2020/10/06 by Felipe de Souza, de Souza, Felipe, Raphael A. Stern +1 · 3 citations
Engineering · Social Sciences · #FOS: Electrical engineering #Systems and Control (eess.SY) #Traffic control and management #Transportation Planning and Optimization #Vehicle emissions and performance #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2010.03109
openalex publication_date 2020/10/06 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Adaptive cruise control (ACC) vehicles are the first step toward\ncomprehensive vehicle automation. However, the impacts of such vehicles on the\nunderlying traffic flow are not yet clear. Therefore, it is of interest to\naccurately model vehicle-level dynamics of commercially available ACC vehicles\nso that they may be used in further modeling efforts to quantify the impact of\ncommercially available ACC vehicles on traffic flow. Importantly, not only\nmodel selection but also the calibration approach and error metric used for\ncalibration are critical to accurately model ACC vehicle behavior. In this\nwork, we explore the question of how to calibrate car following models to\ndescribe ACC vehicle dynamics. Specifically, we apply a multi-objective\ncalibration approach to understand the tradeoff between calibrating model\nparameters to minimize speed error vs. spacing error. Three different\ncar-following models are calibrated for data from six vehicles. The results are\nin line with recent literature and verify that targeting a low spacing error\ndoes not compromise the speed accuracy whether the opposite is not true for\nmodeling ACC vehicle dynamics.\n