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Video Recognition for Analyzing the Characteristics of Vehicle–Bicycle Conflict

Xingjian Xue1,*, Zixu Wang1, Linjuan Ge1, Lirong Deng1, Rui Song1, Neal Naixue Xiong2

1 College of Logistics and Traffic, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China
2 Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, 74464, OK, United States

* Corresponding Author: Xingjian Xue. Email: email

Computers, Materials & Continua 2021, 69(2), 2779-2791. https://doi.org/10.32604/cmc.2021.016885

Abstract

Vehicle–bicycle conflict incurs a higher risk of traffic accidents, particularly as it frequently takes place at intersections. Mastering the traffic characteristics of vehicle–bicycle conflict and optimizing the design of intersections can effectively reduce such conflict. In this paper, the conflict between right-turning motor vehicles and straight-riding bicycles was taken as the research object, and T-Analyst video recognition technology was used to obtain data on riding (driving) behavior and vehicle–bicycle conflict at seven intersections in Changsha, China. Herein, eight typical traffic characteristics of vehicle–bicycle conflict are summarized, the causes of vehicle–bicycle conflict are analyzed using 18 factors in three dimensions, the internal relationship between intersection design factors and traffic conflicts is explored, and the guiding of design optimization based on the width of bicycle lanes and the soft separation between vehicles and bicycles is discussed. The results showed that colored paved bicycle lanes were better, performing better at a width of 2.5 m compared to 1.5 m. However, the colored pavement was not suitable for the entire road and had to be set at the position, at which the trajectories of a bicycle and motor vehicle overlapped. Thus, a 2.5-m-wide bicycle lane provides good safety. However, there are still defects in the existing safety indicators, so it is necessary to develop new indicators to reflect real vehicle–bicycle conflict situations more comprehensively.

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Cite This Article

X. Xue, Z. Wang, L. Ge, L. Deng, R. Song et al., "Video recognition for analyzing the characteristics of vehicle–bicycle conflict," Computers, Materials & Continua, vol. 69, no.2, pp. 2779–2791, 2021. https://doi.org/10.32604/cmc.2021.016885



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