ELLIIT LU P11: Online Optimization and Control towards Autonomous Vehicle Maneuvering

The results obtained so far have mainly been investigating the results of different tire friction models and vehicle behavior models in simulations and offline optimization scenarios. The investigated systems include both standard models reported in the literature and models identified from real test drives. Based on the previous results the new project will focus on the online aspects for re-planning and control and the introduction of more complex vehicle models representing e.g., truck and trailer systems, which comprise non-trivial extension due to significant differences in dynamic behavior. The traffic safety-related issues of heavy vehicles is one important driving factor behind this. Experimental facilities at the Vehicular Lab systems, Linköping University, and corresponding research infrastructure at RobotLab, Lund University, will be employed in e.g., the evaluation of the online path tracking algorithms.
The research is planned along two different routes which can be characterized as “online optimized maneuvers” and “narrow lane driving”, respectively. The former focuses on investigating and developing models for optimal control in critical situations (e.g. evasive maneuvers), as well as studying the maneuvering strategies that are obtained from these optimizations and how they can be utilized in future advanced safety systems and autonomous driving The second is related to fundamental properties of path following relaxed to a “narrow lane” and the optimal control problems of both reaching and traversing along this lane subject to e.g. actuator saturation. Project research and outcomes will have synergies with, among others, theWallenberg Autonomous Systems Program (WASP) on safety and autonomous driving.