Hybrid A*-Based Reverse Path-Planning of a Vehicle with Trailer System
Xincheng Cao, Haochong Chen, Bilin Aksun-Guvenc, Levent Guvenc, Brian Link + 4 more
TLDR
Proposes a modified Hybrid A* algorithm for reverse path-planning of vehicle-trailer systems, incorporating collision avoidance and jackknife prevention.
Key contributions
- Modified Hybrid A* for reverse path-planning of vehicle-trailer systems.
- Incorporates collision avoidance with obstacles and other vehicles.
- Prevents jackknife incidents by adapting steering input limits dynamically.
Why it matters
Reverse parking with trailers is challenging for humans and existing algorithms often lack collision avoidance. This paper provides a robust solution, making autonomous trailer maneuvering safer and more practical. It addresses a critical gap in current path-planning research.
Original Abstract
Reverse parking maneuvering of a vehicle with trailer system is a difficult task to complete for human drivers due to the multi-body nature of the system and the unintuitive controls required to orientate the trailer properly. The problem is complicated with the presence of other vehicles that the trailer and its connected vehicle must avoid during the reverse parking maneuver. While path planning methods in reverse motion for vehicles with trailers exist, there is a lack of results that also offer collision avoidance as part of the algorithm. This paper hence proposes a modified Hybrid A*-based algorithm that can accommodate the vehicle-trailer system as well as collision avoidance considerations with the other vehicles and obstacles in the parking environment. One of the novelties of this proposed approach is its adaptability to the vehicle with trailer system, where limits of usable steering input that prevent the occurrence of jackknife incidents vary with respect to system configuration. The other contribution is the addition of the collision avoidance functionality which the standard Hybrid A* algorithm lacks. The method is developed and presented first, followed by simulation case studies to demonstrate the efficacy of the proposed approach.
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