International Journal of Automotive Engineering
Online ISSN : 2185-0992
Print ISSN : 2185-0984
ISSN-L : 2185-0992
Selected and Extended Papers from AVEC14
Motion Planning and Control of Autonomous Driving Intelligence System Based on Risk Potential Optimization Framework
Pongsathorn RaksincharoensakTakahiro HasegawaMasao Nagai
Author information

2016 Volume 7 Issue AVEC14 Pages 53-60


This study proposes a motion planning and control system based on collision risk potential prediction characteristics of experienced drivers. Recently, automatic braking systems have been deployed in current automotive markets. However, the existing systems cannot avoid collisions in critical scenario such as a pedestrian suddenly darting out from a poor-visibility blind corner. By optimizing the potential field function in the framework of optimal control theory, the desired yaw rate and the desired longitudinal deceleration are theoretically calculated. Finally, the validity of the proposed motion planning and control system is verified by comparing the simulation results with the actual driving data by experienced drivers.

Content from these authors
© 2016 Society of Automotive Engineers of Japan, Inc

This article is licensed under a Creative Commons [Attribution-NonCommercial-ShareAlike 4.0 International] license.
Next article