Railway drivers' physiological responses to typical hazardous scenarios: differences between professional drivers and student drivers [0.03%]
职业驾驶员与学生驾驶员在典型危险场景下的生理反应差异
Zizheng Guo,Junjie Tang,Mingrui Li et al.
Zizheng Guo et al.
Unexpected object intrusions on railways present significant safety hazards that can lead to accidents, injuries, and operational disruptions. Railway drivers serve as the critical final line of defense in accident prevention, it is very ne...
Study on a multi-factor lane-changing risk resilience assessment model based on genetic algorithm and fault tree analysis [0.03%]
基于遗传算法和故障树分析的多因素车道变更鲁棒风险评估模型研究
Qiang Luo,Haihui Wang,Junheng Yang et al.
Qiang Luo et al.
Current lane-change risk assessment models often lack dynamic adaptation to adverse weather and validation against real-world outcomes. To bridge this gap, this study re-frames the problem through a resilience engineering lens, defining ris...
GeoShapley-based interpretation of older adult pedestrian fatal vs injury crash frequency in dense urban environments [0.03%]
基于GeoShapley的大城市密集环境中老年行人致命事故与伤害事故频率的解释
I Gede Brawiswa Putra,Pei-Fen Kuo,Febrian Fitryanik Susanta et al.
I Gede Brawiswa Putra et al.
As the world's population ages, ensuring the safety of older adult pedestrians has become an urgent priority in transportation planning. However, most existing studies rely on global models that overlook spatial heterogeneity and fail to ca...
Modeling crash frequencies at highway-railroad grade crossings in Kentucky in the United States [0.03%]
美国肯塔基州铁路平交道口交通事故分布模型研究
Arunabha Banerjee,Kirolos Haleem
Arunabha Banerjee
Previous safety studies at highway-railroad grade crossings (HRGCs) have typically examined crash severities. However, there remains a notable gap in studies that developed safety performance functions (SPFs) (or crash frequency models) at ...
CoDEA: A framework for extraction and augmentation of cooperative lane-changing scenarios from naturalistic driving data [0.03%]
基于自然驾驶数据的协作变道场景提取与增强框架
Ye Li,Weiran Li,Rui Zhou et al.
Ye Li et al.
As modern transportation systems face increasing complexity, with challenges such as increased vehicle volumes, limited road resources, and rising safety concerns, there is an urgent need for innovative solutions. Cooperative driving, which...
The myth of quick conflict-based road safety analysis: Limits of short-term conflict data in collision risk prediction [0.03%]
基于冲突的快速道路安全分析的误区：短期冲突数据在碰撞风险预测中的局限性
Reza Aminghafouri,Liping Fu
Reza Aminghafouri
Traditional road safety analysis is reactive and often hindered by scarce collision data. Traffic conflicts, or near-misses, offer a proactive surrogate for safety assessment, using Extreme Value Theory to extrapolate collision risk from th...
Evaluating the impact of vehicle automation on the safety of highway design: A 3D risk assessment approach using reliability theory [0.03%]
基于可靠性理论的三维风险评估方法评价车辆自动化对高速公路安全的影响
Youjia Liu,Suliman Gargoum,Tarek Sayed
Youjia Liu
Empirical quantification of how automation affects road safety, particularly whether current highway designs can accommodate autonomous vehicles (AV), remains under-researched. This study addresses the gap using a 3D risk assessment framewo...
Driver behavior analysis at alternative intersection corridors through driving simulator [0.03%]
利用驾驶模拟器分析替代性交叉路口范围内的驾驶员行为特征
Guangchuan Yang,R Thomas Chase,Yunmei Liu et al.
Guangchuan Yang et al.
Alternative intersection (AI) designs, such as the Median U-Turn (MUT), Reduced Conflict Intersection (RCI), Continuous Flow Intersection (CFI), and Quadrant Roadway Intersection (QRI), introduce innovative geometric and control features co...
Speeding across Texas: identifying high-risk locations using probe data [0.03%]
使用探测数据识别高风险位置：得克萨斯州的超速行为
Keya Li,Kara M Kockelman
Keya Li
Speeding contributes to one-third of all motor vehicle fatalities in the U.S., making it crucial to understand speeding behaviors for traffic safety. This work compares a random sample of 39.1 million vehicle speeds in November 2024 to post...
Modeling interactive car-following behaviors of automated and human-driven vehicles in safety-critical events: a multi-agent state-space attention-enhanced framework [0.03%]
基于多智能体状态空间注意力增强框架的自动驾驶与人工驾驶车辆在安全临界事件下的互动跟随行为模拟研究
Qingwen Pu,Kun Xie,Hongyu Guo
Qingwen Pu
As automated vehicles (AVs) become increasingly prevalent in mixed-traffic environments, it is essential to understand how they interact with human-driven vehicles (HDVs), especially in safety-critical situations. Existing research has prim...