Dangerous Situation Recognition Method of Driver Assistance System

Jiao, Chengwu; Jiang, Guiyan; Liu, Ximin; Ding, Tongqiang

doi:10.1109/icves.2006.371576

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Kashani and Mohaymany 26 applied CART model to predict the crash severity on two-lane, two-way rural roads in Iran. In addition, other algorithms, such as artificial network, 27 fault tree analysis (FTA), 28 logistic regression, 29 and Naïve Bayes (NB), 30 have also been adopted to identify traffic crashes and traffic injury severity.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel feature extraction model for traffic injury severity and its application to Fatality Analysis Reporting System data analysis

Yan

Qin³

et al. 2019

Science Progress

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The prevention of severe injuries during crashes has become one of the leading issues in traffic management and transportation safety. Identifying the impact factors that affect traffic injury severity is critical for reducing the occurrence of severe injuries. In this study, the Fatality Analysis Reporting System data are selected as the dataset for the analysis. An algorithm named improved Markov Blanket was proposed to extract the significant and common factors that affect crash injury severity from 29 variables related to driver characteristics, vehicle characteristics, accidents types, road condition, and environment characteristics. The Pearson correlation coefficient test is applied to verify the significant correlation between the selected factors and traffic injury severity. Two widely used classification algorithms (Bayesian networks and C4.5 decision tree) were employed to evaluate the performance of the proposed feature selection algorithm. The calculation result of the correlation coefficient, accuracy of classification, and classification error rate indicated that the improved Markov Blanket not only could extract the significant impact factors but could also improve the accuracy of classification. Meanwhile, the relationship between five selected factors (atmospheric condition, time of crash, alcohol test result, crash type, and driver’s distraction) and traffic injury severity was also analyzed in this study. The results indicated that crashes occurred in bad weather condition (e.g. fog or worse), in night time, in drunk driving, in crash type of single driver, and in distracted driving, which are associated with more severe injuries.

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