Empirical study on car-following characteristics of commercial automated vehicles with different headway settings
Empirical study on car-following characteristics of commercial automated vehicles with different headway settings
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DOI：
10.1016/j.trc.2021.103134
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Xiaowei Shi;X. Li
中科院分区：
文献类型：
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作者：
Xiaowei Shi;X. Li
最近的一项研究(Li，2020)使用简约的线性跟车模型，分析预测了自动车辆(AV)在安全性、机动性和稳定性方面的特性之间的权衡。这项工作旨在通过使用商用自动驾驶系统(例如具有自适应巡航控制(ACC)功能的车辆)的实证实验来验证上述研究中的关键理论发现。我们收集了一排不同间隔设置的多架商用无人机的高分辨率轨迹数据。用数据估计了捕捉安全、机动性和稳定性方面的一阶参数的简约线性AV跟随模型。关键参数的估计结果验证了Li(2020)的几个理论预测。具体地说，研究发现，随着时间延迟设置的增加，相应的安全缓冲器减小，这表明可以以较少追求AV移动性来提高AV安全性，或者相反，AV移动性的改善可能以更严格的安全要求为代价。此外，随着时间延迟设置的增加，AV串的稳定性也会增加，这表明走走停停的流量可能会受到影响的AV移动性的影响。因此，对观察到的商用AV跟随控制(即ACC功能)的字符串不稳定性的一种可能的解释是，汽车制造商可能更愿意以牺牲字符串稳定性为代价来确保相对较短的车头间隔(从而在车辆机动性上获得更好的用户体验)。研究还发现，随着时滞的增加，交通振荡的周期变长，振荡放大变小，这支持了机动性和稳定性之间的权衡。另一方面，现场实验揭示了简单线性模型无法预测的问题。也就是说，在不同的车速和车距设置下，车辆控制灵敏度因子是不同的，关键参数的模型估计结果在不同的速度范围内并不一致。这为研究AV跟随建模中的非线性和随机性开辟了未来的研究需求。
A recent study (Li, 2020) analytically predicted tradeoffs between automated vehicle (AV) following characteristics on safety, mobility, and stability using a parsimonious linear car-following model. This work aimed to verify the key theoretical findings in the above study with empirical experiments using commercial AVs, e.g., vehicles with adaptive cruise control (ACC) functions. We collect high-resolution trajectory data of multiple commercial AVs following one another in a platoon with different headway settings. Parsimonious linear AV-following models that capture the first-order parameters on safety, mobility, and stability aspects are estimated with the data. The estimation results of the key parameters validate several theoretical predictions predicted by Li (2020). Specifically, it was found that as the time lag setting increases, the corresponding safety buffer decreases, indicating that AV safety could be improved with less pursuit of AV mobility or, conversely, AV mobility improvement may come at a cost of more stringent safety requirements. Also, as the time lag setting increases, AV string stability increases, indicating that stop-and-go traffic potentially could be dampened by compromising AV mobility. With this, one possible explanation to the observed string instability of commercial AV following control (i.e., ACC function) is that automakers may prefer to ensure a relatively short headway (and thus better user experience on vehicle mobility) at a cost of compromising string stability. It was also found that as the time lag increases, the cycle period of traffic oscillations gets longer, and the oscillation amplification gets smaller, which supports the tradeoff between mobility and stability. On the other hand, field experiments revealed issues beyond the predictivity of a simple linear model. That is, vehicle control sensitivity factors vary across different speed and headway settings, and the model estimation results for key parameters are not consistent over different speed ranges. This opens future research needs for investigating nonlinearity and stochasticity in the AV following modeling.