01334515

Component

https://doi.org/10.3141/2241-08

http://scholar.google.com...arby&publication_year=2011

This paper introduces two logistic statistical models for the driver stop–run decision at the onset of yellow at signalized intersections to capture the stochastic nature of the driver stop–run decision. One model is a classical frequentist model, whereas the other uses a Bayesian statistics approach. The Bayesian model parameters were calibrated by using the Markov Chain Monte Carlo slice procedure implemented within the MATLAB software. Both models were developed with 3,328 stop–run records, which were collected in a field experiment on the Virginia Smart Road, a limited-access highway between Blacksburg and Interstate 81 in Montgomery County, Virginia. The variables included in each model were driver gender, age, time to intersection, yellow time, approaching speed, and speed limit. Both models were shown to be consistent. For the Bayesian model application, two procedures were illustrated: cascaded regression and Cholesky decomposition. Both procedures produced replications consistent with the Bayesian model realizations, while these procedures captured the parameter correlations without the need to store the set of parameter realizations. The Bayesian model produced valid and transferable behavior by replicating multiple experimental results. The proposed Bayesian approach is ideal for modeling multiagent systems in which each agent has its own unique set of parameters.

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01361671

11-1828

English

pp 58-77

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309167611

Print

Figures (5) ; References (11) ; Tables (6)

Behavior; Decision making; Drivers; Markov chains; Mathematical models; Monte Carlo method; Signalized intersections; Stochastic processes; Yellow interval (Traffic signal cycle)

Virginia Smart Road

Bayesian models

Virginia

Data and Information Technology; Highways; Safety and Human Factors; I83: Accidents and the Human Factor

TRIS, TRB, ATRI

Feb 17 2011 5:56PM

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