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Calibrating Microscopic Car-Following Models for Adaptive Cruise Control Vehicles: Multiobjective Approach
| 题名： | Calibrating Microscopic Car-Following Models for Adaptive Cruise Control Vehicles: Multiobjective Approach |
| 正文语种： | eng |
| 作者： | Felipe de Souza;Raphael Stern |
| 作者单位： | Div. of Ene Systems Argonne National Laboratory 9700 Cass Ave. Lemont IL 60439;Dept. of Civil Environmental and Geo-Engineering Univ. of Minnesota 500 Pillsbury Dr. SE Minneapolis MN 55455 |
| 摘要： | Adaptive cruise control (ACC) vehicles are the first step toward comprehensive vehicle automation. However, the impacts of such vehicles on the underlying traffic flow are not yet clear. Therefore, it is of interest to accurately model vehicle-level dynamics of commercially available ACC vehicles so that they may be used in further modeling efforts to quantify the impact of commercially available ACC vehicles on traffic flow. Importantly, not only model selection but also the calibration approach and error metric used for calibration are critical to accurately model ACC vehicle behavior. In this work, we explore the question of how to calibrate car-following models to describe ACC vehicle dynamics. Specifically, we apply a multiobjective calibration approach to understand the trade-off between calibrating model parameters to minimize speed error versus spacing error. Three different car-following models are calibrated for data from seven vehicles. The results are in line with recent literature and verify that targeting a low spacing error does not compromise the speed accuracy whether the opposite is not true for modeling ACC vehicle dynamics. |
| 出版年： | 2021 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 147 |
| 期： | 1 |
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