Evaluating the Impact of Adaptive Cruise Control on Freeway Merging Performance Using VISSIM

Abstract

Adaptive cruise control (ACC) is an advanced driver assistance system (ADAS) designed to automatically adjust a vehicle’s speed to maintain a safe following distance, enhancing traffic flow and reducing driver workload. This study evaluates the impacts of ACC on traffic performance using microscopic traffic simulations in PTV VISSIM. A three-mile segment of southbound Interstate 5 (I-5) in California was modeled, incorporating real-world traffic volume and speed data for calibration and validation. The analysis examined five ACC penetration rates (0%, 25%, 50%, 75%, and 100%) under default and varied ACC parameter settings, focusing on key performance metrics such as flow, capacity, speed, and travel time. Additionally, time–space diagrams were generated to visualize vehicle trajectories and examine the microscopic effects of ACC on traffic stability and merging dynamics. The findings reveal that the adoption of ACC significantly enhances traffic flow. Average speeds increased notably with higher penetration rates, and travel times were reduced, particularly under varied ACC parameters, which demonstrated superior performance at lower penetration levels. Vehicle trajectories indicated smoother and more uniform spacing at higher penetration rates, reducing bottlenecks and enhancing merging efficiency. The results underscore the potential of ACC systems to mitigate congestion, increase capacity, and enhance flow stability.