Open Access

ARTICLE

Safety Analysis of Riding at Intersection Entrance Using Video Recognition Technology

Xingjian Xue^1,*, Linjuan Ge², Longxin Zeng², Weiran Li², Rui Song², Neal N. Xiong³

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

* Corresponding Author: Xingjian Xue. Email:

Computers, Materials & Continua 2022, 72(3), 5135-5148. https://doi.org/10.32604/cmc.2022.027356

Received 15 January 2022; Accepted 04 March 2022; Issue published 21 April 2022

Abstract

To study riding safety at intersection entrance, video recognition technology is used to build vehicle-bicycle conflict models based on the Bayesian method. It is analyzed the relationship among the width of non-motorized lanes at the entrance lane of the intersection, the vehicle-bicycle soft isolation form of the entrance lane of intersection, the traffic volume of right-turning motor vehicles and straight-going non-motor vehicles, the speed of right-turning motor vehicles, and straight-going non-motor vehicles, and the conflict between right-turning motor vehicles and straight-going non-motor vehicles. Due to the traditional statistical methods, to overcome the discreteness of vehicle-bicycle conflict data and the differences of influencing factors, the Bayesian random effect Poisson-log-normal model and random effect negative binomial regression model are established. The results show that the random effect Poisson-log-normal model is better than the negative binomial distribution of random effects; The width of non-motorized lanes, the form of vehicle-bicycle soft isolation, the traffic volume of right-turning motor vehicles, and the coefficients of straight traffic volume obey a normal distribution. Among them, the type of vehicle-bicycle soft isolation facilities and the vehicle-bicycle traffic volumes are significantly positively correlated with the number of vehicle-bicycle conflicts. The width of non-motorized lanes is significantly negatively correlated with the number of vehicle-bicycle conflicts. Peak periods and flat periods, the average speed of right-turning motor vehicles, and the average speed of straight-going non-motor vehicles have no significant influence on the number of vehicle-bicycle conflicts.

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Keywords

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