Trajectory Planning of Automated Vehicles in Tube-like Road Segments

TL;DR

This paper introduces a linear programming approach for automated vehicle trajectory planning in tube-like road segments, integrating obstacle avoidance, timing, and dynamic constraints in a spatial framework.

Contribution

It develops a novel spatial-based modeling method that incorporates vehicle dynamics, obstacle avoidance, and constraints for efficient trajectory planning.

Findings

The method effectively plans trajectories considering vehicle dimensions and friction constraints.

Comparison shows the proposed spatial-based approach outperforms traditional time-based methods.

The approach can be extended to dynamic vehicle models for enhanced realism.

Abstract

This paper presents a method based on linear programming for trajectory planning of automated vehicles, combining obstacle avoidance, time scheduling for the reaching of waypoints and time-optimal traversal of tube-like road segments. System modeling is conducted entirely spatial-based. Kinematic vehicle dynamics as well as time are expressed in a road-aligned coordinate frame with path along the road centerline serving as the dependent variable. We elaborate on control rate constraints in the spatial domain. A vehicle dimension constraint heuristic is proposed to constrain vehicle dimensions inside road boundaries. It is outlined how friction constraints are accounted for. The discussion is extended to dynamic vehicle models. The benefits of the proposed method are illustrated by a comparison to a time-based method.