Driver behaviour and traffic accident involvement among professional urban bus drivers in China

Han, Wanli; Zhao, Jianyou

doi:10.1016/j.trf.2020.08.007

Cited by 50 publications

(11 citation statements)

References 45 publications

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“…Castritius et al [36] employed an online questionnaire to investigate the public's willingness and views on platooning technology in Germany and California with 536 participants. At present, besides the SEM, there are several analysis methods to deal with the questionnaire data, such as factor analysis [37], principal component analysis [36], hypothesis testing [31], and correlation analysis [38]. In this paper, given that our purpose was to sort the importance of the questionnaire items, we choose the principal component analysis (PCA) as the analysis tool [39].…”

Section: Subjective Awareness Surveymentioning

confidence: 99%

How to Use Advanced Fleet Management System to Promote Energy Saving in Transportation: A Survey of Drivers’ Awareness of Fuel-Saving Factors

Zhang

Bai

et al. 2021

Journal of Advanced Transportation

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Despite the broad application of advanced fleet management systems (FMSs) in third-party logistics (3PL) companies, there is a marginally limited understanding of how to employ them to enhance transport energy efficiency. In a case study of a Chinese 3PL company, this paper analyzed data obtained from the online FMS to assess drivers’ awareness of fuel-saving factors. A questionnaire was primarily designed to investigate the drivers’ awareness of fuel-saving factors based on the reliability and validity test. Then, Extreme Gradient Boosting (XGBoost), a machine learning algorithm, was utilized to explore the intrinsic impacts of various factors on fuel consumption with the outputs providing the evaluation basis for individual awareness of the drivers. The results show a significant deviation in the driver’s awareness of fuel-saving factors, among which the three indicators of engine speed, idling condition, and rolling without engine load are seriously underestimated, while the indicators related to the environment are seriously overestimated due to social expectations. In addition, the average speed was found to be the most important fuel-saving indicator besides the load. Based on these findings, this paper recommends that the 3PL companies choose a route with more freeways when planning, and the mileage should be controlled within 800 km as far as possible.

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Section: Subjective Awareness Surveymentioning

confidence: 99%

How to Use Advanced Fleet Management System to Promote Energy Saving in Transportation: A Survey of Drivers’ Awareness of Fuel-Saving Factors

Zhang

Bai

et al. 2021

Journal of Advanced Transportation

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“…For instance, bus drivers in Santiago, Chile were interviewed to model their behaviors [81]. The purpose of the current study was to scrutinize the relationships involving different types of driver behavior (inattention errors, errors, and violations), demographic information (mobility, age, and driving experience), traffic accidents, and self-assessment [111].…”

Section: B Survey Data Collectionmentioning

confidence: 99%

“…It is essential to understand and perceive the influencing factors of professional urban bus driver behavior in order to maintain road safety [52,63,111]. Vehicle type is also considered as a fruitful area of research given its significant influence on road safety and number of accidents [12,23,31,35,44,49,50].…”

Section: ) Benefits Of Road Safetymentioning

confidence: 99%

“…Work zone design and assessment, particularly taper configuration in urban terrain, is another aspect that should benefit from further evaluation [21]. A system to adopt traffic safety is also recommended to remind drivers of traffic conflicts and accidents and to promote positive traffic culture, rather than creating the fear of hazard [111]. More studies in similar contexts are needed to provide better interpretation of the performance under different circumstances [7].…”

Section: ) Recommendations Of Traffic Safetymentioning

confidence: 99%

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A Landscape of Research on Bus Driver Behavior: Taxonomy, Open Challenges, Motivations, Recommendations, Limitations, and Pathways Solution in Future

et al. 2021

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Driver behavior is a concerning issue in the area of intelligent transportation system (ITS). Driver behavior is a significant key player in a wide range of unpleasant events during the ride, such as accidents or crashes, traffic congestion, harsh braking, and acceleration/deceleration. Influencing factors of driver behavior have been explored in several studies. It is imperative to investigate these factors in order to provide a comprehensive analysis and to categorize them on the basis of a coherent taxonomy. With that, this study conducted a systematic review on prior studies that focused on bus driver behavior, particularly in the ITS. This study also established a taxonomy on the topic of driver behavior in multiple areas of ITS and their classifications. Different databases, namely ScienceDirect, Web of Science, and IEEE Explore, were utilized to obtain relevant articles from 2008 to 2021 (15 April). Several filtering and scanning stages were performed according to the exclusion/inclusion criteria on all 2,803 articles obtained; however, only 87 articles met the criteria. The final set of articles were categorized into a taxonomy. The first part of the taxonomy focuses on five main factors that influence driver behavior: environmental, demographic, habit, vehicle, and on-road routine factors. The second part of the taxonomy discusses the mapping of data collection methods on the basis of four categories: real-time data collection, survey, simulation, and benchmark. Discussion and analysis were provided to highlight the critical literature gaps on bus driver behavior in the ITS, involving the use of real-time data collection, which is imperative for acquiring highly accurate and sophisticated data. This multi-field systematic review has exposed new research opportunities, motivations, challenges, limitations, and recommendations and highlighted the need for the synergistic integration of interdisciplinary works. Overall, this study presented pathways solution in future direction on the basis of three sequenced phases, namely design, labeling and validation, and machine learning. This study can serve as a guide for future researchers, as it addressed the ambiguities in the ITS-driver behavior domain and provided valuable information on these ITS-driver behavior trends.

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“…Some scholars have done research on unsafe behaviors using the traditional method of a questionnaire or a simulated driving experiment [14]. Sullman et al [15], Han and Zhao [16], and Shirmohammadi et al [17] studied the crash risk level by a driving simulator. Figueira et al [18] studied traffic crash risk level by driving simulator.…”

Section: Introductionmentioning

confidence: 99%

Survival analysis of the unsafe behaviors leading to urban expressway crashes

Ning

Bai

2022

PLoS ONE

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A common cause of vehicle crashes on urban expressways lies in the unsafe behaviors of drivers. This study focused on analyzing the influence of various unsafe behaviors on crash duration. Based on actual video image of vehicle crashes, 14 unsafe behaviors were identified for the analysis of crashes on urban expressways. Using the correspondence analysis method, the correlation among unsafe behaviors and collision types was obtained. Nonparametric survival analysis was then presented to obtain the survival rate curves of sideswipe crashes and rear-end crashes. Finally, parametric survival analysis method can get the influence of unsafe behaviors on crash duration. The survival rate of any time was quantified through the reasoning of key unsafe behaviors for different types of crashes. The results show that there were striking differences in the duration among different types of crashes. The unsafe behaviors had a significant impact on duration for different types of crashes. This study focused on the duration under the influence of unsafe behaviors before the crash, and the results provide valuable information to prevent crashes, which can improve traffic safety.

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Driver behaviour and traffic accident involvement among professional urban bus drivers in China

Cited by 50 publications

References 45 publications

How to Use Advanced Fleet Management System to Promote Energy Saving in Transportation: A Survey of Drivers’ Awareness of Fuel-Saving Factors

How to Use Advanced Fleet Management System to Promote Energy Saving in Transportation: A Survey of Drivers’ Awareness of Fuel-Saving Factors

A Landscape of Research on Bus Driver Behavior: Taxonomy, Open Challenges, Motivations, Recommendations, Limitations, and Pathways Solution in Future

Survival analysis of the unsafe behaviors leading to urban expressway crashes

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