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contributor authorTian, Yuan
contributor authorZhang, Zihao
contributor authorLi, Zhouyuan
contributor authorFu, Xueqing
contributor authorWang, Guangmao
contributor authorMa, Yuan
contributor authorWu, Jianqing
date accessioned2026-08-20T20:53:13Z
date available2026-08-20T20:53:13Z
date copyright2025/09/09
date issued2025
identifier otherJTEPBS.TEENG-8918.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313619
description abstractAbstractRamp merging areas are high-risk zones for traffic accidents due to the high traffic density and frequent changes in vehicle speed. This study proposes a comprehensive approach that integrates machine learning with feature interpretation to ...Practical ApplicationsRamp merging areas, where vehicles enter or exit highways, are known to be high-risk zones for accidents due to heavy traffic and frequent speed fluctuations. This study offers a new method for assessing the risk of traffic conflicts ...
publisherAmerican Society of Civil Engineers
titleTraffic Conflict Identification and Risk Assessment at Ramp Merging Areas Based on Improved XGBoost and SHAP
typeJournal Article
journal volume151
journal issue11
journal titleJournal of Transportation Engineering, Part A: Systems
identifier doi10.1061/JTEPBS.TEENG-8918
journal fristpage04025091-1
journal lastpage04025091-11
page11
treeJournal of Transportation Engineering, Part A: Systems:;2025:;Volume ( 151 ):;issue: 011
contenttypeFulltext


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