Electrical Engineering

Title: Data-driven analysis of ACC car-following time gaps for different driving contexts
Students: Yusheng Yang &amp; Ruohan Li Supervisor: Jie Zhu Volvo Cars, Fangting Zhou Chalmers, ACE Colleagues from Volvo Cars: Viktor Wänerlöv, Pengcheng Wu Examiner: Balazs Kulcsar, E2
Date: 2025. August 27, 10-11 am Place: E2 Room 5430 Femman
Abstract: Adaptive Cruise Control (ACC) is a key component of the Advanced Driver Assistance System which automatically adjusts the vehicle speed to maintain a safe distance from vehicles ahead. While velocity is the dominant factor for ACC time gap control to keep a safe distance, other relevant factors, such as infrastructure, other road users, traffic density, lead vehicle type, and environmental conditions, influence human driving behavior. In this project, we adopt a data-driven approach to analyze and quantify the influence of these factors on time gap control. We also identify and construct critical scenarios to study the combined impacts of multiple factors. We filter steady car-following driving state on the highway, and apply permutation importance to evaluate the relevance of various factors. In addition, we compare the distribution difference and calculate the confidence interval for the time gap across different traffic groups. We use a Hidden Markov Model (HMM) to cluster different states of cut-in behavior and apply a smoothing filter for sensor fusion data. These methods provide insights into human driving behavior under diverse scenarios. As a result, we propose adaptive time gap recommendations for varying driving conditions to improve user experience.
Welcome! Yusheng, Ruohan and Balazs&nbsp;

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Presentation of master thesis

Master thesis presentations at Electrical Engineering

27 August, 2025

10.00-11.00 Yusheng Yang & Ruohan Li, MPICT and MPALG