Investigating the contributors to hit-and-run crashes using gradient boosting decision trees. by Baorui Han, Haibo Huang, Gen Li, Chenming Jiang, Zhen Yang, Zhenjun Zhu

“…A classification prediction model is established based on a nonlinear method-Gradient Boosting Decision Tree (GBDT) to investigate the factors contributing to a perpetrator's escape behavior in hit-and-run crashes. Given the U.S. Crash Report Sampling System (CRSS) dataset, the model is trained and compared with the state-of-art methods (Classification and Regression Tree, Random Forest, and Logistic Regression). …”
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Determinants of Bicyclist Injury Severity Resulting from Crashes at Roundabouts, Crossroads, and T-Junctions by Jinxing Shen, Tiantong Wang, Changjiang Zheng, Miao Yu

“…Using bicycle-involved crash data in the UK over nine years (from 2009 to 2017), the bicyclist injury severity (with three severity levels: fatal injury, serious injury, and slight injury) was estimated using the generalized ordered logit (GOL) model and partial proportional odds (PPO) model. …”
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Analysis of Influencing Factors of Drivers’ Fault Emergency Response Behavior in CMV-NCMV Crashes by Panyi Wei, Jianling Huang, Yanyan Chen, Jianming Ma, Yunchao Zhang, Shaohua Wang, Ning Chen

“…Drivers’ fault emergency response behavior can easily lead to crashes, resulting in significant economic and property losses. …”
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Analysis of Work-Zone Crashes Using the Ordered Probit Model with Factor Analysis in Egypt by Kairan Zhang, Mohamed Hassan, Mahama Yahaya, Shupeng Yang

“…The exposure to danger underscores the need for proper understanding of the occurrence of work-zone crashes, as well as the risk factors associated with them. …”
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ANALYSIS AND OPTIMIZATION ON VEHICLE LOW SPEED BACK-CRASH DESIGN BASED ON RCAR TESTS by ZHANG Yu, ZHENG ShengWei

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Exploring Factors Contributing to Crash Injury Severity in the Rural-Urban Fringe of the Central City by Biao Wu, Xingyu Wang, Tuo Liu, Naibao Dong, Yun Li

“…To analyze the risk factors influencing the crash injury severity in rural-urban fringes, crash data in rural-urban fringes were collected from Harbin, China. …”
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TOPOLOGICAL OPTIMIZATION DESIGN OF TB LEVEL ENERGY ABSORBER BOX OF GUIDING CRASH CUSHION by LEI ZhengBao, LIU MeiGang, ZHANG JiaBo, CHEN XiaoYong

Subjects: “…Crash cushion…”
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A novel and fast crash simulation method: Revolutionising racetrack safety barrier analysis by Bhavinkumar Arya, Jianchun Yao, John Laurence Davy, Mohammad Fard

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REKAYASA DESAIN CIRCULAR HYBRID CRASH BOX UNTUK PENINGKATAN PERFORMA KELAYAKAN TABRAK by Delia Hani Wakhidah, Moch. Agus Choiron, Yudy Surya Irawan

Subjects: “…crash box…”
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Investigating the Relationship between Traffic Violations and Crashes at Signalized Intersections: An Empirical Study in China by Ze-Hao Jiang, Xiao-Guang Yang, Tuo Sun, Tao Wang, Zheng Yang

“…About 90% of traffic crashes are caused by human factors, within which traffic violations are one of the most typical and common causes. …”
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Research on restraint strategies for rearward-reclined occupants in a frontal rigid barrier crash by Daowen Zhang, Jixiang Yang, Yi Lei, Junlian Yan, Lei Xu

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A Data-Driven Deep Learning Framework for Prediction of Traffic Crashes at Road Intersections by Mengxiang Wang, Wang-Chien Lee, Na Liu, Qiang Fu, Fujun Wan, Ge Yu

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ROBUST DESIGN OF CRASH CUSHION ENERGY-ABSORBING BOX BASED ON THE CRASHWORTHINESS TOPOLOGY OPTIMIZATION by HUANG YuPeng, SONG Jie, LEI ZhengBao

Subjects: “…Crash cushion energy absorbing box…”
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Understanding price momentum, market fluctuations, and crashes: insights from the extended Samuelson model by Qingyuan Han

“…Second, ESM predicts the 1987 Black Monday crash weeks in advance, offering a new perspective on its underlying cause. …”
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TECHNO ECONOMIC ANALYSIS OF BIOMASS AS AN ALTERNATIVE ENERGY HOUSEHOLDS AND SMALL INDUSTRIES by Rany Puspita Dewi, Trisma Jaya Saputra, Mario Ammar Rasyid

Subjects: “…crash box…”
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Crash Prediction on Expressway Incorporating Traffic Flow Continuity Parameters Based on Machine Learning Approach by Tian Lei, Jia Peng, Xingliang Liu, Qin Luo

“…Real-time crash prediction helps identify and prevent the occurrence of traffic crash. …”
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Predicting Wet-Road Crashes Using the Finite-Mixture Zero-Truncated Negative Binomial Model by Ying Chen, Zhongxiang Huang

“…Safety researchers have proposed various analytic methods to predict crashes. However, most of them require complete roadway inventory, traffic, and crash data. …”
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An Empirical Assessment of Factors Influencing Injury Severities of Motor Vehicle Crashes on National Highways of Pakistan by Hanif Ullah, Asim Farooq, Akhtar Ali Shah

“…Due to the high number of road traffic crashes and resulting fatalities, a random parameters logit model was estimated to determine the risk factors that influence the severity of injuries caused by motor vehicle crashes on national highways. …”
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Analysis of Freeway Secondary Crashes in Different Traffic Flow States by Three-Phase Traffic Theory by Bo Yang, Yao Wu, Weihua Zhang

“…The objective of this study is to analyse the relationship between secondary crash risk and traffic flow states and explore the contributing factors of secondary crashes in different traffic flow states. …”
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Investigation of Contributing Factors to Traffic Crashes and Violations: A Random Parameter Multinomial Logit Approach by Jaeyoung Lee, Xing Li, Suyi Mao, Wen Fu

“…The traffic violations are divided into four categories by seriousness (unintentional violation, minor violation, serious violation, and crash with violation). The results of the random parameter multinomial logit model indicate that various factors potentially affect the severity of traffic violations. …”
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