Modeling and analysis of influencing factors of primary accidents to secondary accidents based on structural equation model [0.03%]
基于结构方程模型的主要事故对次生事故影响因素的计量分析
Xiaoran Gong,Runze Liu,Jinjun Tang
Xiaoran Gong
Objectives: Secondary accidents generate a serious threat to road safety and traffic efficiency due to their compounded impact on congestion and emergency response. Due to the higher risks and difficulty for prevention of...
Relationship between occupant compartment intrusion and injury by crash counterpart relevant to MASH requirements [0.03%]
与MASH要求相关的乘员舱侵入及碰撞对伤者伤害的关系研究
Garrett Mattos,Tim Kenney,Keith Friedman et al.
Garrett Mattos et al.
Objective: This study used recent crash data to quantify the correlation between MASH intrusion limits and injury outcomes for crashes with roadside hardware, vehicles, or fixed objects. The study also provides additional...
Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision [0.03%]
基于风险规则过滤的LSTM-Duelling DQN自主车道变换决策方法
Zhicai Chen,Kai Zhu
Zhicai Chen
Objective: Autonomous vehicle lane-change decision making has long been a prominent research topic in intelligent transportation systems. To enhance both the safety and efficiency of lane changes in dynamic traffic enviro...
Evaluation of the redesigned "Booze It & Lose It" campaign in North Carolina [0.03%]
北卡罗来纳州“酒驾人财两失”运动改进效果评价
Charles M Farmer,Angela H Eichelberger,Mark M Ezzell et al.
Charles M Farmer et al.
Objective: In 2023, the North Carolina Governor's Highway Safety Program and the Insurance Institute for Highway Safety joined with local law enforcement and other partners to update the "Booze It & Lose It" campaign thro...
Sam D Doecke,Matthew R J Baldock
Sam D Doecke
Objective: To assess the degree to which speed limits are being set in accordance with the Safe System, with fatal crash rates remaining negligible regardless of speed limit. A further objective was to examine the reducti...
A machine learning model to predict the severity of road traffic injury based on aberrant driving behaviors and driver characteristics [0.03%]
基于异常驾驶行为和驾驶员特征的交通事故伤情严重程度预测模型研究
Alireza Abdolrazaghi,Shima Zarabadi Pour
Alireza Abdolrazaghi
Objectives: Road traffic injuries remain a leading cause of mortality and disability worldwide, especially in low- and middle-income countries. This study aimed to develop and validate a machine-learning model to predict ...
Identifying the contributory chains and patterns of road facilities in bus-involved crashes using latent class clustering and association rules [0.03%]
基于潜在类别聚类和关联规则的公交肇事链及模式识别研究
Chunting Nie,Shunchao Wang,Qinghai Lin
Chunting Nie
Objective: This study aims to investigate the heterogeneity in bus-involved crashes by identifying association rules and contributory patterns of road facilities across different crash types and severities. The goal is to...
A finite element study on the effect of initial head-neck posture on neck injury risk in frontal collisions [0.03%]
初始头颈姿势对正面碰撞中颈部受伤风险影响的有限元法研究
Zhixin Liu,Xiao-Yang Zhang,Weidong Liu et al.
Zhixin Liu et al.
Objective: Neck injuries represent a predominant category of injuries in automotive collisions. Non-neutral head-neck postures are believed to increase the risk of neck injury during rear impact scenarios. However, quanti...
Community norms and transportation safety behaviors among caregivers of children 6 months to 10 years old in chicago [0.03%]
芝加哥6个月至10岁儿童监护人的社区规范与交通行为安全研究
Mario M Landa,Bethany Pollock,Leopoldo Castillo et al.
Mario M Landa et al.
Objective: Motor vehicle collisions are a leading cause of death for children. Risks of driver speeding, distraction, and impairment and protective benefits of following child passenger safety guidelines are well establis...
Driving under the influence of drugs: perceptions and attitudes of Chinese professional drivers [0.03%]
关于中国职业司机吸毒后驾驶的相关态度及认知状况调查报告
Jia Wang,Shizhe Jia,Jun Li et al.
Jia Wang et al.
Objectives: This study explored the status and causative factors of drug driving behavior among professional drivers in China, by examining their perceptions of impairment caused by legal and illegal drugs, attitudes towa...