Systematic Analysis of the Contributory Factors Related to Major Coach and Bus Accidents in China

Sha, Yongzhong; Junyan, Hu; Zhang, Qingxia; Wang, Chao

doi:10.3390/su142215354

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…analysis is an important part of grey system theory. Its basic principle is to calculate the grey correlation degree to measure the correlation between sequences by studying the magnitude of correlation between comparison sequence and reference sequence, so as to assist in decision-making, which has the advantages of small calculation and high applicability [39][40][41][42]. Te specifc steps of the grey correlation analysis method in this study are as follows:…”

Section: Grey Correlation Analysis Method Grey Correlationmentioning

confidence: 99%

Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient

Wang

Ding

Wang

2023

Journal of Advanced Transportation

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Cell phone call operations during driving can lead to distraction and cause potential safety hazards. In order to quantitatively characterize the influence of cell phone call mode on the driver’s visual behavior in different traffic conditions and to analyze the risk level of distracted driving from the visual level, a distracted driving simulation test was carried out based on a driving simulator and eye tracker. The eye movement data of drivers during normal driving, hands-free call, and video call under two typical traffic conditions of free flow and congested flow on the urban expressway were collected. Firstly, four visual characteristics indicators that were highly sensitive to traffic conditions and driving states were selected in terms of visual field range, visual recognition, visual search, and visual load, which were the information entropy of fixation area (IEFA), saccade amplitude, peak-to-average ratio of saccade velocity (PARSV), and relative change intensity of pupil area (RCPA). Then, based on the improved CRITIC method, the visual stability coefficient (VSC) was constructed as a new indicator to comprehensively assess the risk level of the driving state, and the assessment criteria were divided. Finally, the grey correlation analysis method was introduced to verify the assessment effect of VSC. The results show that different cell phone call modes increased driving risk in both traffic conditions. Among them, the negative influence of video calls on driving safety was significantly higher than that of hands-free calls, with a significant decrease in VSC, and the drivers’ VSC in the free flow scenario was more sensitive to the impact of cell phone call operation, and the driving risk increased significantly during distracted driving. The VSC can quantitatively assess driving risk from the perspective of visual psychological safety and contributes to the development of corresponding early warning and control measures.

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Section: Grey Correlation Analysis Method Grey Correlationmentioning

confidence: 99%

Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient

Wang

Ding

Wang

2023

Journal of Advanced Transportation

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Causal analysis of coach and bus accidents in China based on road alignments

Zhang¹,

Lu²,

Fan³

et al. 2023

Heliyon

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A study on human errors of air traffic controllers based on HFACS-AHP

Zhu,

Chen

2023

JCM

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Safety is the lifeline of civil aviation. With the advancement of technology, human factors have become the primary factor affecting aviation safety. Among these, human errors in air traffic control (ATC) account for a significant proportion of aviation accidents. In order to investigate human errors in ATC, this paper introduces two common human factors conceptual models – the Reason model and the HFACS model, and analyzes the specific application of the HFACS model in aviation. It is found that the HFACS model can effectively establish a classification system for human errors in ATC. Moreover, this paper combines the HFACS model with AHP (Analytic Hierarchy Process) and uses the HFACS model to establish a first and second level indicator system for human errors in ATC. We calculated the weights of each specific factor using the Analytic Hierarchy Process. The results show that the most significant influencing factor in the first level indicators is organizational factors, while the most significant influencing factor in the second level indicators is Air Traffic Resource Management. Among the 13 second level indicators, the smallest weight is the controller’s violation. Based on the calculated weight results, in order to improve the safety level of ATC, the first step should be to improve the level of ATC organizational management. This is also of great significance for improving the safety level of the entire aviation system. The findings of this study suggest that the HFACS model, combined with AHP, can be an effective tool for identifying and analyzing human factors in ATC and ultimately improving the safety of the aviation industry.

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Systematic Analysis of the Contributory Factors Related to Major Coach and Bus Accidents in China

Cited by 3 publications

References 49 publications

Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient

Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient

Causal analysis of coach and bus accidents in China based on road alignments

A study on human errors of air traffic controllers based on HFACS-AHP

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