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First published online April 28, 2019

Modeling Driver Behavior in Work and Nonwork Zones: Multidimensional Psychophysical car-Following Framework

Abstract

A new multidimensional framework for modeling car following on the basis of statistical evaluation of driver behavior in work and non-work zones is presented. The models developed as part of this multidimensional framework use psychophysical concepts for car following that are close in character to the Wiedemann model used in popular traffic simulation software such as VISSIM. The authors hypothesized that with an instrumented research vehicle (IRV) in a living laboratory (LL) along a roadway, the parameters of models developed from the multidimensional framework could be derived statistically and calibrated for driver behavior in work zones. This hypothesis was validated with data collected from a group of 64 random participants who drove the IRV through an LL set up along a work zone on I-95 near Washington, D.C. For this validation, the IRV was equipped with sensors, including radar, and an onboard data collection system to record the vehicle performance. One of the limitations of current car-following models is that they account for only one overall behavioral condition. This study demonstrated that there are four different categories of car-following behavior models, each with different parameter distributions: the four categories are divided by traffic condition (congested versus non congested) and by roadway condition (work versus nonwork zone). Calibrated threshold values for each of these four categories are presented. Furthermore, this new framework for modeling car-following behavior is described in a multidimensional setting and can be used to enhance vehicle behavior in microsimulation models.

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References

1. Heaslip K., Collura J., and Louisell C. Evaluation of Work Zone Design Strategies Quantifying the Impact of Driver Behavior on Traffic Flow and Safety. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.
2. Ramezani H., Benekoha R., and Avrenli K. Determining Queue and Congestion in Highway Work Zone Bottlenecks. Project No. 046IY02. NEXTRANS Center, Purdue University, West Lafayette, Ind., 2011.
3. Brackstone M., and McDonald M. Car-Following: A Historical Review. Transportation Research Part F: Traffic Psychology and Behavior, Vol. 2, No. 4, 1994, pp. 181–196.
4. Herrey E., and Herrey H. Principles of Physics Applied to Traffic Movements and Road Conditions. American Journal of Physics, Vol. 13, No. 1, 1945, pp. 1–14.
5. Newell G. A Simplified Car-Following Theory: A Lower Order Model. Transportation Research Part B: Methodological, Vol. 36, No. 3, 2002, pp. 195–205.
6. Kometani E., and Sasaki T. Dynamic Behavior of Traffic with a Nonlinear Spacing-Speed Relationship. Symposium on Theory of Traffic Flow, 1959, pp. 105–119.
7. Rothery R. W. Traffic Flow Theory: Chapter 4: Car Following Models. Transportation Research Board Special Report, 1994.
8. Gipps P. G. A Behavioural Car-Following Model for Computer Simulation. Transportation Research Part B, Vol. 15B, No. 2-C, 1981, p. 7.
9. Hwang S., and Park C. Modeling of the Gap Acceptance Behavior at a Merging Section of Urban Freeway. Proceedings of the Eastern Asia Society for Transportation Studies, Tokyo, Vol. 5, 2005, pp. 1641–1656.
10. Wiedemann R. Simulation des Strassenverkehrsflusses, Schriftenreihe des Instituts fur Verkehrswesen. University Karlsruhe, Karlsruhe, Germany, 1974.
11. Todosiev E. The Action Point Model of Driver–Vehicle Systems. PhD dissertation. Ohio State University, Engineering Experiment Station, 1963.
12. Wiedemann R., and Reiter U. Microscopic Traffic Simulation: The Simulation System Mission. University Karlsruhe, Karlsruhe, Germany, 1992.
13. PTV Group. VISSIM 6.0 User Manual. Karlsruhe, Germany, 2013.
14. Fritzsche H. A Model for Traffic Simulation. Transportation Engineering Contribution, Vol. 5, 1994, pp. 317–321.
15. Olstam J., and Tapani A. Comparison of Car-Following Models. VTI meddelande 960A. Swedish National Road Administration, Linkoping, Sweden, 2004.
16. Lochrane T. W. P., Al-Deek H., Dailey D., and Bared J. Living Laboratory for Freeway Operations: Case Study for Collecting Driver Behavior Data Though Freeway Work Zones. ASCE Journal of Transportation Engineering, Vol. 140, No. 7, 2014, pp. 04014024–1–04014024-7.
17. Brackstone M., McDonald M., and Sultan B. Dynamic Behavioral Data Collection Using an Instrumented Vehicle. In Transportation Research Record: Journal of the Transportation Research Board, No. 1689, TRB, National Research Council, Washington, D.C., 1999, pp. 9–17.
18. Dellaert F. The Expectation Maximization Algorithm. Technical Report No. GIT-GVU-02-20. College of Computing, Georgia Institute of Technology, Atlanta, 2002.
19. Lochrane T. W. P. A New Multidimensional Psychophysical Framework for Modeling Car-Following in a Freeway Work Zone. PhD dissertation. University of Central Florida, Orlando, 2014.
20. Driver Behavior in Traffic. Publication FHWA-HRT-12-036. FHWA, U.S. Department of Transportation, 2010.
21. Palshikar G. Simple Algorithms for Peak Detection in Time-Series. Proceedings of the 1st International Conference Advanced Data Analysis, Business Analytics and Intelligence, Indian Institute of Management, Ahmedabad, India, 2009.
22. Schneider R. Survey of Peaks–Valleys Identification in Time Series. Department of Informatics, University of Zurich, Switzerland, 2011.

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Article first published online: April 28, 2019
Issue published: January 2015

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© 2015 National Academy of Sciences.
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Authors

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Taylor W. P. Lochrane
Turner–Fairbank Highway Research Center, FHWA, U.S. Department of Transportation, 6300 Georgetown Pike, McLean, VA 22101
Haitham Al-Deek
Department of Civil, Environmental, and Construction Engineering, University of Central Florida, 12800 Pegasus Drive, Suite 211, P.O. Box 162450, Orlando, FL 32816-2450
Daniel J. Dailey
Department of Electrical Engineering, University of Washington, 1410 Northeast Campus Parkway, Seattle, WA 98195.
Cory Krause
Turner–Fairbank Highway Research Center, FHWA, U.S. Department of Transportation, 6300 Georgetown Pike, McLean, VA 22101

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