Comparative Analysis of Fixed and Dynamic Adaptive Cruise Control Settings for Automated Vehicles using Microsimulation

Partially Automated Vehicles (AVs) with Adaptive Cruise Control (ACC) have been introduced, and their impacts have mainly been studied through microsimulation. Most research varies ACC headway settings to represent driving styles but assumes they remain constant. In reality, drivers often adjust headway due to traffic conditions. This study examines how such dynamic behavior affects traffic efficiency compared to a fixed ACC setting on a highway in Veneto, Italy.

Microsimulation analyses were performed in VISSIM software, considering average travel time, average speed, and flow rate as traffic performance metrics across varying Market Penetration Rates (MPRs) of AVs, ranging from 0% to 100% in a step of 25%. ANOVA was used for statistical testing.

The results indicated that with an increase in MPRs of AVs, travel time increases, while speed and flow rate reduce. Dynamically changing the headway settings for ACC further worsens traffic performance metrics, where travel time increases by about 55%, speed and flow rate reduce by about 30% and 25%, respectively.

These results highlight the importance of incorporating realistic drivers’ preferences in ACC modeling, as neglecting the dynamic nature of headway preferences in ACC users may lead to overly optimistic evaluations of AV impacts on traffic efficiency.

In this study, traffic performance declined as AV penetration increased, and the effects were stronger when drivers adjusted headway dynamically rather than keeping it fixed. These outcomes emphasize the need to reflect realistic driving behavior in ACC modeling to generate more reliable expectations for future traffic operations.