Investigating pedestrian crash patterns at high-speed intersection and road segments:Findings from the unsupervised learning algorithm  

作　　者：Ahmed Hossain Xiaoduan Sun Niaz Mahmud Zafri Julius Codjoe 

机构地区：[1]Department of Civil Engineering,University of Louisiana at Lafayette,Lafayette,LA 70503,United States [2]Department of Urban and Regional Planning,Bangladesh University of Engineering and Technology,Dhaka 1000,Bangladesh [3]Special Studies Research Administrator,Louisiana Transportation Research Center,Baton Rouge,LA,70808,United States

出　　处：《International Journal of Transportation Science and Technology》2024年第2期186-201,共16页交通科学与技术(英文)

基　　金：the support of the Louisiana Department of Transportation Development(LADOTD)for supplying the database used in this study.

摘　　要：Pedestrian crashes at high-speed locations are a persistent road safety concern.Driving at high speeds means that the driver has less time to react and make evasive maneuvers to avoid a pedestrian crash.On top of this,other crash-contributing factors such as humans(pedestrians or drivers),vehicles,roadways,and surrounding environmental factors actively interact together to cause a crash at high-speed locations.The pattern of pedestrian crashes also differs significantly according to the high-speed intersection and segment locations which require further investigation.This study applied association rules mining(ARM),an unsupervised learning algorithm,to reveal the hidden association of pedestrian crash risk factors according to the high-speed intersection and segments separately.The study used Louisiana pedestrian fatal and injury crash data(2010 to 2019).Any crash location with a posted speed limit of 45 mph or above is classified as a high-speed location.Based on the generated association rules,the results show that pedestrian crashes at a high-speed intersection are associated with the intersection geometry(3-leg)and control(1 stop,no traffic control device),driver characteristics(careless operation,failure to yield,inattentive-distracted,older,and younger driver),pedestrian-related factors(violations,alcohol/drug involvement),settings(open country,residential,business,industrial),dark lighting conditions and so on.Most pedestrian crashes at high-speed segments are associated with roadways with no physical separation,dark-no-streetlight conditions,open country locations,interstates and so on.The findings of the study may help to select appropriate countermeasures to reduce pedestrian crashes at high-speed locations.

关 键 词：HIGH-SPEED Unsupervised learning FATAL Alcohol Dark-no-streetlight 

分 类 号：U49[交通运输工程—交通运输规划与管理]