942 resultados para Driver Behavior Modeling.


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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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Energy Department, Division of Transportation Conservation, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Driver and Pedestrian Programs, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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Mode of access: Internet.

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Performance prediction and application behavior modeling have been the subject of exten- sive research that aim to estimate applications performance with an acceptable precision. A novel approach to predict the performance of parallel applications is based in the con- cept of Parallel Application Signatures that consists in extract an application most relevant parts (phases) and the number of times they repeat (weights). Executing these phases in a target machine and multiplying its exeuction time by its weight an estimation of the application total execution time can be made. One of the problems is that the performance of an application depends on the program workload. Every type of workload affects differently how an application performs in a given system and so affects the signature execution time. Since the workloads used in most scientific parallel applications have dimensions and data ranges well known and the behavior of these applications are mostly deterministic, a model of how the programs workload affect its performance can be obtained. We create a new methodology to model how a program’s workload affect the parallel application signature. Using regression analysis we are able to generalize each phase time execution and weight function to predict an application performance in a target system for any type of workload within predefined range. We validate our methodology using a synthetic program, benchmarks applications and well known real scientific applications.

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Nationwide, over 1,000 fatalities and 40,000 injuries occur annually in work zones, which include both construction zones and areas where maintenance is performed. The majority (85%) of work zone accidents result from unsafe driver behavior, and vehicle speed is often a factor in work zone crashes. In order to address speed and driver behavior near work zones, roadway agencies have developed different traffic calming measures. The objective of this research is to summarize the effectiveness of different traffic calming treatments for reducing speeds in work zones. This project 1. identified work zone traffic calming treatments for which information has not been well summarized, 2. identified state of the art and new technologies for work zone traffic calming, and 3. synthesized research related to items 1 and 2

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To support the analysis of driver behavior at rural freeway work zone lane closure merge points, Center for Transportation Research and Education staff collected traffic data at merge areas using video image processing technology. The collection of data and the calculation of the capacity of lane closures are reported in a companion report, "Traffic Management Strategies for Merge Areas in Rural Interstate Work Zones". These data are used in the work reported in this document and are used to calibrate a microscopic simulation model of a typical, Iowa rural freeway lane closure. The model developed is a high fidelity computer simulation with an animation interface. It simulates traffic operations at a work zone lane closure. This model enables traffic engineers to visually demonstrate the forecasted delay that is likely to result when freeway reconstruction makes it necessary to close freeway lanes. Further, the model is also sensitive to variations in driver behavior and is used to test the impact of slow moving vehicles and other driver behaviors. This report consists of two parts. The first part describes the development of the work zone simulation model. The simulation analysis is calibrated and verified through data collected at a work zone in Interstate Highway 80 in Scott County, Iowa. The second part is a user's manual for the simulation model, which is provided to assist users with its set up and operation. No prior computer programming skills are required to use the simulation model.

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The Iowa Department of Transportation, like many other state transportation agencies, is experiencing growing congestion and traffic delays in work zones on rural interstate highways. The congestion results in unproductive and wasteful delays for both motorists and commercial vehicles. It also results in hazardous conditions where vehicle stopped in queues on rural interstate highways are being approached by vehicles upstream at very high speeds. The delays also result in driver frustration, making some drivers willing to take unsafe risks in an effort to bypass delays. To reduce the safety hazards and unproductive delays of congested rural interstate work zones, the Iowa Department of Transportation would like to improve its traffic management strategies at these locations. Applying better management practices requires knowledge of the traffic flow properties and driver behavior in and around work zones, and knowledge of possible management strategies. The project reported here and in a companion report documents research which seeks to better understand traffic flow behavior at rural interstate highway work zones and to estimate the traffic carrying capacity of work zone lane closures. In addition, this document also reports on technology available to better manage traffic in and around work zones.