The motion control of autonomous vehicles with a modular, service-oriented system architecture poses new challenges, as trajectory-planning and -execution are independent software functions. In this paper, requirements for an encapsulated trajectory tracking control are derived and it’s shown that key differences to conventional vehicles with an integrated system architecture exist, requiring additional attention during controller design. A novel, encapsulated control architecture is presented that incorporates multiple extensions and support functions, fulfilling the derived requirements. It allows the application within the modular architecture without loss of functionality or performance. The controller considers vehicle stability and enables the yaw motion as an independent degree of freedom. The concept is applied and validated within the vehicles of the UNICARagil research project, that feature the previously described system architecture to increase flexibility of application by dynamically interconnecting services based on the current use-case.
In this paper, it is investigated how the planning of physically feasible trajectories for automated vehicles can be ensured in a motion control architecture with separated planning and control stages. Within such an architecture, the planning stage shall not be adapted to a specific vehicle during development to assure reusability of developed algorithms. It is shown, that the planning stage does not need any information about downstream modules such as the controller and the actuators, as long as certain physical execution limits are considered during trajectory planning. For these constraints, a feedback loop from the control to the planning stage is proposed that ensures feasible trajectories, as long as these limits are accurately estimated. An additional escalation mechanism is developed to prevent safety critical behavior of the vehicle if errors are made during estimation of the relevant limits. The proposed approach hence encapsulates information within the vehicle and enables a greater separation of planning and execution stages as well as the use of different planning algorithms with a common controller. It can therefore raise the reusability of developed functions and reduce the necessary customization of algorithms to a specific vehicle architecture.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.