Fuel Consumption of Adaptive Cruise Control Platoons: Bench Experiments and Data-Driven Estimation for Real Traffic

Thibault Charlottin, Silvia Varotto, Bruno Jeanneret, Sylvain Gillet, Christine Buisson
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Abstract

Vehicles equipped with adaptive cruise control (ACC) systems are expected to improve traffic safety and decrease fuel consumption. Recent experimental studies have shown that ACC leads to string instability in the case of platooning and can, therefore, result in higher energy needs compared with a platoon of human-driven vehicles (HDV). However, the impact of ACC on fuel consumption in the case of platooning and the global impact of ACC fuel overconsumption in traffic are not known yet. This study examines the impact of ACC systems on traffic fuel consumption using experimental data and traffic records. In this study, we inject the speed profiles of ACC and HDV platoons that follow a similar leader trajectory into an engine bench. Then, we identify the event that leads to an overconsumption of fuel in the case of platooning. The results of the engine bench show that only ACC platoons of six or more vehicles with a short time-gap setting consume more fuel than HDV platoons. Using HighD and ExiD records, we detect if the events leading to fuel overconsumption often happen in traffic. The results on HighD and ExiD show that such an event happens once out of 1,250 episodes if we divide the time into episodes of 15 s. This shows that, even if fuel overconsumption exists in specific cases, those cases are actually too rare in traffic to affect global fuel consumption.
自适应巡航控制排的耗油量:真实交通的台架实验和数据驱动估算
配备自适应巡航控制系统(ACC)的车辆有望提高交通安全性并降低油耗。最近的实验研究表明,自适应巡航控制系统会导致排成一排的车辆出现车群不稳定的情况,因此,与一排由人类驾驶的车辆(HDV)相比,自适应巡航控制系统会导致更高的能源需求。然而,目前还不清楚自动控制排成一排对燃料消耗的影响,以及自动控制排成一排对交通燃料过度消耗的总体影响。本研究利用实验数据和交通记录研究了自动驾驶辅助系统对交通燃料消耗的影响。在这项研究中,我们将遵循类似领队轨迹的自动空调系统和 HDV 排队的速度曲线注入发动机工作台。然后,我们确定了在排成一行的情况下导致燃料过度消耗的事件。发动机台架的结果表明,只有六辆或更多车辆组成的 ACC 排在短时间间隔设置下比 HDV 排消耗更多燃料。利用 HighD 和 ExiD 记录,我们可以检测导致燃油消耗过量的事件是否经常发生在交通流中。HighD 和 ExiD 的结果显示,如果我们将时间划分为 15 秒一集,那么在 1,250 集事件中就会发生一次这样的事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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