01663908

Component

Most of the existing research on variable speed limit (VSL) models assumes either 100% driver compliance, or tests the models at various compliance levels, rather than modeling driver compliance. Based on vehicle trajectory data collected from a driving simulator experiment, this paper aims to quantify and model driver compliance to VSL, and to develop a VSL microscopic behavior model that incorporates driver compliance. The study estimates driver compliance through the development of a model that considers the vehicle’s initial and final states, and captures the degree to which compliance occurs at each speed decision. Regression results show that a statistically significant driver compliance model exists (R²= 0.95) and can be utilized to estimate the degree to which drivers will comply with VSL based on the presence/absence of variable message signs, the base speed limit, and the requested speed change of the VSL. Finally, the compliance model is incorporated into a two-state microscopic behavior model which considers both car following and speed limit tracking. Several vehicle trajectories obtained from the simulator experiment are fit to the model with low calibration error. This paper develops a two-state microscopic model that can be implemented in future microsimulation research to improve the accuracy of modeled behavior. A limitation in the conducted study, and consequently a room for future improvement, is the homogenous make-up of the driving simulator participants.

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

18-03711

English

15p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Photos; References; Tables

Automobile drivers; Automobile driving; Behavior; Car following; Compliance; Driving simulators; Microscopic traffic flow; Microsimulation; Regression analysis; Variable message signs; Variable speed limits; Vehicle trajectories

Highways; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-03711

TRIS, TRB, ATRI

Jan 8 2018 10:55AM