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Statistical Analysis of the Occurrence and Severity of Crashes Involving Vulnerable Road Users

机译:道路弱势人群撞车事故发生和严重程度的统计分析

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Cities have been often organized in terms of planning with special attention to motor vehicles and not well prepared for pedestrians and cyclists. In order to privilege active modes, there is the need to ensure the safety of these vulnerable road users. The main objective of this paper is to implement a statistical analysis to assess the occurrence and severity of road crashes involving vulnerable road users. This research is focused on analyzing the trends and causes of road crashes involving cyclists and pedestrians and what are the main difficulties that people using active modes do face in their journeys. In order to reach this objective, a database of crashes registrations involving motor vehicles and vulnerable road users from Aveiro, Portugal, between 2012 and 2015 was created. This analysis intends to evaluate the evolution of the number of crashes and to create patterns of risk factors such as weather conditions, specific locations and singularities that might represent additional risk, profile of pedestrian or cyclist involved. Regarding the analyzed variables that characterize crashes participations, the dependent variables considered were: meteorological conditions, location, proximity to a pedestrians’ crosswalk and gender of the VRU. The probability of the vulnerable road user being a pedestrian increases by 2.7 times if the crash occurs on a urban street segment, 10.6 times if the crash occurs at a pedestrians’ crosswalk, and 3.5 times if the VRU is a female.
机译:城市通常是在规划方面进行组织的,尤其要注意机动车辆,而对行人和骑自行车的人却没有做好充分的准备。为了赋予活动模式特权,需要确保这些易受伤害的道路使用者的安全。本文的主要目的是进行统计分析,以评估涉及弱势道路使用者的道路撞车事故的发生和严重程度。这项研究的重点是分析涉及骑自行车者和行人的道路交通事故的趋势和原因,以及使用主动模式的人在旅途中面临的主要困难是什么。为了实现这一目标,创建了2012年至2015年之间涉及葡萄牙阿威罗的机动车和弱势道路使用者的撞车登记数据库。该分析旨在评估事故数量的演变,并创建风险因素的模式,例如天气状况,特定位置和奇异之处,这些风险因素可能代表额外的风险,所涉行人或骑自行车的人的概况。关于表征碰撞事故的分析变量,考虑的因变量是:气象条件,位置,与行人的人行横道的接近程度以及VRU的性别。如果在城市街道上发生撞车事故,易受伤害的道路使用者成为行人的概率增加2.7倍;如果在行人的人行横道发生撞车事故,则脆弱的道路用户的事故概率增加20.6倍;如果VRU是女性,则增加3.5倍。

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