Road-Network-Based Event Information System in a Cooperative ITS Environment

Author:

Lee Kieun1ORCID,Hong Dongwon1,Kim Juhyun1,Cha Dongkeun1,Choi Hyunmin1,Moon Jeongmin1,Moon Changjoo1ORCID

Affiliation:

1. Department of Smart Vehicle Engineering, Konkuk University, Seoul 05029, Republic of Korea

Abstract

This study proposes and implements an intelligent transportation system (ITS)-based system that collects road event information via a vehicle’s on-board unit (OBU) and roadside unit (RSU), integrates and processes information based on the database and the road network, and provides information to vehicles. This system enables the collection of road unit information without calculating the exact location of event information recognized by the vehicle and facilitates duplicate processing of information recognized from multiple sources. This information can then be provided to other vehicles or road operators via apps or the web, enabling immediate response to emergency situations or changes in road conditions. To verify the practical applicability of this system, we developed a prototype and validated its functions through experiments. Using this system and methods, general drivers, autonomous vehicles, and infrastructure can cooperate in an ITS environment to recognize and propagate various road situations, contributing to the creation of safer and more efficient roads.

Funder

the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korean Government

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference35 articles.

1. ETSI (2023, May 24). TR 102 v1.1.1 2011-06 Intelligent Transport Systems (Its); Vehicular Communications; Basic Set of Applications; Local Dynamic Map (ldm); Rationale for and Guidance on Standardization. Available online: https://www.etsi.org.

2. Chakraborty, P., Sharma, A., and Hegde, C. (2018, January 4–7). Freeway traffic incident detection from cameras: A semi-supervised learning approach. Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA.

3. (2023, May 24). An Unexpected Accident on the Road, AI CCTV Finds It and Informs You in 1 Minute [Website]. Available online: https://www.yna.co.kr/view/AKR20200427164700003.

4. Gokasar, I., Timurogullari, A., Özkan, S.S., Deveci, M., and Lv, Z. (2022). MSND: Modified standard normal deviate incident detection algorithm for connected autonomous and human-driven vehicles in mixed traffic. IEEE Trans. Intell. Transp. Syst., 1–10.

5. Shin, S., Kim, J., and Moon, C. (2021). Road dynamic object mapping system based on edge-fog-cloud computing. Electronics, 10.

Cited by 2 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

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