Modeling Commercial Adaptive Cruise Control (ACC) on Multi-Lane Facilities by Incorporating Receiving-Lane-Change Car-Following

Today's mainstream vehicles are partially automated via an advanced driver assistance system (ADAS) including Adaptive Cruise Control (ACC). ACC uses on-board remote sensor target detection and tracking to automatically adjust speed to maintain a constant time-gap. Contrary to expectations, ACC may reduce capacity at bottlenecks because its delayed response and limited acceleration during queue discharge could increase the average headway. However, this has not been investigated for cases when lane changers enter from the adjacent lane, which prevents accurate analysis for multi-lane roadways. ACC could respond differently for those scenarios, and such car following behavior is often referred as receiving-lane-change (RLC) car following. Using data from carefully planned field tests on lane change car following an RLC car following model was developed in this study. This model has then been integrated into a comprehensive ACC car-following model for microscopic traffic simulation. Lastly, this study proposed a revised ACC car-following model to represent electric vehicles (EV) with ACC, that exhibit significantly different braking and acceleration characteristics verses internal combustion (IC) engine ACC-vehicles.