Optimization and Mathematical Modelling for Path Planning of Cooperative Urban Autonomous Vehicles

城市自主车辆协同路径规划的优化与数学建模

• 批准号: 2383174
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2383174
• 关键词: Optimization; Mathematical; Modelling; Path; Planning

This project in Optimization and Mathematical Modelling for Path Planning of Cooperative Urban Autonomous Vehicles - "Automated vehicles have the potential to transform the way in which we travel and in which transport is provided. The technology is now sufficiently advanced that their deployment is rapidly approaching, with notable developments such as Tesla's Autopilot (so-called level 2/3 automation) and the highly-automated (level 4) such as Volvo's Drive Me. A great deal of attention has been paid on how they will operate and interacts on motorways, but much less effort has been devoted to urban areas, which are potentially much more complex. Urban areas do not always have a notion of well-defined lanes (lane-discipline), making it difficult to deploy current autonomous vehicle technology. In addition, traditional vehicles, parked vehicles, pedestrians and bicycles dynamically influence what would be the optimal trajectory/path for such an autonomous vehicle, both on roads and through intersections. This makes a typical car-following, lane-tracking autonomous control algorithm of less value in the urban context. The goal of this project is to develop an autonomous vehicle controller for groups of vehicles that can take advantage of the higher flow rates available on roads where lanes are not well defined. It will do so by calculating optimal trajectories for a group of autonomous vehicles in interaction with traditional vehicles, parked vehicles, pedestrians and bicycles. This will allow for deployment of autonomous vehicles in areas with irregular lane placement, large numbers of pedestrians, bicycles and parked cars, while taking advantage of platooning of autonomous vehicles both laterally and longitudinally."

这个项目在优化和数学建模的路径规划合作城市自动驾驶汽车-“自动驾驶汽车有潜力改变我们的旅行方式和提供交通。该技术现在已经足够先进，它们的部署正在迅速接近，如特斯拉的Autopilot（所谓的2/3级自动化）和高度自动化（4级），如沃尔沃的Drive Me。人们对它们如何在高速公路上运行和互动给予了大量关注，但对城市地区的关注要少得多，因为城市地区可能要复杂得多。城市地区并不总是有明确的车道概念（车道规则），这使得部署当前的自动驾驶汽车技术变得困难。此外，传统车辆、停放的车辆、行人和自行车动态地影响这种自动驾驶车辆在道路上和通过交叉口的最佳轨迹/路径。这使得典型的车辆跟随、车道跟踪自主控制算法在城市环境中的价值较小。该项目的目标是为车辆群开发一种自动车辆控制器，该控制器可以利用车道不明确的道路上的较高流量。它将通过计算一组自动驾驶车辆与传统车辆、停放的车辆、行人和自行车相互作用的最佳轨迹来实现这一目标。这将允许在车道布置不规则、有大量行人、自行车和停放的汽车的区域部署自动驾驶车辆，同时利用自动驾驶车辆的横向和纵向排队。"