Applications and Communications Requirements of Connected and Autonomous Vehicles

联网和自动驾驶汽车的应用和通信要求

• 批准号: RGPIN-2022-04012
• 负责人: Sakr, Ahmed
• 金额: $ 2.11万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752251
• 关键词: Applications; Communications; Requirements; Connected; Autonomous

Connected and autonomous vehicles (CAVs) are envisioned to transform transportation systems to become safer, less congested, and more efficient. Vehicle-to-everything (V2X) communication enables vehicles and infrastructure to exchange real-time safety-related and situational awareness information which is intended to complement on-board sensors (e.g., radar, lidar, cameras, etc.) and extend the perception range of connected vehicles beyond their line-of-sight. CAVs represent a major innovation that will impact the public, automotive industry, and governments and are expected to revolutionize the way we commute. The main objective of the research program is to explore novel cooperative and autonomous driving (CAD) designs for CAVs and quantify the minimum requirements of V2X for CAD applications to ensure robustness, scalability, and reliability of modern intelligent transportation systems. To achieve this target, the proposed research focuses on two tracks in parallel, namely, Applications and Communications Requirements. The Applications track will focus on developing cooperative maneuvering strategies for CAVs in mixed traffic of connected and unconnected vehicles as well as human-driven and autonomous vehicles that will coexist on the road for the next two decades. For example, an interaction-aware cooperative adaptive cruise control (ICACC) designs will be developed to improve traffic flow and safety by considering the predicted behavior of surrounding noncooperative and unconnected vehicles. The efficiency, safety, and comfort of the developed algorithms will then be evaluated using real-world experimental data collected by real vehicles and/or a small-scale multi-vehicle testbed. The Communications Requirements track aims at investigating the interplay between V2X key performance indicators (e.g., latency, data rate, packet loss, etc.) and the scalability and reliability requirements of CAD applications. This research program will focus on the high-density regime when a large number of connected vehicles are transmitting V2X messages at the same time to evaluate the trade-off of using different levels of cooperation (e.g., status sharing, intent sharing, agreement seeking, and prescriptive messages as per current standards) and the load on the vehicular communication network. This will help to understand the strengths and limitations of the wireless links and to optimize network resources utilization by dynamically limiting the amount of information shared by road users based on the desired degree of cooperation, complexity of the cooperative maneuver, and the current and predicted status of the network. The findings of the research program are expected to attract the attention of the automotive industry, wireless industry, and all levels of the Government of Canada including federal, provincial, and municipal governments to improve efficiency of the road network and reduce the number of lives lost every year in vehicle-related accidents.

互联和自动驾驶汽车（CAV）被设想为改变交通系统，使其变得更安全，更少拥堵，更高效。车联网（V2X）通信使车辆和基础设施能够交换实时安全相关和态势感知信息，这些信息旨在补充车载传感器（例如，雷达、激光雷达、摄像头等）并将联网车辆的感知范围扩展到视线之外。CAV代表了一项重大创新，将影响公众、汽车行业和政府，并有望彻底改变我们的通勤方式。该研究计划的主要目标是探索CAV的新型协作和自动驾驶（CAD）设计，并量化CAD应用程序对V2X的最低要求，以确保现代智能交通系统的鲁棒性，可扩展性和可靠性。为了实现这一目标，拟议的研究重点放在两个并行的轨道上，即应用程序和通信要求。应用轨道将专注于开发CAV在联网和非联网车辆以及未来二十年将在道路上共存的人类驾驶和自动驾驶车辆的混合交通中的协同操纵策略。例如，将开发交互感知的协同自适应巡航控制（ICACC）设计，以通过考虑周围非合作和未连接车辆的预测行为来改善交通流量和安全性。然后，将使用由真实的车辆和/或小规模多车辆试验台收集的真实实验数据来评估所开发算法的效率、安全性和舒适性。通信需求跟踪旨在调查V2X关键性能指标（例如，延迟、数据速率、分组丢失等）以及CAD应用程序的可扩展性和可靠性要求。该研究计划将重点关注大量互联车辆同时传输V2X消息时的高密度状态，以评估使用不同级别合作的权衡（例如，状态共享、意图共享、协议寻求以及按照当前标准的规定消息）和车辆通信网络上的负载。这将有助于了解无线链路的优势和局限性，并通过基于所需的合作程度、合作机动的复杂性以及网络的当前和预测状态动态限制道路用户共享的信息量来优化网络资源利用率。该研究计划的结果预计将引起汽车行业、无线行业和加拿大各级政府（包括联邦、省和市政府）的关注，以提高道路网络的效率，减少每年因车辆相关事故而丧生的人数。