R2 IM- Robust and Resilient Intersection Management of Connected Autonomous Vehicles
R2 IM- Robust and Resilient Intersection Management of Connected Autonomous Vehicles
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R2 IM- 联网自动驾驶车辆的稳健且有弹性的交叉口管理
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Aviral Shrivastava
中科院分区：
文献类型：
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作者：
M. Khayatian;Rachel Dedinsky;S. Choudhary;Mohammadreza Mehrabian;Aviral Shrivastava
联网自动驾驶车辆 (CAV) 的交叉口管理有可能显着提高安全性和机动性。虽然过去几十年来提出了许多交叉口管理设计，但大多数都假设 CAV 将精确遵循交叉口管理器 (IM) 的指示，并基于此假设证明安全性并证明效率。然而，在现实生活中，穿过十字路口的 CAV 可能会发生故障、加速失控或谎报其信息（例如预期的驶出车道）并导致事故。在本文中，我们首先定义了一个称为“流氓车辆”的故障模型，它本质上是一种不诚实或不遵循 IM 指示的 CAV，然后提出一种新颖的管理算法 $(R^{2}IM)$，即使 CAV 在任何时间点变得“流氓”，该算法也将确保安全运行。我们证明，只要同时不超过一辆“流氓车辆”，十字路口内就不会发生事故。我们通过在 1/10 比例模型 CAV 上进行实验和模拟来证明 $R^{2}IM$ 的安全性。我们还表明，我们的方法可以在恶意车辆离开/被移除后恢复。
Intersection management of Connected Autonomous Vehicles (CAVs) has the potential to significantly improve safety and mobility. While numerous intersection management designs have been proposed in the past few decades, most of them assume that the CAVs will precisely follow the directions of the Intersection Manager (IM) and prove the safety and demonstrate the efficiency based on this assumption. In real life, however, a CAV that is crossing the intersection may break down, accelerate out-of-control or lie about its information (e.g. intended outgoing lane) and cause an accident. In this paper, we first define a fault model called “rogue vehicle”, which is essentially a CAV that either is dishonest or does not follow the IM’s directions and then, propose a novel management algorithm $(R^{2}IM)$ that will ensure safe operation, even if a CAV becomes “rogue” at any point in time. We prove that there can be no accidents inside the intersection, as long as there is no more than one “rogue vehicle” at a time. We demonstrate the safety of $R^{2}IM$ by performing experiments on 1/10 scale model CAVs and in simulation. We also show that our approach can recover after the rogue vehicle leaves/is removed.
DOI：
10.1145/3359986.3361203
发表时间：
2019-10
期刊：
Proceedings of the 17th ACM-IEEE International Conference on Formal Methods and Models for System Design
影响因子：
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作者：
Mohammad Hekmatnejad;Shakiba Yaghoubi;Adel Dokhanchi;H. B. Amor;Aviral Shrivastava;Lina Karam;Georgios Fainekos
通讯作者：
Mohammad Hekmatnejad;Shakiba Yaghoubi;Adel Dokhanchi;H. B. Amor;Aviral Shrivastava;Lina Karam;Georgios Fainekos
影响因子：
2.3
作者：
Khayatian, Mohammad;Mehrabian, Mohammadreza;Shrivastava, Aviral
通讯作者：
Shrivastava, Aviral
DOI：
10.1109/hpec.2019.8916237
发表时间：
2019-09
期刊：
2019 IEEE High Performance Extreme Computing Conference (HPEC)
影响因子：
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作者：
Mohammad Farhadi;Mehdi Ghasemi;Yezhou Yang
通讯作者：
Mohammad Farhadi;Mehdi Ghasemi;Yezhou Yang