01588983

Component

The objective of this paper is to model driver intersection approach and traversal trajectories in response to traffic signals and driver behavior based on stopping behavior. This study analyzed 12,688 observations from signalized intersections from the CICAS-V project (1) database. The selected data were subjected to Multivariate Adaptive Regression Splining to develop a model of a typical driver’s velocity on their approach to the intersection based on the vehicle’s proximity to the stop bar (range [m]) and other categorical factors such as vehicle type, time of day, road surface condition, and weather. The resulting models highlight how driver approach speeds vary as a function of range and other factors depending on the signal phase and intended course of action. The models predict the vehicle speed as a function of distance to the stop bar of the intersection (range). The results suggest that the behaviors of red and yellow light runners are difficult to distinguish from each other, but it is possible. These models will be used to calculate vehicle approach speeds in real-world intersection crashes.

This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.

01584066

16-1490

English

12p

2016

Transportation Research Board 95th Annual Meeting

Web

Figures; Photos; References (15) ; Tables

Behavior; Drivers; Signalized intersections; Stopping; Traffic control devices; Vehicle trajectories

Highways; Operations and Traffic Management; Safety and Human Factors; I73: Traffic Control; I83: Accidents and the Human Factor

Transportation Research Board Annual Meeting 2016 Paper #16-1490

TRIS, TRB, ATRI

Jan 12 2016 4:39PM