Novel Time-Delay Side-Collision Warning Model at Non-Signalized Intersections Based on Vehicle-to-Infrastructure Communication

Author:

Lyu NengchaoORCID,Wen Jiaqiang,Wu Chaozhong

Abstract

In complex traffic environments, collision warning systems that rely only on in-vehicle sensors are limited in accuracy and range. Vehicle-to-infrastructure (V2I) communication systems, however, offer more robust information exchange, and thus, warnings. In this study, V2I was used to analyze side-collision warning models at non-signalized intersections: A novel time-delay side-collision warning model was developed according to the motion compensation principle. This novel time-delay model was compared with and verified against a traditional side-collision warning model. Using a V2I-oriented simulated driving platform, three vehicle-vehicle collision scenarios were designed at non-signalized intersections. Twenty participants were recruited to conduct simulated driving experiments to test and verify the performance of each collision warning model. The results showed that compared with no warning system, both side-collision warning models reduced the proportion of vehicle collisions. In terms of efficacy, the traditional model generated an effective warning in 84.2% of cases, while the novel time-delay model generated an effective warning in 90.2%. In terms of response time and conflict time difference, the traditional model gave a longer response time of 0.91 s (that of the time-delay model is 0.78 s), but the time-delay model reduced the driving risk with a larger conflict time difference. Based on an analysis of driver gaze change post-warning, the statistical results showed that the proportion of effective gaze changes reached 84.3%. Based on subjective evaluations, drivers reported a higher degree of acceptance of the time-delay model. Therefore, the time-delay side-collision warning model for non-signalized intersections proposed herein can improve the applicability and efficacy of warning systems in such complex traffic environments and provide reference for safety applications in V2I systems.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference39 articles.

1. Right-Turn Assessment Technique of Intersection Based on Event Chain;Wang;J. Tongji Univ. Nat. Sci.,2018

2. A Safety Evaluation Model for Unsignalized T-Intersections Based on Conflict Probability;Zhang;J. Transp. Inf. Saf.,2015

3. Study on the Framework of Intersection Pedestrian Collision Warning System Considering Pedestrian Characteristics

4. How to present collision warnings at intersections?—A comparison of different approaches

5. A Fixed Sensor-Based Intersection Collision Warning System in Vulnerable Line-of-Sight and/or Traffic-Violation-Prone Environment

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication;Sensors;2024-05-25

2. Vehicle Collision Avoidance Algorithm at Unsignalized Intersection based on Car Following Model;2024 9th International Conference on Electronic Technology and Information Science (ICETIS);2024-05-17

3. Dynamic Risk Detection and Early Warning Strategy for Vehicle Collisions at Signal-free Intersections*;2023 7th International Conference on Transportation Information and Safety (ICTIS);2023-08-04

4. A Survey on Collaborative Collision Warning of Connected Vehicles at Signal-Free Intersections*;2023 7th International Conference on Transportation Information and Safety (ICTIS);2023-08-04

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