CPS: Small: NSF-DST: Safety-Aware Behaviour-Driven Reinforcement Learning Based Autonomous Driving Solution for Urban Areas

CPS：小型：NSF-DST：基于安全意识行为驱动的强化学习的城市自动驾驶解决方案

• 批准号: 2343167
• 负责人: Xiaopeng Li
• 金额: $ 47.78万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2343167&HistoricalAwards=false
• 关键词: CPS; Small; NSF; DST; Safety

This NSF Cyber-Physical Systems (CPS) project will support research that intends to enhance the operation of automated vehicles (AV) swarms in various traffic environments, including structured intersections (e.g., intersections in the US) and unstructured intersections (e.g., intersections in India). The project will examine the 'Tragedy of the Commons (ToC)'— a situation where AVs, while smart on their own, might cause significant traffic oscillation and disorder when they all use the same logic. The research will also examine human-like 'Emergent Cooperative Behavior (ECB)' in complex traffic situations, aiming to incorporate such cooperative driving behaviors into AV control systems and hoping to achieve efficient operation in multi-agent systems. This project could lead to cutting-edge advancements in collaborative control and management in various traffic environments with AVs, which is crucial as they become more common on our streets. Moreover, insights gained from understanding the 'Tragedy of the Commons' and 'Emergent Cooperative Behavior' in AVs could apply to a broader range of multi-agent systems, potentially influencing fields as varied as financial market algorithms or robotics. The collaboration between the U.S. and India in this endeavor not only paves the way for improved global road performance but also sets new international benchmarks. The primary technical objective of this research is to transition the control and interaction patterns of AVs from the ToC to ECB in diverse traffic environments. The hypothesis that AV control exhibits the ToC such that a stream of AVs may have inferior performance (e.g., causing traffic breakdown) even when an individual AV performs superior (e.g., with less instability) will first be tested. The counterpart of the hypothesis is that human-driven vehicle (HV) behavior manifests the ECB such that while an individual HV may not perform as well, a stream of HVs may maintain reasonable performance even in adverse conditions. This hypothesis will be tested by investigating the Markovian and uniformity properties of AVs and HVs. The Markovian property indicates that the vehicle action is determined by the current traffic state independent of its previous experience, while uniformity implies that vehicles follow a similar behavior rule regardless of the traffic environment. The conjecture that AVs have these properties while HVs do not will be evaluated using field data. How these properties would lead to TOC for AVs yet ECB for HVs with the be examined using analytical modeling and simulation. The finding of these fundamental properties will be used to construct a meta-learning-based AV control approach applicable to both US and Indian intersections, with the intention of reversing the ToC phenomenon for existing AVs and cultivating new AV control using an ECB system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该NSF网络物理系统（CPS）项目将支持打算在各种交通环境中增强自动化车辆（AV）群（包括结构化交叉点（例如，美国的交叉路口）和非结构化的交叉点（例如，印度的交叉点））的研究。该项目将检查“公地的悲剧（TOC）”，这种情况在这种情况下，虽然自身聪明，但在他们使用相同逻辑时可能会引起大量的交通振荡和混乱。该研究还将在复杂的交通情况下检查类似人类的“新兴合作行为（ECB）”，旨在将这种合作驾驶行为纳入AV控制系统，并希望在多代理系统中实现有效的操作。该项目可能会导致与AVS在各种交通环境中的协作控制和管理方面的最先进的进步，这在我们的街道上变得越来越普遍。此外，从理解AVS中的“公地的悲剧”和“新兴合作行为”而获得的见解可能适用于更广泛的多代理系统，可能影响与金融市场算法或机器人技术一样多样化的领域。美国和印度之间在这项工作中的合作不仅为改善全球道路表现铺平了道路，而且为新的国际基准树立了新的基准。这项研究的主要技术目标是将AV的控制和相互作用模式从TOC转变为潜水员交通环境中的欧洲央行。 AV控制表现出TOC的假说，即使单个AV表现出色（例如，不稳定性较小），AVS流的性能也可能较低（例如，导致交通崩溃）。该假设的对应物是，人类驱动的车辆（HV）行为表现出欧洲央行，使得虽然单个HV的性能也不太执行，但即使在提前条件下，HVS也可以保持合理的性能。该假设将通过研究AVS和HVS的马尔可夫和均匀性来检验。马尔可夫属性表明，车辆的行动是由当前的交通状态独立于其以前的经验决定的，而均匀性则意味着车辆遵循类似的行为规则，无论交通环境如何。 AV具有这些属性而HVS的缔合将使用现场数据进行评估。这些特性将如何通过使用分析建模和仿真对HVS的AVS但欧洲央行进行TOC。 The finding of these fundamental properties will be used to construct a meta-learning-based AV control approach applicable to both US and Indian intersections, with the intention of reversing the ToC phenomenon for existing AVs and cultivating new AV control using an ECB system.This award reflects NSF's statutory mission and has been deemed honestly of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.