Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion
Journal article, 2019

Collision avoidance at intersections involving a host vehicle turning left across the path of an oncoming vehicle (Left Turn Across Path/Opposite Direction or LTAP/OD) have been studied in the past, but mostly using simplified interventions and rarely considering the possibility of crossing the intersection ahead of a bullet vehicle. Such a scenario where the driver preference is to avoid a collision by crossing the intersection ahead of a bullet vehicle is considered in this work. The optimal vehicle motion for collision avoidance in this scenario is determined analytically using a particle model within an optimal control framework. The optimal manoeuvres are then verified through numerical optimisations using a two-track vehicle model, where it was seen that the wheel forces followed the analytical global force angle result independently of the other wheels. A Modified Hamiltonian Algorithm (MHA) controller for collision avoidance that uses the analytical optimal control solution is then implemented and tested in CarMaker simulations using a validated Volvo XC90 vehicle model. Simulation results showed that collision risk can be significantly reduced in this scenario using the proposed controller, and that more benefit can be expected in scenarios that require larger speed changes.

LTAP/OD

Driver assistance systems

Intersection accidents

Optimal control

Integrated vehicle motion control

Collision avoidance

Author

Adithya Arikere

Chalmers, Mechanics and Maritime Sciences, Vehicle Engineering and Autonomous Systems

American Axle & Manufacturing, Inc.

Derong Yang

Volvo Cars

Matthijs Klomp

Volvo Cars

Chalmers, Mechanics and Maritime Sciences, Vehicle Engineering and Autonomous Systems

Vehicle System Dynamics

0042-3114 (ISSN)

Vol. 57 5 637-664

Areas of Advance

Transport

Subject Categories

Applied Mechanics

Vehicle Engineering

Control Engineering

DOI

10.1080/00423114.2018.1478107

More information

Latest update

9/16/2019