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Calibrating Microscopic Car-Following Models for Adaptive Cruise Control Vehicles: Multiobjective Approach

机译：校准微观车辆跟踪适应性巡航控制车辆的模型：多目标方法

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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.
机译：自适应巡航控制（ACC）车辆是朝着综合汽车自动化的第一步。然而，这些车辆对底层交通流量的影响尚不清楚。因此，对商业上可获得的ACC车辆的车辆级动力学是感兴趣的，因此它们可以用于进一步的建模努力来量化市售的ACC车辆对交通流量的影响。重要的是，不仅模型选择，而且还有用于校准的校准方法和误差度量对于准确地模拟ACC车辆行为至关重要。在这项工作中，我们探讨了如何校准校准车间模型来描述ACC车辆动态的问题。具体而言，我们应用了一个多目标校准方法来了解校准模型参数之间的权衡，以最大限度地减少速度误差与间距错误。为七辆车的数据校准了三种不同的汽车之后模型。结果符合最近的文献，并验证靶向低间距误差不会损害速度精度是否与建模ACC车辆动态不正确。

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  • 来源
    《Journal of Transportation Engineering》 |2021年第1期|04020150.1-04020150.11|共11页
  • 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;

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