channel Access and Admission Control in 802.11e EDCA for Healthcare Applications
Son, Sunghwa; Park, Kyung-Joon; Park, Eun-Chan
2016-01-01
In this paper, we deal with the problem of assuring medical-grade quality of service (QoS) for real-time medical applications in wireless healthcare systems based on IEEE 802.11e. Firstly, we show that the differentiated channel access of IEEE 802.11e cannot effectively assure medical-grade QoS because of priority inversion. To resolve this problem, we propose an efficient channel access algorithm. The proposed algorithm adjusts arbitrary inter-frame space (AIFS) in the IEEE 802.11e protocol depending on the QoS measurement of medical traffic, to provide differentiated near-absolute priority for medical traffic. In addition, based on rigorous capacity analysis, we propose an admission control scheme that can avoid performance degradation due to network overload. Via extensive simulations, we show that the proposed mechanism strictly assures the medical-grade QoS and improves the throughput of low-priority traffic by more than several times compared to the conventional IEEE 802.11e. PMID:27490666
Sciammas, Charlie; Seto, Edmund; Bhatia, Rajiv; Rivard, Tom
2009-01-01
Health impacts on neighborhood residents from transportation systems can be an environmental justice issue. To assess the effects of transportation planning decisions, including the construction of an intraurban freeway, on residents of the Excelsior neighborhood in southeast San Francisco, PODER (People Organizing to Demand Environmental and Economic Rights), a local grassroots environmental justice organization; the San Francisco Department of Public Health; and the University of California, Berkeley, collaborated on participatory research. We used our findings regarding traffic-related exposures and health hazards in the area to facilitate community education and action to address transportation-related health burdens on neighborhood residents. PMID:19890147
Barrois, Sebastian; Wagenknecht, Hans-Achim
2013-05-21
The combination of thiazole orange (TO) and thiazole red (TR) as an internal pair of fluorescent DNA base surrogates ("DNA traffic lights") allows us to follow at least two consecutive DNA strand displacements in real time through a distinct fluorescence colour change from green to red and vice versa.
Fu, Yunhai; Ma, Lin; Xu, Yubin
2015-01-01
In spectrum aggregation (SA), two or more component carriers (CCs) of different bandwidths in different bands can be aggregated to support a wider transmission bandwidth. The scheduling delay is the most important design constraint for the broadband wireless trunking (BWT) system, especially in the cognitive radio (CR) condition. The current resource scheduling schemes for spectrum aggregation become questionable and are not suitable for meeting the challenge of the delay requirement. Consequently, the authors propose a novel component carrier configuration and switching scheme for real-time traffic (RT-CCCS) to satisfy the delay requirement in the CR-based SA system. In this work, the authors consider a sensor-network-assisted CR network. The authors first introduce a resource scheduling structure for SA in the CR condition. Then the proposed scheme is analyzed in detail. Finally, simulations are carried out to verify the analysis on the proposed scheme. Simulation results prove that our proposed scheme can satisfy the delay requirement in the CR-based SA system. PMID:26393594
Li, Jinjian; Dridi, Mahjoub; El-Moudni, Abdellah
2016-01-01
The problem of reducing traffic delays and decreasing fuel consumption simultaneously in a network of intersections without traffic lights is solved by a cooperative traffic control algorithm, where the cooperation is executed based on the connection of Vehicle-to-Infrastructure (V2I). This resolution of the problem contains two main steps. The first step concerns the itinerary of which intersections are chosen by vehicles to arrive at their destination from their starting point. Based on the principle of minimal travel distance, each vehicle chooses its itinerary dynamically based on the traffic loads in the adjacent intersections. The second step is related to the following proposed cooperative procedures to allow vehicles to pass through each intersection rapidly and economically: on one hand, according to the real-time information sent by vehicles via V2I in the edge of the communication zone, each intersection applies Dynamic Programming (DP) to cooperatively optimize the vehicle passing sequence with minimal traffic delays so that the vehicles may rapidly pass the intersection under the relevant safety constraints; on the other hand, after receiving this sequence, each vehicle finds the optimal speed profiles with the minimal fuel consumption by an exhaustive search. The simulation results reveal that the proposed algorithm can significantly reduce both travel delays and fuel consumption compared with other papers under different traffic volumes. PMID:27999333
ERIC Educational Resources Information Center
Parr, Judy M.; Hawe, Eleanor
2017-01-01
This study investigates conditions designed to optimize learning where professionals utilize the expertise and support of one another. It describes a research--practice collaboration to enhance teacher knowledge and practice through peer observation of, and feedback about, classroom practice in writing. A collaboratively designed observation…
A Real-Time Ship Manoeuvring Simulation Study for the Strait of Istanbul (Bosporus)
NASA Astrophysics Data System (ADS)
Sar[Inodot]Öz, Kadir; Kükner, Abdi; Narl[Inodot], Ebru
During the past thirty years, there has been a steady growth in the size and number of ships that use the Strait of Istanbul (Bosporus), which is one of the most difficult, crowded, and potentially dangerous waterways in the world. There have been over two hundred accidents over the past decade resulting in loss of life and serious damage to the environment. Many of the proposed export routes for forthcoming production from the Caspian sea region pass westwards through the Black Sea and the Bosporus en-route to the Mediterranean Sea and world markets. The risks and dangers associated with tanker navigation, maritime accidents and environmental catastrophe are aggravated with the increase in the density of traffic, tanker size and cargo capacity, as well as the nature of the cargo. In order to ease the problem, a Traffic Separation Scheme (TSS) was established and approved by IMO in 1994. This scheme has drastically reduced the number of collisions. However, one-way or two-way suspension of traffic in the Bosporus is inevitable for ships that cannot comply with the TSS because of their type, size or poor manoeuvring characteristics. The selection of size criteria to comply with the TSS has been a matter of discussion. This paper presents the results of a real-time simulation study investigating the manoeuvring performance of large tankers in the Bosporus. The study was conducted with a simulator capable of subjecting a given hull form to any combination of environmental conditions, i.e. wind, current and wave drift forces. The results indicate that, when realistic environmental conditions are taken into account, the size of ships that can navigate safely in compliance with the traffic separation lanes is limited.
Bowman, Ellen Lambert; Liu, Lei
2017-01-01
Virtual reality has great potential in training road safety skills to individuals with low vision but the feasibility of such training has not been demonstrated. We tested the hypotheses that low vision individuals could learn useful skills in virtual streets and could apply them to improve real street safety. Twelve participants, whose vision was too poor to use the pedestrian signals were taught by a certified orientation and mobility specialist to determine the safest time to cross the street using the visual and auditory signals made by the start of previously stopped cars at a traffic-light controlled street intersection. Four participants were trained in real streets and eight in virtual streets presented on 3 projection screens. The crossing timing of all participants was evaluated in real streets before and after training. The participants were instructed to say "GO" at the time when they felt the safest to cross the street. A safety score was derived to quantify the GO calls based on its occurrence in the pedestrian phase (when the pedestrian sign did not show DON'T WALK). Before training, > 50% of the GO calls from all participants fell in the DON'T WALK phase of the traffic cycle and thus were totally unsafe. 20% of the GO calls fell in the latter half of the pedestrian phase. These calls were unsafe because one initiated crossing this late might not have sufficient time to walk across the street. After training, 90% of the GO calls fell in the early half of the pedestrian phase. These calls were safer because one initiated crossing in the pedestrian phase and had at least half of the pedestrian phase for walking across. Similar safety changes occurred in both virtual street and real street trained participants. An ANOVA showed a significant increase of the safety scores after training and there was no difference in this safety improvement between the virtual street and real street trained participants. This study demonstrated that virtual reality-based orientation and mobility training could be as efficient as real street training in improving street safety in individuals with severely impaired vision.
Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity.
Kesting, Arne; Treiber, Martin; Helbing, Dirk
2010-10-13
With an increasing number of vehicles equipped with adaptive cruise control (ACC), the impact of such vehicles on the collective dynamics of traffic flow becomes relevant. By means of simulation, we investigate the influence of variable percentages of ACC vehicles on traffic flow characteristics. For simulating the ACC vehicles, we propose a new car-following model that also serves as the basis of an ACC implementation in real cars. The model is based on the intelligent driver model (IDM) and inherits its intuitive behavioural parameters: desired velocity, acceleration, comfortable deceleration and desired minimum time headway. It eliminates, however, the sometimes unrealistic behaviour of the IDM in cut-in situations with ensuing small gaps that regularly are caused by lane changes of other vehicles in dense or congested traffic. We simulate the influence of different ACC strategies on the maximum capacity before breakdown and the (dynamic) bottleneck capacity after breakdown. With a suitable strategy, we find sensitivities of the order of 0.3, i.e. 1 per cent more ACC vehicles will lead to an increase in the capacities by about 0.3 per cent. This sensitivity multiplies when considering travel times at actual breakdowns.
Real-time traffic sign detection and recognition
NASA Astrophysics Data System (ADS)
Herbschleb, Ernst; de With, Peter H. N.
2009-01-01
The continuous growth of imaging databases increasingly requires analysis tools for extraction of features. In this paper, a new architecture for the detection of traffic signs is proposed. The architecture is designed to process a large database with tens of millions of images with a resolution up to 4,800x2,400 pixels. Because of the size of the database, a high reliability as well as a high throughput is required. The novel architecture consists of a three-stage algorithm with multiple steps per stage, combining both color and specific spatial information. The first stage contains an area-limitation step which is performance critical in both the detection rate as the overall processing time. The second stage locates suggestions for traffic signs using recently published feature processing. The third stage contains a validation step to enhance reliability of the algorithm. During this stage, the traffic signs are recognized. Experiments show a convincing detection rate of 99%. With respect to computational speed, the throughput for line-of-sight images of 800×600 pixels is 35 Hz and for panorama images it is 4 Hz. Our novel architecture outperforms existing algorithms, with respect to both detection rate and throughput
Christodoulou, Manolis A; Kontogeorgou, Chrysa
2008-10-01
In recent years there has been a great effort to convert the existing Air Traffic Control system into a novel system known as Free Flight. Free Flight is based on the concept that increasing international airspace capacity will grant more freedom to individual pilots during the enroute flight phase, thereby giving them the opportunity to alter flight paths in real time. Under the current system, pilots must request, then receive permission from air traffic controllers to alter flight paths. Understandably the new system allows pilots to gain the upper hand in air traffic. At the same time, however, this freedom increase pilot responsibility. Pilots face a new challenge in avoiding the traffic shares congested air space. In order to ensure safety, an accurate system, able to predict and prevent conflict among aircraft is essential. There are certain flight maneuvers that exist in order to prevent flight disturbances or collision and these are graded in the following categories: vertical, lateral and airspeed. This work focuses on airspeed maneuvers and tries to introduce a new idea for the control of Free Flight, in three dimensions, using neural networks trained with examples prepared through non-linear programming.
Methodology for Time-Domain Estimation of Storm-Time Electric Fields Using the 3D Earth Impedance
NASA Astrophysics Data System (ADS)
Kelbert, A.; Balch, C. C.; Pulkkinen, A. A.; Egbert, G. D.; Love, J. J.; Rigler, E. J.; Fujii, I.
2016-12-01
Magnetic storms can induce geoelectric fields in the Earth's electrically conducting interior, interfering with the operations of electric-power grid industry. The ability to estimate these electric fields at Earth's surface in close to real-time and to provide local short-term predictions would improve the ability of the industry to protect their operations. At any given time, the electric field at the Earth's surface is a function of the time-variant magnetic activity (driven by the solar wind), and the local electrical conductivity structure of the Earth's crust and mantle. For this reason, implementation of an operational electric field estimation service requires an interdisciplinary, collaborative effort between space science, real-time space weather operations, and solid Earth geophysics. We highlight in this talk an ongoing collaboration between USGS, NOAA, NASA, Oregon State University, and the Japan Meteorological Agency, to develop algorithms that can be used for scenario analyses and which might be implemented in a real-time, operational setting. We discuss the development of a time domain algorithm that employs discrete time domain representation of the impedance tensor for a realistic 3D Earth, known as the discrete time impulse response (DTIR), convolved with the local magnetic field time series, to estimate the local electric field disturbances. The algorithm is validated against measured storm-time electric field data collected in the United States and Japan. We also discuss our plans for operational real-time electric field estimation using 3D Earth impedances.
MPEG-4 solutions for virtualizing RDP-based applications
NASA Astrophysics Data System (ADS)
Joveski, Bojan; Mitrea, Mihai; Ganji, Rama-Rao
2014-02-01
The present paper provides the proof-of-concepts for the use of the MPEG-4 multimedia scene representations (BiFS and LASeR) as a virtualization tool for RDP-based applications (e.g. MS Windows applications). Two main applicative benefits are thus granted. First, any legacy application can be virtualized without additional programming effort. Second, heterogeneous mobile devices (different manufacturers, OS) can collaboratively enjoy full multimedia experiences. From the methodological point of view, the main novelty consists in (1) designing an architecture allowing the conversion of the RDP content into a semantic multimedia scene-graph and its subsequent rendering on the client and (2) providing the underlying scene graph management and interactivity tools. Experiments consider 5 users and two RDP applications (MS Word and Internet Explorer), and benchmark our solution against two state-of-the-art technologies (VNC and FreeRDP). The visual quality is evaluated by six objective measures (e.g. PSNR<37dB, SSIM<0.99). The network traffic evaluation shows that: (1) for text editing, the MPEG-based solutions outperforms the VNC by a factor 1.8 while being 2 times heavier then the FreeRDP; (2) for Internet browsing, the MPEG solutions outperform both VNC and FreeRDP by factors of 1.9 and 1.5, respectively. The average round-trip times (less than 40ms) cope with real-time application constraints.
DOT National Transportation Integrated Search
1975-04-01
The report describes a computer simulation of the Air Traffic Control Radar Beacon System (ATCRBS). Operating on real air traffic data and actual characteristics of the relevant ground interrogators, the FORTRAN program re-enacts system operation in ...
DOT National Transportation Integrated Search
1975-04-01
The report describes a computer simulation of the Air Traffic Control Radar Beacon System (ATCRBS). Operating on real air traffic data and actual characteristics of the relevant ground interrogators, the FORTRAN program re-enacts system operation in ...
Simulator evaluation of the final approach spacing tool
NASA Technical Reports Server (NTRS)
Davis, Thomas J.; Erzberger, Heinz; Green, Steven M.
1990-01-01
The design and simulator evaluation of an automation tool for assisting terminal radar approach controllers in sequencing and spacing traffic onto the final approach course is described. The automation tool, referred to as the Final Approach Spacing Tool (FAST), displays speed and heading advisories for arrivals as well as sequencing information on the controller's radar display. The main functional elements of FAST are a scheduler that schedules and sequences the traffic, a 4-D trajectory synthesizer that generates the advisories, and a graphical interface that displays the information to the controller. FAST was implemented on a high performance workstation. It can be operated as a stand-alone in the Terminal Radar Approach Control (TRACON) Facility or as an element of a system integrated with automation tools in the Air Route Traffic Control Center (ARTCC). FAST was evaluated by experienced TRACON controllers in a real-time air traffic control simulation. Simulation results show that FAST significantly reduced controller workload and demonstrated a potential for an increase in landing rate.
NASA Technical Reports Server (NTRS)
Aponso, Bimal; Coppenbarger, Richard A.; Jung, Yoon; Quon, Leighton; Lohr, Gary; O’Connor, Neil; Engelland, Shawn
2015-01-01
NASA's Aeronautics Research Mission Directorate (ARMD) collaborates with the FAA and industry to provide concepts and technologies that enhance the transition to the next-generation air-traffic management system (NextGen). To facilitate this collaboration, ARMD has a series of Airspace Technology Demonstration (ATD) sub-projects that develop, demonstrate, and transitions NASA technologies and concepts for implementation in the National Airspace System (NAS). The second of these sub-projects, ATD-2, is focused on the potential benefits to NAS stakeholders of integrated arrival, departure, surface (IADS) operations. To determine the project objectives and assess the benefits of a potential solution, NASA surveyed NAS stakeholders to understand the existing issues in arrival, departure, and surface operations, and the perceived benefits of better integrating these operations. NASA surveyed a broad cross-section of stakeholders representing the airlines, airports, air-navigation service providers, and industry providers of NAS tools. The survey indicated that improving the predictability of flight times (schedules) could improve efficiency in arrival, departure, and surface operations. Stakeholders also mentioned the need for better strategic and tactical information on traffic constraints as well as better information sharing and a coupled collaborative planning process that allows stakeholders to coordinate IADS operations. To assess the impact of a potential solution, NASA sketched an initial departure scheduling concept and assessed its viability by surveying a select group of stakeholders for a second time. The objective of the departure scheduler was to enable flights to move continuously from gate to cruise with minimal interruption in a busy metroplex airspace environment using strategic and tactical scheduling enhanced by collaborative planning between airlines and service providers. The stakeholders agreed that this departure concept could improve schedule predictability and suggested several key attributes that were necessary to make the concept successful. The goals and objectives of the planned ATD-2 sub-project will incorporate the results of this stakeholder feedback.
Use of the WWW as a Collaborative Tool in a Large HEP Collaboration
NASA Astrophysics Data System (ADS)
Bower, G.; Dubois, R.; Johnson, A. S.; Moss, L.; Perl, J.; Langston, M.; Weiss, E.
As the phenomenal growth of the WWW continues it is easy to view it purely as a tool for PR and advertising, and to forget its roots as a collaborative tool for HEP research. The SLD collaboration has made extensive use of WWW in this latter role, using it to allow collaborators to sign up for shifts, to monitor physics data-taking in near real time, and as a tool to educate and inform collaborators. By their nature such tools are accessible to all collaborators wherever they are located. In this talk we will describe our current system and comment on its effectiveness, and discuss possible enhancements based on forthcoming more powerful web browsers.
Airspace Technology Demonstration 3 (ATD-3): Applied Traffic Flow Management Project Overview
NASA Technical Reports Server (NTRS)
Gong, Chester
2016-01-01
ATD-3 Project Overview for 3rd Joint Workshop for KAIA-KARI - NASA ATM Research Collaboration. This presentation gives a high level description of the ATD-3 project and related technologies. These technologies include Multi-Flight Common Routes (MFCR), Traffic Aware Strategic Aircrew Requests (TASAR) and Dynamic Routes for Arrivals in Weather (DRAW).
Datalink in air traffic management: Human factors issues in communications.
Stedmon, Alex W; Sharples, Sarah; Littlewood, Robert; Cox, Gemma; Patel, Harshada; Wilson, John R
2007-07-01
This paper examines issues underpinning the potential move in aviation away from real speech radiotelephony (R/T) communications towards datalink communications involving text and synthetic speech communications. Using a novel air traffic control (ATC) task, two experiments are reported. Experiment 1 compared the use of speech and text while Experiment 2 compared the use of real and synthetic speech communications. Results indicated that generally there were no significant differences between speech and text communications and that either type could be used without any main effects on performance. However, a number of specific differences were observed across the different phases of the scenarios indicating that workload levels may be more varied when speech communications are used. Experiment 2 illustrated that participants placed a greater level of trust in real speech than synthetic speech, and trusted true communications more than false communications (regardless of whether they were real or synthetic voices). The findings are considered in terms of datalink initiatives for future air traffic management, the importance placed on real speech R/T communications, and the need to develop more natural synthetic speech in this application area.
A distributed scheduling algorithm for heterogeneous real-time systems
NASA Technical Reports Server (NTRS)
Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi
1991-01-01
Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.
Cyber-Critical Infrastructure Protection Using Real-Time Payload-Based Anomaly Detection
NASA Astrophysics Data System (ADS)
Düssel, Patrick; Gehl, Christian; Laskov, Pavel; Bußer, Jens-Uwe; Störmann, Christof; Kästner, Jan
With an increasing demand of inter-connectivity and protocol standardization modern cyber-critical infrastructures are exposed to a multitude of serious threats that may give rise to severe damage for life and assets without the implementation of proper safeguards. Thus, we propose a method that is capable to reliably detect unknown, exploit-based attacks on cyber-critical infrastructures carried out over the network. We illustrate the effectiveness of the proposed method by conducting experiments on network traffic that can be found in modern industrial control systems. Moreover, we provide results of a throughput measuring which demonstrate the real-time capabilities of our system.
Arico, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Graziani, Ilenia; Imbert, Jean-Paul; Granger, Geraud; Benhacene, Railene; Terenzi, Michela; Pozzi, Simone; Babiloni, Fabio
2015-08-01
Machine-learning approaches for mental workload (MW) estimation by using the user brain activity went through a rapid expansion in the last decades. In fact, these techniques allow now to measure the MW with a high time resolution (e.g. few seconds). Despite such advancements, one of the outstanding problems of these techniques regards their ability to maintain a high reliability over time (e.g. high accuracy of classification even across consecutive days) without performing any recalibration procedure. Such characteristic will be highly desirable in real world applications, in which human operators could use such approach without undergo a daily training of the device. In this work, we reported that if a simple classifier is calibrated by using a low number of brain spectral features, between those ones strictly related to the MW (i.e. Frontal and Occipital Theta and Parietal Alpha rhythms), those features will make the classifier performance stable over time. In other words, the discrimination accuracy achieved by the classifier will not degrade significantly across different days (i.e. until one week). The methodology has been tested on twelve Air Traffic Controls (ATCOs) trainees while performing different Air Traffic Management (ATM) scenarios under three different difficulty levels.
An efficient method to detect periodic behavior in botnet traffic by analyzing control plane traffic
AsSadhan, Basil; Moura, José M.F.
2013-01-01
Botnets are large networks of bots (compromised machines) that are under the control of a small number of bot masters. They pose a significant threat to Internet’s communications and applications. A botnet relies on command and control (C2) communications channels traffic between its members for its attack execution. C2 traffic occurs prior to any attack; hence, the detection of botnet’s C2 traffic enables the detection of members of the botnet before any real harm happens. We analyze C2 traffic and find that it exhibits a periodic behavior. This is due to the pre-programmed behavior of bots that check for updates to download them every T seconds. We exploit this periodic behavior to detect C2 traffic. The detection involves evaluating the periodogram of the monitored traffic. Then applying Walker’s large sample test to the periodogram’s maximum ordinate in order to determine if it is due to a periodic component or not. If the periodogram of the monitored traffic contains a periodic component, then it is highly likely that it is due to a bot’s C2 traffic. The test looks only at aggregate control plane traffic behavior, which makes it more scalable than techniques that involve deep packet inspection (DPI) or tracking the communication flows of different hosts. We apply the test to two types of botnet, tinyP2P and IRC that are generated by SLINGbot. We verify the periodic behavior of their C2 traffic and compare it to the results we get on real traffic that is obtained from a secured enterprise network. We further study the characteristics of the test in the presence of injected HTTP background traffic and the effect of the duty cycle on the periodic behavior. PMID:25685512
Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi
2011-01-01
To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.
Research on driver fatigue detection
NASA Astrophysics Data System (ADS)
Zhang, Ting; Chen, Zhong; Ouyang, Chao
2018-03-01
Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.
Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions
2017-01-01
Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels. PMID:29244762
Real-Time Process Analytics in Emergency Healthcare.
Koufi, Vassiliki; Malamateniou, Flora; Prentza, Adrianna; Vassilacopoulos, George
2017-01-01
Emergency medical systems (EMS) are considered to be amongst the most crucial systems as they involve a variety of activities which are performed from the time of a call to an ambulance service till the time of patient's discharge from the emergency department of a hospital. These activities are closely interrelated so that collaboration and coordination becomes a vital issue for patients and for emergency healthcare service performance. The utilization of standard workflow technology in the context of Service Oriented Architecture can provide an appropriate technological infrastructure for defining and automating EMS processes that span organizational boundaries so that to create and empower collaboration and coordination among the participating organizations. In such systems, the utilization of leading-edge analytics tools can prove important as it can facilitate real-time extraction and visualization of useful insights from the mountains of generated data pertaining to emergency case management. This paper presents a framework which provides healthcare professionals with just-in-time insight within and across emergency healthcare processes by performing real-time analysis on process-related data in order to better support decision making and identify potential critical risks that may affect the provision of emergency care to patients.
NASA Astrophysics Data System (ADS)
Sohn, Illsoo; Lee, Byong Ok; Lee, Kwang Bok
Recently, multimedia services are increasing with the widespread use of various wireless applications such as web browsers, real-time video, and interactive games, which results in traffic asymmetry between the uplink and downlink. Hence, time division duplex (TDD) systems which provide advantages in efficient bandwidth utilization under asymmetric traffic environments have become one of the most important issues in future mobile cellular systems. It is known that two types of intercell interference, referred to as crossed-slot interference, additionally arise in TDD systems; the performances of the uplink and downlink transmissions are degraded by BS-to-BS crossed-slot interference and MS-to-MS crossed-slot interference, respectively. The resulting performance unbalance between the uplink and downlink makes network deployment severely inefficient. Previous works have proposed intelligent time slot allocation algorithms to mitigate the crossed-slot interference problem. However, they require centralized control, which causes large signaling overhead in the network. In this paper, we propose to change the shape of the cellular structure itself. The conventional cellular structure is easily transformed into the proposed cellular structure with distributed receive antennas (DRAs). We set up statistical Markov chain traffic model and analyze the bit error performances of the conventional cellular structure and proposed cellular structure under asymmetric traffic environments. Numerical results show that the uplink and downlink performances of the proposed cellular structure become balanced with the proper number of DRAs and thus the proposed cellular structure is notably cost-effective in network deployment compared to the conventional cellular structure. As a result, extending the conventional cellular structure into the proposed cellular structure with DRAs is a remarkably cost-effective solution to support asymmetric traffic environments in future mobile cellular systems.
Optimisation of sensing time and transmission time in cognitive radio-based smart grid networks
NASA Astrophysics Data System (ADS)
Yang, Chao; Fu, Yuli; Yang, Junjie
2016-07-01
Cognitive radio (CR)-based smart grid (SG) networks have been widely recognised as emerging communication paradigms in power grids. However, a sufficient spectrum resource and reliability are two major challenges for real-time applications in CR-based SG networks. In this article, we study the traffic data collection problem. Based on the two-stage power pricing model, the power price is associated with the efficient received traffic data in a metre data management system (MDMS). In order to minimise the system power price, a wideband hybrid access strategy is proposed and analysed, to share the spectrum between the SG nodes and CR networks. The sensing time and transmission time are jointly optimised, while both the interference to primary users and the spectrum opportunity loss of secondary users are considered. Two algorithms are proposed to solve the joint optimisation problem. Simulation results show that the proposed joint optimisation algorithms outperform the fixed parameters (sensing time and transmission time) algorithms, and the power cost is reduced efficiently.
Krauskopf, Julian; Caiment, Florian; van Veldhoven, Karin; Chadeau-Hyam, Marc; Sinharay, Rudy; Chung, Kian Fan; Cullinan, Paul; Collins, Peter; Barratt, Benjamin; Kelly, Frank J; Vermeulen, Roel; Vineis, Paolo; de Kok, Theo M; Kleinjans, Jos C
2018-04-01
Traffic-related air pollution is a complex mixture of particulate matter (PM) and gaseous pollutants, such as nitrogen dioxide (NO2). PM exposure contributes to the pathogenesis of many diseases including several types of cancer, as well as pulmonary, cardiovascular and neurodegenerative diseases. Also exposure to NO2 has been related to increased cardiovascular mortality. In search of an early diagnostic biomarker for improved air pollution-associated health risk assessment, recent human studies have shown that certain circulating miRNAs are altered upon exposure to traffic-related air pollutants. Here, we present for the first time a global analysis of the circulating miRNA genome in an experimental cross-over study of a human population exposed to traffic-related air pollution. By utilizing next-generation sequencing technology and detailed real-time exposure measurements we identified 54 circulating miRNAs to be dose- and pollutant species-dependently associated with PM10, PM2.5, black carbon, ultrafine particles and NO2 already after 2 h of exposure. Bioinformatics analysis suggests that these circulating miRNAs actually reflect the adverse consequences of traffic pollution-induced toxicity in target tissues including the lung, heart, kidney and brain. This study shows the strong potential of circulating miRNAs as novel biomarkers for environmental health risk assessment. Copyright © 2018 Elsevier Ltd. All rights reserved.
Providing Situational Awareness for Pipeline Control Operations
NASA Astrophysics Data System (ADS)
Butts, Jonathan; Kleinhans, Hugo; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet
A SCADA system for a single 3,000-mile-long strand of oil or gas pipeline may employ several thousand field devices to measure process parameters and operate equipment. Because of the vital tasks performed by these sensors and actuators, pipeline operators need accurate and timely information about their status and integrity. This paper describes a realtime scanner that provides situational awareness about SCADA devices and control operations. The scanner, with the assistance of lightweight, distributed sensors, analyzes SCADA network traffic, verifies the operational status and integrity of field devices, and identifies anomalous activity. Experimental results obtained using real pipeline control traffic demonstrate the utility of the scanner in industrial settings.
NASA Technical Reports Server (NTRS)
Sawyer, R. H.; Mclaughlin, M. D.
1974-01-01
The operating problems and equipment requirements for STOL airplanes in terminal area operations in simulated air traffic control (ATC) environments were studied. These studies consisted of Instrument Flight Rules (IFR) arrivals and departures in the New York area to and from a downtown STOL port, STOL runways at John F. Kennedy International Airport, or STOL runways at a hypothetical international airport. The studies were accomplished in real time by using a STOL airplane flight simulator. An experimental powered lift STOL airplane and two in-service airplanes having high aerodynamic lift (i.e., STOL) capability were used in the simulations.
Gallagher, J; Gill, L W; McNabola, A
2013-08-01
This study investigates the potential real world application of passive control systems to reduce personal pollutant exposure in an urban street canyon in Dublin, Ireland. The implementation of parked cars and/or low boundary walls as a passive control system has been shown to minimise personal exposure to pollutants on footpaths in previous investigations. However, previous research has been limited to generic numerical modelling studies. This study combines real-time traffic data, meteorological conditions and pollution concentrations, in a real world urban street canyon before and after the implementation of a passive control system. Using a combination of field measurements and numerical modelling this study assessed the potential impact of passive controls on personal exposure to nitric oxide (NO) concentrations in the street canyon in winter conditions. A calibrated numerical model of the urban street canyon was developed, taking into account the variability in traffic and meteorological conditions. The modelling system combined the computational fluid dynamic (CFD) simulations and a semi-empirical equation, and demonstrated a good agreement with measured field data collected in the street canyon. The results indicated that lane distribution, fleet composition and vehicular turbulence all affected pollutant dispersion, in addition to the canyon geometry and local meteorological conditions. The introduction of passive controls displayed mixed results for improvements in air quality on the footpaths for different wind and traffic conditions. Parked cars demonstrated the most comprehensive passive control system with average improvements in air quality of up to 15% on the footpaths. This study highlights the potential of passive controls in a real street canyon to increase dispersion and improve air quality at street level. Copyright © 2013 Elsevier B.V. All rights reserved.
Data streaming in telepresence environments.
Lamboray, Edouard; Würmlin, Stephan; Gross, Markus
2005-01-01
In this paper, we discuss data transmission in telepresence environments for collaborative virtual reality applications. We analyze data streams in the context of networked virtual environments and classify them according to their traffic characteristics. Special emphasis is put on geometry-enhanced (3D) video. We review architectures for real-time 3D video pipelines and derive theoretical bounds on the minimal system latency as a function of the transmission and processing delays. Furthermore, we discuss bandwidth issues of differential update coding for 3D video. In our telepresence system-the blue-c-we use a point-based 3D video technology which allows for differentially encoded 3D representations of human users. While we discuss the considerations which lead to the design of our three-stage 3D video pipeline, we also elucidate some critical implementation details regarding decoupling of acquisition, processing and rendering frame rates, and audio/video synchronization. Finally, we demonstrate the communication and networking features of the blue-c system in its full deployment. We show how the system can possibly be controlled to face processing or networking bottlenecks by adapting the multiple system components like audio, application data, and 3D video.
An experimental study on CHVE's performance evaluation.
Paiva, Paulo V F; Machado, Liliane S; Oliveira, Jauvane C
2012-01-01
Virtual reality-based training simulators, with collaborative capabilities, are known to improve the way users interact with one another while learning or improving skills on a given medical procedure. Performance evaluation of Collaborative Haptic Virtual Environments (CHVE) allows us to understand how such systems can work in the Internet, as well as the requirements for multisensorial and real-time data. This work discloses new performance evaluation results for the collaborative module of the CyberMed VR framework.
Bernal-Rusiel, Jorge L.; Rannou, Nicolas; Gollub, Randy L.; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E.; Pienaar, Rudolph
2017-01-01
In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution. PMID:28507515
Hahn, Intaek; Brixey, Laurie A; Wiener, Russell W; Henkle, Stacy W; Baldauf, Richard
2009-12-01
Analyses of outdoor traffic-related particulate matter (PM) concentration distribution and fluctuation patterns in urban street canyons within a microscale distance of less than 500 m from a highway source are presented as part of the results from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study. Various patterns of spatial and temporal changes in the street canyon PM concentrations were investigated using time-series data of real-time PM concentrations measured during multiple monitoring periods. Concurrent time-series data of local street canyon wind conditions and wind data from the John F. Kennedy (JFK) International Airport National Weather Service (NWS) were used to characterize the effects of various wind conditions on the behavior of street canyon PM concentrations.Our results suggest that wind direction may strongly influence time-averaged mean PM concentration distribution patterns in near-highway urban street canyons. The rooftop-level wind speeds were found to be strongly correlated with the PM concentration fluctuation intensities in the middle sections of the street blocks. The ambient turbulence generated by shifting local wind directions (angles) showed a good correlation with the PM concentration fluctuation intensities along the entire distance of the first and second street blocks only when the wind angle standard deviations were larger than 30 degrees. Within-canyon turbulent shearing, caused by fluctuating local street canyon wind speeds, showed no correlation with PM concentration fluctuation intensities. The time-averaged mean PM concentration distribution along the longitudinal distances of the street blocks when wind direction was mostly constantly parallel to the street was found to be similar to the distribution pattern for the entire monitoring period when wind direction fluctuated wildly. Finally, we showed that two different PM concentration metrics-time-averaged mean concentration and number of concentration peaks above a certain threshold level-can possibly lead to different assessments of spatial concentration distribution patterns.
Global collaboration on road traffic injury prevention.
Peden, Margie
2005-06-01
Worldwide, nearly 1.2 million people are killed in road traffic crashes every year and 20 million to 50 million more are injured or disabled. These injuries account for 2.1% of global mortality and 2.6% of all disability-adjusted life years (DALYs) lost. Low- and middle-income countries account for about 85% of the deaths and 90% of the DALYs lost annually. Without appropriate action, by 2020, road traffic injuries are predicted to be the third leading contributor to the global burden of disease. The economic cost of road traffic crashes is enormous. Globally it is estimated that US$518 billion is spent on road traffic crashes with low- and middle-income countries accounting for US$65 billion--more than these countries receive in development assistance. But these costs are just the tip of the iceberg. For everyone killed, injured or disabled by a road traffic crash there are countless others deeply affected. Many families are driven into poverty by the expenses of prolonged medical care, loss of a family breadwinner or the added burden of caring for the disabled. There is an urgent need for global collaboration on road traffic injury prevention. Since 2000, WHO has stepped up its response to the road safety crisis by firstly developing a 5-year strategy for road traffic injury prevention and following this by dedicating World Health Day 2004 to road safety and launching the WHO/World Bank World Report on Road Traffic Injury Prevention at the global World Health Day event in Paris, France. This short article highlights the main messages from the World Report and the six recommendations for action on road safety at a national and international level. It goes on to briefly discuss other international achievements since World Health Day and calls for countries to take up the challenge of implementing the recommendations of the World Report.
DOT National Transportation Integrated Search
2005-12-01
Major roads and arterials in the City of Tucson and Pima County are already significantly detectorized with inductive loop detectors and, at places, with video-based detectors. These detectors are used for semi-actuated signal control and for limited...
Validation Of The Airspace Concept Evaluation System Using Real World Data
NASA Technical Reports Server (NTRS)
Zelinski, Shannon
2005-01-01
This paper discusses the process of performing a validation of the Airspace Concept Evaluation System (ACES) using real world historical flight operational data. ACES inputs are generated from select real world data and processed to create a realistic reproduction of a single day of operations within the National Airspace System (NAS). ACES outputs are then compared to real world operational metrics and delay statistics for the reproduced day. Preliminary results indicate that ACES produces delays and airport operational metrics similar to the real world with minor variations of delay by phase of flight. ACES is a nation-wide fast-time simulation tool developed at NASA Ames Research Center. ACES models and simulates the NAS using interacting agents representing center control, terminal flow management, airports, individual flights, and other NAS elements. These agents pass messages between one another similar to real world communications. This distributed agent based system is designed to emulate the highly unpredictable nature of the NAS, making it a suitable tool to evaluate current and envisioned airspace concepts. To ensure that ACES produces the most realistic results, the system must be validated. There is no way to validate future concepts scenarios using real world historical data, but current day scenario validations increase confidence in the validity of future scenario results. Each operational day has unique weather and traffic demand schedules. The more a simulation utilizes the unique characteristic of a specific day, the more realistic the results should be. ACES is able to simulate the full scale demand traffic necessary to perform a validation using real world data. Through direct comparison with the real world, models may continuee to be improved and unusual trends and biases may be filtered out of the system or used to normalize the results of future concept simulations.
Measurements and modelling of base station power consumption under real traffic loads.
Lorincz, Josip; Garma, Tonko; Petrovic, Goran
2012-01-01
Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.
Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †
Lorincz, Josip; Garma, Tonko; Petrovic, Goran
2012-01-01
Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026