Citation

Horri N, Haas O, Wang S, Foo M, Fernandez MS. Transp. Res. Rec. 2022; 2676(3): 712-727.

Copyright

(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211056636

PMID

unavailable

Abstract

This paper proposes a mode switching supervisory controller for autonomous vehicles. The supervisory controller selects the most appropriate controller based on safety constraints and on the vehicle location with respect to junctions. Autonomous steering, throttle and deceleration control inputs are used to perform variable speed lane keeping assist, standard or emergency braking and to manage junctions, including roundabouts. Adaptive model predictive control with lane keeping assist is performed on the main roads and a linear pure pursuit inspired controller is applied using waypoints at road junctions where lane keeping assist sensors present a safety risk. A multi-stage rule based autonomous braking algorithm performs stop, restart and emergency braking maneuvers. The controllers are implemented in MATLAB® and Simulink™ and are demonstrated using the Automatic Driving Toolbox™ environment. Numerical simulations of autonomous driving scenarios demonstrate the efficiency of the lane keeping assist mode on roads with curvature and the ability to accurately track waypoints at cross intersections and roundabouts using a simpler pure pursuit inspired mode. The ego vehicle also autonomously stops in time at signaled intersections or to avoid collision with other road users.

Language: en

Keywords

automated; bicycles; human factors; intelligent transportation systems; modeling; operations; pedestrians; road user measurement and evaluation; safe systems; safety; transportation safety management systems; vehicle simulation; vehicle technologies; vehicles