Evaluating connected vehicle-based weather responsive management strategies using weather-sensitive microscopic simulation

Abstract

The purpose of this study is to perform analysis, modeling, and simulation (AMS) to investigate the effectiveness of connected vehicle (CV)-based Weather Responsive Management Strategies (WRMS) to address safety concerns on freeway corridors under adverse weather conditions. This study investigates three CV-based WRMS applications: Forward Collision Warning (FCW), Early Lane Change (ELC) advisory, and Variable Speed Limit (VSL), designs operational alternatives for WRMS using CV data, and develops an AMS tool using a weather-sensitive microscopic traffic simulator to understand the effectiveness of the three WRMS under different scenarios. Various CV market penetration rates (MPR), weather conditions, and WRMS algorithm settings are tested in this study. The case study is based on a real-world freeway corridor, a segment of the I–80 Connected Vehicle Testbed in Wyoming. The simulation results show the effectiveness of selected WRMS applications and provide operational insights that state and local transportation agencies may use in future strategic planning and operations of their weather-responsive programs.