Impact of urban form and street infrastructure on pedestrian-motorist collisions [0.03%]
城市形态和街道基础设施对人车碰撞的影响
Taylor Foreman,Meimei Lin,Wei Tu et al.
Taylor Foreman et al.
This study examines the impact of urban form and street infrastructure on pedestrian safety in Atlanta, Georgia, and Boston, Massachusetts. With a significant rise in pedestrian fatalities over the past decade, understanding how cities' bui...
Bivariate ordered probit modelling of motorcycle riders and pillion passengers' injury severities relationship and associated risk factors [0.03%]
摩托车骑手和后座乘客的伤情严重程度及其相关危险因素的二元有序概率模型分析
Mohammed A Yakubu,Eric N Aidoo,Richard T Ampofo et al.
Mohammed A Yakubu et al.
This study simultaneously modelled the injury severity of motorcycle riders and their pillion passengers and determine the associated risk factors. The analysis is based on motorcycle crashes data in Ashanti region of Ghana spanning from 20...
Factors affecting the intention to wear helmets for e-bike riders: the case of Chinese college students [0.03%]
影响电动自行车骑行者佩戴头盔意愿的因素——以中国大学生为例
Ying Yang,Chun Li,Kun Cheng et al.
Ying Yang et al.
As the popularity of electric bicycles (e-bikes) continues to surge, the number of accidents involving them has commensurately increased. A significant factor contributing to the high fatality rate in these accidents is the low usage of hel...
A comparative analysis of risk factors in taxi-related crashes using XGBoost and SHAP [0.03%]
基于XGBoost和SHAP的出租车相关事故风险因素对比分析
Zhipeng Peng,Jingping Zuo,Hao Ji et al.
Zhipeng Peng et al.
Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted...
Hazardous traffic scenarios for motorcyclists in Indonesia: a comprehensive insight from police accident data and self-reports [0.03%]
印度尼西亚摩托车手的危险交通场景：来自警方事故数据和自报数据的全面见解
Naomi Srie Kusumastutie,Bhina Patria,Sri Kusrohmaniah et al.
Naomi Srie Kusumastutie et al.
Motorcycle safety remains a concern in low- and middle-income countries. This study addresses this issue by identifying hazardous scenarios for motorcyclists in Indonesia. We conducted a two-step cluster analysis and injury analysis to exam...
Evaluating the crash risk of powered two-wheelers in urban mixed traffic environments: a conflict threshold perspective [0.03%]
城市混合交通环境条件下机动车与电动二轮车冲突及碰撞风险评估
Shivasai Samalla,Pranab Kar,Mallikarjuna Chunchu
Shivasai Samalla
The study investigates the crash risk of powered two-wheelers (PTWs) involved in multiple conflict types, with different vehicle classes constituting a mixed traffic stream. This study uses the extreme value theory to estimate the crash ris...
Analysis of the elderly pedestrian traffic accidents in urban scenarios: the case of the Spanish municipalities [0.03%]
基于西班牙城市案例的老年人行人交通事故分析
Daniel Gálvez-Pérez,Begoña Guirao,Armando Ortuño
Daniel Gálvez-Pérez
As the elderly population grows, there is a greater concern for their safety on the roads. This is particularly important for elderly pedestrians who are more vulnerable to accidents. In Spain, one of the most aged countries in the world, t...
The prevalence of helmet use in motorcyclists around the world: a systematic review and meta-analysis of 5,006,476 participants [0.03%]
全球摩托车驾驶员安全头盔使用率的系统评价和荟萃分析（5,006,476名参与者）
Sina Shool,Seyed Mohammad Piri,Zahra Ghodsi et al.
Sina Shool et al.
Road traffic injuries present a significant public health burden, especially in developing countries. This systematic review and meta-analysis synthesized global evidence on motorcycle helmet use prevalence by including 299 records across 2...
Pedestrians injuries in the north east region of Jamaica: a cross sectional study [0.03%]
牙买加东北部行人受伤情况：一项横断面研究
Cary Fletcher,Kaye Lambert Fletcher
Cary Fletcher
To describe the sociodemographic data of injured pedestrians, temporal patterns of injury, injury patterns, and the independent predictors of hospital admission. A two year cross-sectional study was conducted at the Saint Ann's Bay Regional...
Identification of the best machine learning model for the prediction of driver injury severity [0.03%]
用于预测驾驶员损伤严重程度的最优机器学习模型识别
Neero Gumsar Sorum,Dibyendu Pal
Neero Gumsar Sorum
Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key topic of research in road traffic safety. The current study analyzed the driver injury severity (DIS) using twelve machine learning (ML) algori...