Pro-social control of connected automated vehicles in mixed-autonomy multi-lane highway traffic
Journal article, 2021

We propose pro-social control strategies for connected automated vehicles (CAVs) to mitigate jamming waves in mixed-autonomy multi-lane traffic, resulting from car-following dynamics of human-driven vehicles (HDVs). Different from existing studies, which focus mostly on ego vehicle objectives to control CAVs in an individualistic manner, we devise a pro-social control algorithm. The latter takes into account the objectives (i.e., driving comfort and traffic ef ficiency) of both the ego vehicle and surrounding HDVs to improve smoothness of the entire observable traffic. Under a model predictive control (MPC) framework that uses acceleration and lane change sequences of CAVs as optimization variables, the problem of individualistic, altruistic, and pro-social control is formulated as a non-convex mixed-integer nonlinear program (MINLP) and relaxed to a convex quadratic program through converting the piece-wise-linear constraints due to the optimal velocity with relative velocity (OVRV) car-following model into linear constraints by introducing slack variables. Low-fidelity simulations using the OVRV model and high-fidelity simulations using PTV VISSIM simulator show that pro-social and altruistic control can provide significant performance gains over individualistic driving in terms of efficiency and comfort on both single- and multi-lane roads.

highway

model predictive control

automated vehicle

altruism

connected vehicle

pro-social

traffic control

Author

Jacob Larsson

Student at Chalmers

Furkan Keskin

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

Bile Peng

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

Technische Universität Braunschweig

Balázs Adam Kulcsár

Chalmers, Electrical Engineering, Systems and control, Automatic Control

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

Communications in Transportation Research

2772-4247 (ISSN)

Vol. 1 100019

IRIS: Inverse Reinforcement-Learning and Intelligent Swarm Algorithms for Resilient Transportation Networks

Chalmers, 2020-01-01 -- 2021-12-31.

Subject Categories

Social Psychology

Transport Systems and Logistics

Vehicle Engineering

Control Engineering

Areas of Advance

Transport

DOI

10.1016/j.commtr.2021.100019

More information

Latest update

1/18/2022