Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Arikere, Adithya; Yang, Derong; Klomp, Matthijs · 2019 · Crossref

DOI: 10.1080/00423114.2018.1478107

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Summary

This paper addresses the challenge of collision avoidance in Left Turn Across Path/Opposite Direction (LTAP/OD) intersection scenarios, a common and severe accident type. While previous research has focused on braking interventions or cooperative vehicle-to-vehicle communication, this work investigates a specific driver preference: crossing the intersection ahead of the oncoming "bullet" vehicle rather than stopping. The authors aim to develop an optimal motion control strategy that assists the driver in executing this maneuver safely, leveraging the fast response capabilities of electric propulsion systems to deliver precise torque during the short-duration intervention. The study employs a multi-stage methodology. First, an analytical optimal control framework using a particle model is developed to determine the optimal vehicle motion. The objective function maximizes the distance margin between the host and bullet vehicles at the moment the host crosses the bullet’s path. The authors derive necessary conditions for optimality using Pontryagin’s Maximum Principle, solving for the optimal global force angle and magnitude. These analytical results are then verified through numerical optimizations using both the particle model and a more complex two-track vehicle model. Finally, a Modified Hamiltonian Algorithm (MHA) controller, which utilizes the analytical solution for torque allocation, is implemented and tested in high-fidelity CarMaker simulations using a validated Volvo XC90 vehicle model. The results demonstrate that the analytical particle model provides a robust basis for control, with the two-track model showing that wheel forces align with the analytical global force angle predictions. The MHA controller successfully reduces collision risk in simulated LTAP/OD scenarios. The simulations indicate that the proposed control strategy is particularly effective in situations requiring significant speed changes, allowing the vehicle to navigate the intersection safely ahead of the oncoming traffic. The study also addresses path constraints, showing how the optimal control problem can be augmented to ensure the vehicle remains within road boundaries when necessary. The significance of this work lies in its contribution to advanced driver assistance systems (ADAS) and autonomous vehicle control. By focusing on the under-researched scenario of crossing ahead of an oncoming vehicle, the authors provide a comprehensive online motion control solution that does not rely on external communication systems. The use of electric propulsion assumptions highlights the potential for electrified drivetrains to enhance vehicle controllability in critical safety maneuvers. This approach offers a viable method for improving intersection safety, particularly for non-connected vehicles and vulnerable road users, by providing precise, dynamic assistance that complements driver intent.

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• perception action locomotion