title: Red-light running rates at five intersections by road user in Changsha, China: An observational study.
abstract: The red-light running rate by type of road users has not been reported in China so far. We conducted an observation study to report the violation rate in Changsha, China. Portable digital devices were used to record red-light running violations at five selected intersections. The observation was performed for three days (weekday, weekend and holiday), four time periods per day and an hour per time period (peak and off-peak hours in the morning and in the afternoon). Violation rate was calculated as number of violations divided by total number of vehicles/pedestrians×100%. We used adjusted violation rate ratio (VRR) to quantify the effects of type of day and time period based on Poisson model. Totally, 162,124 vehicles (including motor vehicles, motorcycles and bicycles) and 31,649 pedestrians were recorded. The red-light running rate was 0.14% for motor vehicle drivers, far lowering than those for motorcyclists (18.64%), bicyclists (18.74%) and pedestrians (18.54%). The rate on holiday was 1.89 times that on weekday for drivers. The rate for motorcyclists was high in off-peak hours (adjusted VRR: 1.11), but low on weekend and on holiday (adjusted VRRs: 0.80 and 0.65). The rate for bicyclists was 32% lower on weekend than on weekday. For pedestrians, the rates were high on weekend and holiday and in off-peak hours (adjusted VRR: 1.09, 1.67 and 1.30). The red-light running rate of motor vehicle drivers is far lower than those for motorcyclists, bicyclists and pedestrians. The effects of type of day and time period on violation rate vary with road users, indicating the type of day and time period should be considered when developing and implementing interventions to reduce red-light running of different road users.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, China. Electronic address: 1510615017@qq.com.
authors.forename: Fangfang
authors.initials: F
authors.lastname: Yan
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, China. Electronic address: vergriffene_aye@163.com.
authors.forename: Beixi
authors.initials: B
authors.lastname: Li
authors.affiliation: Longhua District Centers for Disease Control and Prevention, Shenzhen Municipality, Shenzhen, China. Electronic address: 346810994@qq.com.
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, China. Electronic address: huguoqing009@gmail.com.
authors.forename: Guoqing
authors.initials: G
authors.lastname: Hu
mesh_terms: D000063:Accidents, Traffic; D001334:Automobile Driving; D001642:Bicycling; D002681:China; D002947:Cities; D004779:Environment Design; D006801:Humans; D009049:Motorcycles; D000069636:Pedestrians; D012309:Risk-Taking; D012449:Safety; D012926:Social Control, Formal
keywords: Bicyclists; China; Motor vehicle drivers; Motorcyclists; Pedestrians; Red-light running violation rate