Modeling Pipeline Driving Behaviors: A Hidden Markov Model Approach

Zou, Xi and David Levinson (2006) Modeling Pipeline Driving Behaviors: A Hidden Markov Model Approach. Journal of the Transportation Research Board: Transportation Research Record #1980 (Driver Behavior, Older Drivers, Simulation, User Information Systems, and Visualization) pp. 16-23.

36 Pages Posted: 4 Feb 2008

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Xi Zou

affiliation not provided to SSRN

David Matthew Levinson

affiliation not provided to SSRN

Abstract

Abstract: Driving behaviors at intersection are complex because drivers have to perceive more traffic events than normal road driving and thus are exposed to more errors with safety consequences. Drivers make real-time responsesin a stochastic manner. This paper presents our study using Hidden Markov Models (HMM) to model driving behaviors at intersections. Observed vehicle movement data are used to build up the model. A single HMM is used to cluster the vehicle movements when they are close to intersection. The re-estimated clustered HMMs provide better prediction of the vehicle movements compared to traditional car-following models. Only through vehicles on major roads are considered in this paper. Journal of the Transportation Research Board: Transportation

Suggested Citation

Zou, Xi and Levinson, David Matthew, Modeling Pipeline Driving Behaviors: A Hidden Markov Model Approach. Available at SSRN: https://ssrn.com/abstract=1089104

Xi Zou

affiliation not provided to SSRN ( email )

David Matthew Levinson (Contact Author)

affiliation not provided to SSRN

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