Typical accident scene extraction and accident factor association rules analysis for truck-two-wheeler collisions
Typical accident scenarios of truck-two-wheeler collisions were extracted based on video information.The correlation among accident factors within these scenarios was explored using association rules analysis to elucidate accident characteristics that were not typically described by typical accidents.Accident information was extracted from 210 cases of truck-two-wheeler accidents with accompanying video information sourced from the internet.These cases were then subjected to K-modes clustering to obtain typical accident scenarios.Subsequently,association rule mining was employed to analyze the degree of association among accident factors within each accident scenario.The results show that truck-two-wheeler accidents can be categorized into four typical scenarios,namely two types of intersection accidents,one straight road accident,and one T-junction accident.In intersection accidents,there is a high association between accident features and the presence of visual obstacle.The accident featuring a"truck turning left"will cause high accident risk.In straight road accidents,there is an association between truck braking for avoidance and the presence of traffic signals on the road.In T-junction accidents,there is an association between medium-sized truck steering for avoidance and two-wheeler riders being crushed.These research findings can provide reference to safety measures and safety testing scenarios for two-wheeler riders.
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