Analysis of Factors Affecting Traffic Accident Severity Based on Heteroskedasticity Ordinal Logit

Yan, Zhangcun; Lu, Xiaozhao; Hu, Wanxin

doi:10.1061/9780784482742.048

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…Research on traffic literacy evaluation indexes at home and abroad is scarce, and most literature has focused on researching the factors that affect traffic accidents [4][5][6]. Most traffic accidents occur because traffic participants have a relatively poor understanding of safe traffic, and many scholars have evaluated their status by constructing safe traffic evaluation index systems.…”

Section: Introductionmentioning

confidence: 99%

Optimisation of Driver’s Traffic Literacy Evaluation Index from the Perspective of Information Contribution Sensitivity

Wang

Tian

2021

Journal of Mathematics

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The practice has proven that relying solely on large-scale transportation facilities cannot fundamentally alleviate urban transportation problems. Since the motor vehicle drivers are the main participants of transportation, they should improve their knowledge of transportation. Moreover, the drivers should equally cope with transportation problems. This paper establishes an evaluation index system for traffic literacy of urban drivers. In addition, it proposes a method of information contribution sensitivity to optimise the index system. The main results and achievement of this paper include the following: (1) A traffic literacy evaluation index system including 13 evaluation indexes such as traffic rules and general knowledge of machinery has been constructed. (2) Based on the calculation results of the sensitivity of the information contribution, the first 10 indexes that satisfy the cumulative information contribution rate’s value of greater than 90% are retained and 3 indexes with lower contribution rates are eliminated. This study provides a theoretical framework and basic methods to evaluate the traffic literacy of urban drivers.

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Section: Introductionmentioning

confidence: 99%

Optimisation of Driver’s Traffic Literacy Evaluation Index from the Perspective of Information Contribution Sensitivity

Wang

Tian

2021

Journal of Mathematics

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“…Scholars have paid less attention to the research on traffic literacy, and most of the literature aims to explore the factors that affect traffic accidents (e.g., Lu et al, 2019; Nævestad et al, 2015; Yan et al, 2020), traffic safety (Han et al, 2010), and Transportation Health Literacy (Sargent-Cox et al, 2011). Some scholars believe that one of the factors to improve urban traffic safety is the development of urban safety infrastructure, such as the design of roundabouts (Macioszek, 2020), the design of traffic calming devices (Sołowczuk, 2021), and the intelligent city network (Keyvan-Ekbatani et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Optimization of Evaluation Indicators for Driver’s Traffic Literacy: An Improved Principal Component Analysis Method

Chen

Tian

2022

SAGE Open

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The traditional traffic concept seems to be unable to adapt to the traffic problems brought by cities’ rapid development. People must cultivate new modern traffic literacy to deal with traffic problems. Based on traffic literacy, this paper constructs a traffic literacy evaluation indicator system including 13 evaluation indicators such as traffic rules and mechanical knowledge by summarizing relevant literature. We propose an Improved Principal Component Analysis (I-PCA) method, introduce the concept of information contribution sensitivity, and optimize and empower the traffic literacy indicator system. The primary research is to construct a traffic literacy evaluation indicator system including 13 evaluation indicators such as traffic rules and mechanical knowledge. The top 10 indicators that satisfy the cumulative information contribution rate value greater than 90% are retained, and the three indicators with low contribution rate are excluded. The optimization method can retain the indicator with a relatively large information contribution rate so that the indicator’s weight can genuinely reflect the information content of the corresponding indicator. The optimization method can retain the indicator with a relatively large information contribution rate so that the indicator’s weight can genuinely reflect the information content of the corresponding indicator.

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“…Yan, Zhangcun et al [1] employed the heteroscedastic ordered logit (HORL) model. Casado-Sanz [2] utilized latent cluster analysis as an initial tool to analyze the contributing factors that increase the likelihood of fatal outcomes. Sun et al [3] investigated factors influencing the duration of collisions and conducted geostatistical analysis.…”

mentioning

confidence: 99%

Prediction of road traffic accident severity based on multi-model fusion

Lu,

Huang,

2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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Analysis of Factors Affecting Traffic Accident Severity Based on Heteroskedasticity Ordinal Logit

Cited by 4 publications

References 8 publications

Optimisation of Driver’s Traffic Literacy Evaluation Index from the Perspective of Information Contribution Sensitivity

Optimisation of Driver’s Traffic Literacy Evaluation Index from the Perspective of Information Contribution Sensitivity

Optimization of Evaluation Indicators for Driver’s Traffic Literacy: An Improved Principal Component Analysis Method

Prediction of road traffic accident severity based on multi-model fusion

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