Title

Using Drivers' Stop/Go Decisions In Driving Simulator To Assess Rear-End Crash Risk At Signalized Intersections

Keywords

Dilemma zone; Driving simulators; Rear-end crashes; Signal change; Signalized intersections; Stop/go decision

Abstract

Advanced driving simulators have a potential to be utilized to assess crash risks of driving behaviors, traffic surroundings, and highway designs. This study focused on investigating if drivers' stop/go decisions due to signal change in the simulator's virtual reality can be used to assess rear-end crash risk at the signalized intersection. A signalized intersection with as many important features (including roadway geometries, traffic control devices, intersection surroundings, and buildings) was replicated into a high-fidelity driving simulator. Using the virtual signalized intersection, a driving simulator experiment was conducted to test driver's stop/go decisions at two approaches of the intersection that respectively showed higher and lower rear-end crash risks in the crash history analysis. The experiment results showed that the variability in drivers' stop/go decisions at the higher crash-risk location is higher than that at the lower crash-risk location. Further, through modeling rear-end conflicts based on driver's stop/go probability as a function of potential time to intersection, it was found that the rear-end crash tendency at the two locations displayed by the driver's stop/go behavior in driving simulator is consistent with the finding from the trend in crash history analysis. This research supported that driver's stop/go behavior in a driving simulator can be utilized to assess rear-end crash risk at signalized intersections to seek effective engineering countermeasures to lower crash rates for the high-risk locations. © 2009 Taylor & Francis Group, LLC.

Publication Date

1-1-2009

Publication Title

Journal of Transportation Safety and Security

Volume

1

Issue

2

Number of Pages

85-100

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/19439960902735097

Socpus ID

84989303267 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84989303267

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