Risk Predictive Driver Assistance System for Collision Avoidance in Intersection Right Turns

Author:

Fujinami Yohei,Raksincharoensak Pongsathorn,Ulbricht Dirk,Adomat Rolf, ,

Abstract

Most traffic accidents that result in injuries or fatalities occur in intersections. In Japan, where cars drive on the left, most of such accidents involve cars that are turning right. This situation serves as the basis of the development of our Advanced Driver Assistance System (ADAS) for intersection right turns. This research focuses on the scenario in which an object darts out from the blind spot created by heavy oncoming traffic as a vehicle is making an intersection right turn. When this happens, even if the driver brakes as hard as possible or an active safety function such as the Autonomous Emergency Braking System (AEBS) applies the brakes, the natural limits of physical friction may make it impossible to avoid a collision. To improve traffic safety given the limited potential of physical friction, this research seeks to develop a risk-predictive right-turn assistance system. The system predicts potential oncoming objects and reduces the vehicle velocity in advance. Blind corners can be detected by on-board sensors without requiring information from surrounding infrastructure. This paper presents a right-turn assistance system that avoids conflict with the AEBS in emergencies by decelerating the ego vehicle to a safe velocity.

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Reference10 articles.

1. National Police Agency Traffic Bureau, “Status of Traffic Fatal Accident Occurrence and Status of Violation Control of Road Traffic Act in 2015,” Portal Site of Official Statistics of Japan, p. 29, 2016.

2. Institute for Traffic Accident Research and Data Analysis (ITARDA), “Traffic accident status and Human factorial experiment in signalized intersections,” Abridgement research report in 2012, pp. 6-13, 2012.

3. G. R. De Campos, A. H. Runarsson, and F. Granum, “Collision Avoidance at Intersections: A Probabilistic Threat Assessment and Decision-Making System for Safety Interventions,” 17th Int. IEEE Conf. on Intelligent Transportation System, pp. 649-654, 2014.

4. M. Brannstrom, E. Coelingh, and J. Sjoberg, “Threat assessment for avoiding collisions with turning vehicles,” 2009 IEEE Intelligent Vehicle Symposium, pp. 663-668, 2009.

5. N. Uchida, M. Kawakoshi, T. Tagawa, and E. Akutsu, “Investigation of Right-Turn Accident Risks Based on Traffic-Conflict Data – Traffic Situations and Driving Behavior that Degrade Oncoming Vehicle Detection –,” JARI Research J., Vol.31, No.4, pp. 39-43, 2009.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3