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

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5135-5148, 2022, DOI:10.32604/cmc.2022.027356

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… More >

Xingjian Xue^1,*, Zixu Wang¹, Linjuan Ge¹, Lirong Deng¹, Rui Song¹, Neal Naixue Xiong²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2779-2791, 2021, DOI: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… More >