Intersection crossing with reduced number of conflicts
Paper in proceeding, 2018

In this paper, an optimization based algorithm for safe and efficient collaborative driving in intersections is formulated. The problem is to determine the optimal order in which vehicles should travel through an intersection under the assumptions that the longitudinal velocity of all vehicles can be controlled along a predefined path. In the original formulation one quadratic optimization program was solved for each possible crossing order of the vehicles and collisions were avoided by formulating constraints that only allowed one vehicle at the time inside the intersection. To make this algorithm more effective, we formulate less restrictive collision avoidance constraints by introducing one critical zone for each point where two predefined paths cross. It is shown that this formulation leads to a decrease in the number of quadratic optimization programs that need to be solved to find the best crossing order. Further, an algorithm is provided that finds the number of crossing sequences which yield unique formulations of the optimization program. The results show that when simulating more complex scenarios, like four vehicles traveling through an ordinary intersection, the reduction of computational time and the total time it takes for all vehicles to make it through the intersection can be significantly reduced using these less restrictive constraints.

Autonomous vehicles

MPC

Control in intersections

Author

Johan Karlsson

Gdansk University of Technology

Jonas Sjöberg

Chalmers, Electrical Engineering, Systems and control

Nikolce Murgovski

Chalmers, Electrical Engineering, Systems and control

Lowisa Hanning

Susan Luu

Vanessa Olsson

Alexander Rasch

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

1993-1999
978-172810323-5 (ISBN)

21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
Maui, USA,

Automated Driving Applications and Technologies for Intelligent Vehicles (AdaptIVe)

European Commission (EC) (EC/FP7/610428), 2014-01-01 -- 2017-06-30.

Subject Categories

Computational Mathematics

Robotics

Control Engineering

DOI

10.1109/ITSC.2018.8569797

More information

Latest update

6/21/2022