Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network

Liu, Lining; Ye, Xiaofei; Wang, Tao; Yan, Xingchen; Chen, Jun

doi:10.3390/ijerph19106013

Cited by 10 publications

(8 citation statements)

References 21 publications

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“…Some scholars analyze crash severity through decision trees, but for data with inconsistent sample sizes in each category, the information gain is biased toward those features with more values ( 6 ). Some other scholars have used models such as Bayesian networks ( 1 ) and random forests ( 7 ) to explore the influences that affect crash severity. These traditional models are fixed parameter models that consider the estimated parameters of the same factor to be the same for different crash severity levels.…”

Section: Literature Reviewmentioning

confidence: 99%

“…By the end of 2019, there were about 90 million motorcycles, nearly 400 million bicycles, and 300 million electric motorcycles and electric bicycles in China (of which electric motorcycles accounted for 70%). Meanwhile, electric motorcycles and electric bicycles are growing at a rate of 20% per year ( 1 ). The number of electric motorcycles and electric bicycles keeps growing, and at the same time, the number of related traffic accidents is also increasing.…”

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confidence: 99%

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Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

Wang

Jin

Chen

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Exploring the heterogeneity of factors influencing the severity of electric bicycle crashes and electric motorcycle crashes can help target accident prevention policies to improve traffic safety. Therefore, this paper establishes a mean heterogeneity random parameter logit model using crash data from 2016 to 2020 in Guangxi to explore the different factors influencing the severity of crashes involving electric motorcycles and electric bicycles. The results show that the key influences on crash severity differ in electric motorcycle crashes and electric bicycle crashes. At the same time, some common factors affect the two types of crashes to different degrees. In addition, the complex interaction effects of unobserved heterogeneity were considered to explore the random parameters of the two types of crashes. The effect of unobserved heterogeneity on the distribution characteristics of the random parameters was then determined. For example, in electric motorcycle crashes, street lighting at night has a random parameter characteristic. The likelihood of serious crashes decreased when both street lighting at night and vehicle left turn were involved, and decreased when both street lighting at night and no signal control were involved. In electric bicycle crashes, large trucks have a random parameter characteristic. The likelihood of serious crashes increased when both large trucks and motor vehicle lights not turned on were involved, and increased when both large trucks and visibility less than or equal to 200 meters were involved. The results provide a basis for improving the road safety of electric motorcycles and electric bicycles.

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Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 99%

Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

Wang

Jin

Chen

et al. 2023

Transportation Research Record: Journal of the Transportation R

Self Cite

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“…Ye et al [23] analyzed the factors affecting the LOS (level of service) of non-motorized vehicles crossing the signalized intersection, aiming at the mixed non-motorized traffic flow of electric vehicles and bicycles in the Chinese metropolis. Liu et al [24] analyzed the complex coupling relationships among accident factors contributing to the automobile and two-wheeler traffic accidents. The result shows that the Bayesian network (BN) models could reflect the real relationships among the influential factors of the two types of traffic accidents.…”

Section: Research On Traffic Safety For Cyclistsmentioning

confidence: 99%

Analysis of the Relationship between Age and Violation of Traffic Laws and Ordinances in Traffic Accidents on Children

Onishi¹,

Fujiu

Morisaki

et al. 2022

Sustainability

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In Japan, where the birthrate continues to decline, various initiatives are underway to promote traffic safety for children. Although these efforts have helped reduce the number of traffic accidents involving children, an examination of the circumstances under which children were killed or injured in traffic accidents in recent years shows that accidents in which children were riding bicycles accounted for the highest percentage of accidents. We investigated the relationship between the ages of children involved in traffic accidents and violations of traffic laws using traffic accident statistics maintained by the Ishikawa Prefectural Police Headquarters. These records revealed that 16-year-olds were most likely to be involved in traffic accidents. Our analysis of the violations of laws and ordinances with respect to the ages of bicyclists involved in car accidents at intersections found that, of all the age categories, elementary school students had the lowest rate of accidents with no violations and the highest rate of accidents involving a failure to stop. Junior and senior high school students had lower rates of accidents involving a failure to stop than elementary school students. Moreover, at non-intersections, driving safety violations were notably higher for accidents involving bicycling elementary school students than for those in other age groups.

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“…Hediyeh et al conducted a study on pedestrian differences and analyzed the effects of gender, age, the number of pedestrians in the population, crosswalk length, and signal phase on pedestrian movement status, to understand the impact of intersection characteristics on the pedestrian crossing at a micro level [ 11 ]. For the selection of pedestrian crossing behavior indicators, most scholars choose walking speed [ 12 , 13 , 14 ], the number of stops [ 15 ], and whether there is observation behavior [ 16 , 17 ] for analysis. However, the irregular use of pedestrian crosswalks by pedestrians has not been given too much attention, and not many studies have been conducted on it.…”

Section: Literature Reviewmentioning

confidence: 99%

Characterization of Pedestrian Crossing Spatial Violations and Safety Impact Analysis in Advance Right-Turn Lane

Chen

Wang

et al. 2022

IJERPH

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In view of the pedestrian space violation in an advance right-turn lane, the pedestrian crossing paths are divided by collecting the temporal and spatial information of pedestrians and motor vehicles, and the characteristics of different pedestrian crossing behaviors are studied. Combined with the time and speed indicators of conflict severity, the K-means method is used to divide the level of conflict severity. A multivariate ordered logistic regression model of the severity of pedestrian–vehicle conflict was constructed to quantify the effects of different factors on the severity of the pedestrian–vehicle conflict. The study of 1388 pedestrians and the resulting pedestrian–vehicle conflicts found that the type of spatial violation has a significant impact on pedestrian crossing behavior and safety. The average crossing speed and acceleration variation values of spatially violated pedestrians were significantly higher than those of other pedestrians; there is a significant increase in the severity of pedestrian–vehicle conflicts in areas close to the oncoming traffic; the average percentage of pedestrian–vehicle conflicts due to spatial violations increased by 12%, and the percentage of serious conflicts due to each type of spatial violation increased from 18% to 87%, 74%, 30%, and 63%, respectively, compared with those of non-violated pedestrians. In addition, the decrease in the number of lanes and the increase in speed and vehicle reach all lead to an increase in the severity of pedestrian–vehicle conflicts. The results of the study will help traffic authorities to take measures to ensure pedestrian crossing safety.

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Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network

Cited by 10 publications

References 21 publications

Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

Factors Associated With the Severity of Motor Vehicle Crashes Involving Electric Motorcycles and Electric Bicycles: A Random Parameters Logit Approach With Heterogeneity in Means

Analysis of the Relationship between Age and Violation of Traffic Laws and Ordinances in Traffic Accidents on Children

Characterization of Pedestrian Crossing Spatial Violations and Safety Impact Analysis in Advance Right-Turn Lane

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