U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
| Project Information | ||
| Project ID: | FHWA-PROJ-09-0039 | |
| Project Name: | Driver Behavior in Traffic | |
| Project Status: | Completed | |
| Start Date: | September 1, 2009 | |
| End Date: | February 29, 2012 | |
| Contact Information | ||
| Last Name: | Yang | |
| First Name: | David | |
| Telephone: | 202-493-3284 | |
| E-mail: | david.yang@dot.gov | |
| Office: | Office of Operations Research and Development | |
| Team: | Trans Ops Concepts and Analysis Team [HRDO-20] | |
| Program: | Exploratory Advanced Research | |
| Project detail | ||
| Roadmap/Focus area(s): | Travel Modeling | |
| Project Description: | The primary objective for this Exploratory Advanced Research project is to characterize driver behavior under naturalistic driving experiences with respect to critical parameters related to freeway driving. To accomplish such an objective, the research team will develop agents that will learn individual drivers temporal actions for any given traffic state retrieved from the naturalistic database. These characteristics, or driving rules, of the agents will be coded in the VisSim environment to test and study the collective effects of these learned behaviors with multiple drivers involved and under different situations. Analysis of trained agents' characteristics will provide the industry with methods for developing more accurate and sensitive traffic simulation models, which could lead to future research for developing new generations of traffic simulation models to accurately model impacts of driver behavior in traffic during incidents and complex traffic situations. | |
| Goals: | The primary objective for this Exploratory Advanced Research project is to characterize driver behavior under naturalistic driving experiences with respect to critical parameters related to freeway driving. | |
| More Information URL(s): | ||
| Field Test: | No | |
| Product Type: | Research report Software | |
| Test Methodology: | Agent-based modeling and simulation | |
| Partners: | Virginia Center for Transportation Innovation Research; Role(s): Technical | |
| Expected Benefits: | New behavioral models are necessary to predict the safe and efficient use of new connected vehicle and roadside technology. This project demonstrates the ability of agent-based models based on naturalistic driving studies to create new and improved behavioral models. | |
| Deliverables: | Name: Final project report and Application Programming Interface codes. Product Type(s): Research report, Software Description: Detailed final report documenting study effort and findings. Application Programming Interface codes written for study. Publication URL(s): http://www.ntis.gov | |
| Project Findings: | This research provides a foundation for agent-based modeling of driver behavior based on naturalistic data through an integrated framework for safety and operation analysis. Lateral vehicle action was simulated in a microscopic traffic behavior modeling environment, bringing new insights to the modeling of driver maneuvering behavior during safety-critical events. Agents developed and evaluated in the VisSim (a German acronym that refers to a simulation model for traffic in cities) simulation platform revealed a close resemblance to real driver data. The project team improved car-following models through development of a hybrid model for greater accuracy and flexibility and through the addition of the new "passing and hook-following" thresholds. They used the model to simulate vehicle actions in safety-critical events, developed agent-based simulation components integrated with the VisSim simulation package through its driver model, and developed and implemented a robust activation mechanism for agent-based simulation based on discriminant analysis. The investigators also identified key future research issues: adaptability of agents in real time and human factors issues related to warning individual drivers about changes in their driving behavior that might lead to safety-critical events. | |
| FHWA Topics: | Road Operations and Congestion--Transportation Management | |
| TRT Terms: | Driver Behavior Simulation Operations Research Traffic Simulation Driving Traffic |
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| FHWA Disciplines: | Operations |
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| Subject Areas: | Operations and Traffic Management |
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