We consider the problem of maximizing distance to road agents for a self-driving car. To this extent, we employ a Model Predictive Control (MPC) approach for the steering tracking control of an Autonomous Vehicle (AV). Specifically, we first present a traditional MPC controller, which is then extended to encode the clearance maximization goal by manipulating its cost function and constraints. We provide insights on the additional information needed to achieve such goal, and how this modifies the structure of the original controller. Furthermore, a connection between commonly used safety metrics and clearance to road users is established. We implement the MPC controller using two off-the-shelf numerical solvers, assessing its computational feasibility. Finally, we show experimental results of the proposed approach on public roads in Boston and in Singapore.
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.