Robust Cooperative Adaptive Cruise Control of Hybrid Electric Vehicles in Complex Urban Traffic Situations

合作驾驶在过去几年中受到了极大的关注。车辆通信系统的最新进展使得能够为联网车辆的车队开发更智能的驾驶辅助系统。协同自适应巡航控制器（CACC）是一种驾驶员辅助系统，用于通过由无线车对车（V2V）通信提供的汽车之间的数据交换来调整车辆间距离。除了车辆安全性和驾驶员舒适性之外，CACC还可以通过大幅减少连续的走走停停驾驶来显著提高燃油经济性，特别是在城市地区。在CACC支持的一系列车辆中，汽车可以加速或制动，延迟更少，以最大限度地减少车辆间的距离，从而优化交通效率并提高道路容量。然而，开发可靠的CACC用于实际应用，特别是用于城市驾驶，是一个挑战。由各种复杂的交通场景引起的突发干扰，例如频繁的走走停停驾驶，有时由于交通信号灯、十字路口和紧急停车而出现剧烈的减速和加速，以及超车、变道、切入和切出机动，沿着其他不确定性来源，如V2V通信缺陷和手动驾驶汽车的意外行为，会恶化车队的稳定性，导致车祸。** 在这项研究中，将开发一种新的具有最佳性能的鲁棒CACC合成框架，以在城市驾驶中存在各种未知干扰和不确定性的情况下保持串稳定性。我们的计划是开发和评估多个强大的CACC通过做我们的设计方法的核心步骤之一，在几个不同的方式。在本项目结束时，我们希望确定一种有效的开发方法，以获得最佳性能的强大CACC。拟议的CACC将专为城市交通设计，并使用从车载传感器获得的有关即将到来的驾驶（例如，交通信号灯，十字路口，交通堵塞，道路施工）的更广泛数据，以更少的燃料消耗安全驾驶车辆，同时满足旅行时间和舒适度标准。这些控制器将为混合动力电动汽车（HEV）开发，这是可持续交通的近期替代方案之一。混合动力汽车有额外的电力推进，这使得它们比内燃机车辆更复杂。我们的研究结果将在一定程度上影响合作驾驶辅助系统和自动驾驶领域。设计的控制器还将为加拿大汽车公司制造的汽车增加关键的竞争价值，并使它们处于协同驾驶系统创新的最前沿。这些CACC将提高混合动力汽车的安全性和燃油经济性，同时提高道路通行能力和交通效率。

Cooperative driving has received a great deal of attention in past years. Recent advances in vehicular communication systems enable the development of more intelligent driving assistance systems for a fleet of connected vehicles. Cooperative Adaptive Cruise Controller (CACC) is a driver assistance system for adjusting inter-vehicle distances through data exchanges between cars provided by wireless vehicle-to-vehicle (V2V) communications. In addition to vehicle safety and driver comfort, CACCs can improve significantly fuel economy by substantially reducing successive stop-and-go driving, especially in urban areas. In a string of vehicles supported by CACCs, the cars can accelerate or brake with less delays to minimize inter-vehicle distances, which leads to optimized traffic efficiency and enhanced road capacity. However, developing reliable CACCs for practical implementations, especially for urban driving, is a challenge. Sudden disturbances arising from a wide range of complex traffic scenarios, such as frequent stop-and-go driving sometimes with harsh decelerations and accelerations due to traffic lights, intersections, and emergency stops, as well as overtaking, lane-changing, cut-in and cut-out maneuvers, along with other sources of uncertainty like V2V communication defects and unexpected behavior of manually driven cars, can deteriorate the string stability of platoon and lead to car accidents. ******In this research, a novel synthesis framework for robust CACCs with optimal performance will be developed to maintain the string stability in the presence of various unknown disturbances and uncertainties in urban driving. Our plan is to develop and evaluate multiple robust CACCs by doing one of the core steps of our design methodology in several different ways. By the end of this program, we expect to identify an effective development methodology for robust CACCs with the best performance. The proposed CACCs will be designed for urban transport and use a broader range of data about upcoming driving (for instance, traffic lights, intersections, traffic jams, roadwork) obtained from on-board sensors to drive the vehicle safely with less fuel consumptions, while satisfying travel time and comfort criteria. These controllers will be developed for hybrid electric vehicles (HEVs), one of the near-term alternatives for sustainable transportations. HEVs have additional electric propulsion which makes them more complex than internal combustion engine vehicles. Our results will impact the area of cooperative driver assistance systems, and autonomous driving by some degree. The devised controllers will also add critical competitive value to the cars built by Canadian automotive companies and put them at the forefront of collaborative driving systems innovation. These CACCs will improve HEVs safety and fuel economy while enhancing road capacity and traffic efficiency.