Department of Business Strategy and Innovation, Griffith University, Australia.
School of Computing and Information Technology, University of Wollongong, Australia.
Accid Anal Prev. 2024 Nov;207:107742. doi: 10.1016/j.aap.2024.107742. Epub 2024 Aug 12.
As vulnerable road users, pedestrians and cyclists are facing a growing number of injuries and fatalities, which has raised increasing safety concerns globally. Based on the crash records collected in the Australian Capital Territory (ACT) in Australia from 2012 to 2021, this research firstly establishes an extended crash dataset by integrating road network features, land use features, and other features. With the extended dataset, we further explore pedestrian and cyclist crashes at macro- and micro-levels. At the macro-level, random parameters negative binomial (RPNB) model is applied to evaluate the effects of Suburbs and Localities Zones (SLZs) based variables on the frequency of pedestrian and cyclist crashes. At the micro-level, binary logit model is adopted to evaluate the effects of event-based variables on the severity of pedestrian and cyclist crashes. The research findings show that multiple factors are associated with high frequency of pedestrian total crashes and fatal/injury crashes, including high population density, high percentage of urban arterial road, low on-road cycleway density, high number of traffic signals and high number of schools. Meanwhile, many factors have positive relations with high frequency of cyclist total crashes and fatal/injury crashes, including high population density, high percentage of residents cycling to work, high median household income, high percentage of households with no motor vehicle, high percentage of urban arterial road and rural road, high number of bus stops and high number of schools. Additionally, it is found that more severe pedestrian crashes occur: (i) at non-signal intersections, (ii) in suburb areas, (iii) in early morning, and (iv) on weekdays. More severe cyclist crashes are observed when the crash type is overturned or struck object/pedestrian/animal; when more than one cyclist is involved; and when crash occurs at park/green space/nature reserve areas.
作为弱势道路使用者，行人和骑自行车的人面临着越来越多的伤害和死亡，这在全球范围内引起了越来越多的安全关注。本研究基于 2012 年至 2021 年在澳大利亚澳大利亚首都领地（ACT）收集的碰撞记录，首先通过整合道路网络特征、土地利用特征和其他特征来建立扩展的碰撞数据集。利用扩展数据集，我们进一步从宏观和微观层面探讨行人和骑自行车的人碰撞事故。在宏观层面，采用随机参数负二项（RPNB）模型评估郊区和地方行政区（SLZ）基于变量对行人与骑自行车者碰撞频率的影响。在微观层面，采用二元对数模型评估基于事件的变量对行人与骑自行车者碰撞严重程度的影响。研究结果表明，多个因素与行人总碰撞和致命/受伤碰撞的高频率有关，包括人口密度高、城市干道比例高、道路上自行车道密度低、交通信号数量多和学校数量多。同时，许多因素与自行车总碰撞和致命/受伤碰撞的高频率呈正相关，包括人口密度高、骑自行车上班的居民比例高、家庭中位数收入高、无机动车的家庭比例高、城市干道和农村道路比例高、公共汽车站数量多和学校数量多。此外，研究还发现，行人碰撞事故更严重：（i）在无信号交叉口，（ii）在郊区，（iii）在清晨，（iv）在工作日。当碰撞类型为翻车或撞击物体/行人/动物、涉及多名骑自行车者以及在公园/绿地/自然保护区发生碰撞时，更严重的自行车碰撞事故。
