A self-adaptive IDM car-following strategy considering asymptotic stability and damping characteristics

Zhi Zhou, Linheng Li, Xu Qu and Bin Ran

Physica A: Statistical Mechanics and its Applications, 2024, vol. 637, issue C

Abstract: In this study, based on the comprehensive analysis of asymptotic stability and damping characteristics for the Intelligent Driver Model (IDM) car-following strategy, we propose a self-adaptive IDM (SA-IDM) car-following strategy, which is specifically designed for adaptive cruise control (ACC) vehicles. Using a coefficient of self-adaption, SA-IDM strategy can adaptively adjust the acceleration control function of following vehicle in real time given the velocity of preceding vehicle and time headway, in order to guarantee the asymptotically stable and overdamped condition for the vehicle platoon under any circumstances. The results of simulation experiment for a vehicle platoon with NGSIM dataset indicate that, vehicles can drive more stably and smoothly under traffic perturbation using the proposed SA-IDM strategy than the original IDM strategy, as well as the existing IDMM and E-IDM strategies. Meanwhile, SA-IDM strategy helps to improve the driving safety of vehicle platoon considerably. Overall, SA-IDM strategy provides a promising solution with higher stability, reliability, and safety for the longitudinal car-following control in the roadway traffic.

Keywords: Car-following; Asymptotic stability; Damping characteristics; Intelligent Driver Model; Self-adaptive IDM strategy; NGSIM (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:637:y:2024:i:c:s0378437124000475

DOI: 10.1016/j.physa.2024.129539

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