IDILIM: incident detection included linear management using connected autonomous vehicles

Abstract

Autonomous vehicle advancements and communication technologies such as V2V, V2I, and V2X have enabled the development of connected and autonomous vehicles. Because CAVs are directly effective in traffic, their application in traffic management and incident management appears promising. They can immediately begin regulating traffic and acting as sensors due to their connectivity to the infrastructure. This research proposes Incident Detection Included Linear Management (IDILIM), a CAV-based incident management algorithm that regulates CAV and traffic speeds based on dynamic and predicted shockwave speeds. The SUMO simulations are carried out on a 10.4-km-long, three-lane facility with 21 sensors every 500 m. In the scenarios, three traffic demands, eleven CAV penetration rates, and varying incident locations, duration, and lanes are used. A total of 20 simulation seeds are used in each scenario.