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Common Traffic Violations of Bus Drivers in Urban China: An Observational Study.

ABSTRACT: To report common traffic violations in bus drivers and the factors that influence those violations in urban China.We conducted an observational study to record three types of traffic violations among bus drivers in Changsha City, China: illegal stopping at bus stations, violating traffic light signals, and distracted driving. The behaviors of bus drivers on 32 routes (20% of bus routes in the city) were observed. A two-level Poisson regression examined factors that predicted bus driver violations.The incidence of illegal stopping at bus stations was 20.2%. Illegal stopping was less frequent on weekends, sunny days, and at stations with cameras, with adjusted incidence rate ratios (IRRs) of 0.81, 0.65 and 0.89, respectively. The incidence of violating traffic light signals was 2.2%, and was lower on cloudy than sunny days (adjusted IRR: 0.60). The incidence of distracted driving was 3.3%. The incidence of distracted driving was less common on cloudy days, rainy or snowy days, and foggy/windy/dusty days compared to sunny days, with adjusted IRRs of 0.54, 0.55 and 0.07, respectively.Traffic violations are common in bus drivers in urban China and they are associated with the date, weather, and presence of traffic cameras at bus station. Further studies are recommended to understand the behavioral mechanisms that may explain bus driver violations and to develop feasible prevention measures.

SUBMITTER: Wang Q

PROVIDER: S-EPMC4570791 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Project description:IntroductionLittle is known about workplace health promotion for bus drivers. Bus drivers are at-risk of chronic disease because they are exposed to the risk factor combination of poor nutrition, low levels of physical activity, high levels of sedentary time and are often overweight or obese. The purpose of this paper is to situate the quantitative baseline data collected from bus drivers within qualitative findings about the socio-cultural context of the workplace.Materials and methodsBaseline data about physical activity, dietary intake and sedentary hours was collected from 58 drivers employed by a large bus company in southeast Queensland. Ten drivers and seven key workplace informants participated in interviews and discussion groups about driver health behaviours, workplace structure, culture, and resources.ResultsThe quantitative results of our study reveal bus drivers have a cluster of poor health behaviours-limited physical activity, lower than recommended consumption of fruit and vegetables and high levels of sitting time during working-hours-which contribute to a high prevalence of overweight and obesity and a heightened risk of chronic disease. The qualitative findings suggest there are individual and structural barriers to improving drivers' modifiable health behaviours. Individual barriers include ingrained poor habits and more pressing life concerns, while structural barriers in the context of the workplace include time constraints, shift work, long days, a lack of work amenities and a general disconnect of drivers with their workplace.ConclusionIn this workplace, health promotion strategies for bus drivers should be prioritised as a means of improving drivers' health. To maximise uptake and effectiveness, these strategies should make use of existing workplace resources and consider the context of workplace health behaviour change. Further research is warranted in a broader sample of Australian bus companies to explore the context of workplace health behavior change so targeted strategies to improve bus drivers' health can be developed.

Project description:Accurate estimation of traffic emissions and analysis of spatio-temporal distribution on urban roads play a crucial role in the development of low-carbon transportation system. Traditionally, a region's emission characteristics have been studied using numerous emission models with GPS-based spatio-temporal data. Due to the heavy data processing needs of GPS-based data, emission characteristics for a large region have been studied by dividing the region into a limited number of smaller areas or units. Additionally, GPS data are based on a few vehicles in the traffic which does not fully reflect road conditions. This paper proposed an approach that can be used to study and calculate the spatio-temporal emission pattern of a region at a roadway section level by using Baidu's online traffic data and COPERT model. The proposed method can be used to estimate road-level emission patterns while avoiding the impact of redundant data in large datasets, making the dataset more reliable, applicable, and scalable. The proposed approach has been demonstrated through a study of spatio-temporal emission patterns in the Qiaoxi district within city of Shijiazhuang, China. Online data crawling technology was used to obtain data on urban road traffic speed and driving distance. The linear reference technology was used to construct a two-layer road network model to conduct the coupling and matching of traffic data with the road network data. The COPERT model was implemented to calculate the average traffic emissions on each road in the road network, and a traffic emission intensity index was proposed to quantify the CO, VOC, NOx and CO2 emissions on urban roads in the study area. The analysis results show that the traffic emission intensity of the expressway, trunk road, secondary road, and branch road is high during the morning peak (7 AM-9 AM) and evening peak (5 PM-7 PM). The sections with higher traffic emission intensity are mainly concentrated on the main roads and secondary roads such as Jiefang South Street, Shitong Road and Xinhua Road. Nearly one-third of 2nd Ring and 3rd Ring roads also have relatively high emission intensity. The research results provide new ideas for estimating traffic emissions in urban road networks and analyzing the spatio-temporal distribution of traffic emissions. The research results can also provide a decision-making basis for traffic management departments to formulate energy-saving and emission-reduction measures and promote the development of urban green and low-carbon transportation.

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Common Traffic Violations of Bus Drivers in Urban China: An Observational Study.

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