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

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."