Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7115656 | IFAC-PapersOnLine | 2017 | 7 Pages |
Abstract
This paper focuses on high-level control and decision-making for an autonomous car. We develop a hybrid probabilistic model that describes the motion of a car and its surrounding traffic on a two-lane highway/road, where the acceleration of the car and the lane changes serve as control variables. Using approximate dynamic programming (ADP) techniques and an enhanced version of the value iteration algorithm, a control policy is obtained that maximizes the expected time that the car maintains a prescribed minimum (safe) headway. Simulation results for different settings are provided to validate the approach.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Robert A.E. Zidek, Ilya V. Kolmanovsky,