Citation

Ossenbruggen PJ. J. Transp. Eng. A: Systems 2022; 148(9): e04022057.

Copyright

(Copyright © 2022, American Society of Civil Engineers)

DOI

10.1061/JTEPBS.0000700

PMID

unavailable

Abstract

In this study, 20 drivers, who maintain a safe distance at all speeds, are monitored to help determine the principal reason for trip delay. The aim was to develop a driver-assisted technology device or devices to enhance driver comfort and safety. The use of vehicle-to-vehicle (V2V), vehicle-to-everything (V2X), or a combination of devices that can quickly collect and analyze data is contemplated. Collecting real-time driver response data is a challenge and extremely expensive. For these reasons, a stochastic car-following model, called a car-following network model (CFNM), was developed. It features 20 simulated passenger-car drivers traveling around a test track with 2 cruising zones and a bottleneck. Each driver strives to minimize the individual trip time. The model accounts for (1) driver decision-making lapses made over time, (2) a driver's inability to precisely control speed, and (3) a driver's desire to comfortably accelerate and decelerate. Vehicle acceleration and deceleration rates are constrained for (4) driver comfort, and (5) driver health, i.e., vehicle top and lower speeds are adjusted to limit

Keywords

Behavioral models; Car following; Delay; Markov chain; Microscale models; Stochastic models