Trade-off between safety, mobility and stability in automated vehicle following control: An analytical method

理论(学习稳定性) 计算机科学 电子稳定控制 车辆安全 控制(管理) 运输工程 汽车工程 工程类 机器学习 人工智能
作者
Xiaopeng Li
出处
期刊:Transportation Research Part B-methodological [Elsevier BV]
卷期号:166: 1-18 被引量:29
标识
DOI:10.1016/j.trb.2022.09.003
摘要

A recent empirical study (Shi and Li, 2021) showed that commercial automated vehicles (AVs) became more unstable as the headway was set to a smaller value, implying possible intrinsic tradeoffs between safety, mobility, and stability aspects in AV following control design. This study aims to analytically explain the underlying vehicle control mechanism that dictates these tradeoffs. To this end, a robust optimization model is formulated based upon a parsimonious linear AV following model to capture the first-order tradeoffs between safety, mobility, and stability. The robust optimization model aims to maintain a sufficient safety buffer to avoid collisions against all possible realistic preceding vehicle trajectories. As opposed to a numerical solution, we managed to solve this model to an analytical solution that captures relationships between the key parameters determining safety, mobility, and stability. The analytical solution reveals that improving AV mobility (or reducing AV following headway) would require overcoming more safety challenges (e.g., enhancing vehicle control to maintain a short safety buffer) while causing more string-instability. The theoretical findings are consistent with the empirical observations in previous studies. Further, they provide a possible explanation for the observed string instability of commercial AV following control (e.g., adaptive cruise control) as a tradeoff for a smaller headway. Overall, this study lays a new methodology foundation for incorporating safety in traffic flow analysis that traditionally focused on only mobility and stability. Further, the findings yield a set of managerial insights into reasonable AV following design and its implications to emerging AV traffic management. • Build a robust optimization model relating safety, mobility, and stability. • Capture the tradeoffs between safety, mobility, and stability for commercial AVs. • Solve an analytical formulation for these tradeoffs. • Reveal that improving AV mobility would require overcoming more safety challenges while causing more string instability. • Show the consistency between theoretical findings and empirical observations.
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