Abstract

Path-to-trajectory conversion problem for car-like autonomous ground vehicles has been studied in various ways. It is challenging to generate a trajectory which is dynamically feasible for the vehicle and comfortable for the passengers. An important practical concern of low computational costs makes the problem even more difficult. In this work, a path-to-trajectory converter is developed using a novel receding-horizon type suboptimal algorithm. By transforming the dynamic constraints to a longitudinal velocity limit function in the velocity-acceleration phase plane, a time-sub-optimal trajectory satisfying the dynamic constraints and the initial boundary condition is generated by computing the maximum constant acceleration in the down-range horizon. The portion of the trajectory approaching the end of the path is generated in reverse time. As illustrated by some simulation results and validation on a full-scale Kia Soul EV, the proposed path-to-trajectory conversion algorithm is able to account for dynamic constraints of the vehicle and guarantees passenger comfort.

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