Author(s)

Lai Wei, XiChan Zhu, ZhiXiong Ma^*

Affiliation(s)

School of Automotive Studies, Tongji University, Shanghai, 201804, China.

Corresponding Author

ZhiXiong Ma^*

ABSTRACT

In order to scientifically and reasonably test and evaluate the driving ability and behavior of intelligent vehicles in urban scenarios, it is necessary to first cover all types of scenes for the most complex intersection scenes in the city. However, due to the current research mostly using simple intersection shapes for scene classification, it is difficult to achieve exhaustive and traversal of all types of scenes at intersections. This article innovatively proposes the use of road rights composed of a limited number of combinations of directional arrows and traffic signals in the lane as the classification basis for intersections. Through research and summarization, all combination types are obtained, and the frequency distribution of all combination types is statistically analyzed in the automobile demonstration area. Based on this, the classification is carried out, laying the foundation for the testing and evaluation of intelligent vehicles in urban working conditions.

KEYWORDS

Testing and evaluation; Intersection classification; Urban scene; Right of way

CITE THIS PAPER

Lai Wei, XiChan Zhu, ZhiXiong Ma. Construction of classification method for urban road intersections. Eurasia Journal of Science and Technology. 2025, 7(2): 55-62. DOI: https://doi.org/10.61784/ejst3076.

REFERENCES

[1] Zhou Jianhua, Song Rui, Liu Mingyang, et al. Research on Key Technologies of Autonomous Driving Perception and Recognition in Intersection Scenarios. China Automotive, 2022 (05): 32-38.

[2] Liu Chunxu. Research on Real time Signal Intelligent Control Technology for Complex Intersections. Chongqing Jiaotong University, 2013.

[3] Ying Shen, Liang Yuanyi, Jiang Yuewen, et al. Intersection classification and vehicle driving methods and equipment adapted to autonomous driving. Hubei Province: CN115366887A, 2022.

[4] Ma Xuehan, Zhu Xichan, Ma Zhixiong. Analysis of traffic classification and violations in natural driving research//State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University. Infots Procedures of the 14th International Forum of Automotive Traffic Safety, 2017: 28-41

[5] GB 5768.2-2022, Road traffic signs and markings - Part 2: Road traffic signs. 2022. Retrieved from https://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=15B1FC09EE1AE92F1A9EC97BA3C9E451

[6] GB 5768.3-2009, Road traffic signs and markings Part 3: Road traffic markings. 2009. Retrieved from https://std.samr.gov.cn/gb/search/gbDetailed?id=71F772D7C970D3A7E05397BE0A0AB82A

[7] GB 14886-2016, Specification for Setting and Installation of Road Traffic Signal Lights. 2016. Retrieved from https://std.samr.gov.cn/gb/search/gbDetailed?id=71F772D8163DD3A7E05397BE0A0AB82A

[8] IVISTA National Intelligent Automotive Integration System Test Zone IVISTA China Intelligent Vehicle Index Navigation Intelligent Driving Evaluation Regulations (2020 Revised Edition) [S/OL]. 2020. Retrieved from https://www.i-vista.org/d/file/p/2022-09-27/98f534dad920e6f4515376d98b21d69f.pdf