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JRM Vol.35 No.2 pp. 255-261
doi: 10.20965/jrm.2023.p0255
(2023)

Paper:

Study on Control for Prevention of Collision Caused by Failure of Localization for Map-Based Automated Driving Vehicle

Shun Nishimura and Manabu Omae

Graduate School of Media and Governance, Keio University
5322 Endo, Fujisawa, Kanagawa 252-0882, Japan

Received:
October 9, 2022
Accepted:
January 9, 2023
Published:
April 20, 2023
Keywords:
automated driving, collision prevention, steering control
Abstract

In demonstration experiments of automated driving vehicles, lane departures and collisions with roadside structures due to poor vehicle positioning and self-localization have been reported. In this study, we propose a promising method to prevent such departures and collisions, and then validate the proposed method by applying it to an actual automated driving vehicle. The proposed method monitors the target steering angles computed by the automated driving control and limits them before commanded the actuator when there is a risk of colliding with obstacles. As the above-mentioned control is lower-level, it can prevent an automated driving vehicle from colliding with obstacles without complicating upper-level controls. Experiments on an actual automated driving vehicle showed that the steering control structure of the proposed method could prevent an automated driving vehicle from colliding with obstacles by limiting its target steering angle. In addition, the method does not impose excessive limits on the steering angle when the automated driving vehicle follows a normal path and no risk of collision exists.

The map-based automated driving vehicle

The map-based automated driving vehicle

Cite this article as:
S. Nishimura and M. Omae, “Study on Control for Prevention of Collision Caused by Failure of Localization for Map-Based Automated Driving Vehicle,” J. Robot. Mechatron., Vol.35 No.2, pp. 255-261, 2023.
Data files:
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