Random forest models for motorcycle accident prediction using naturalistic driving based big data.

IF 2.3 4区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Injury Control and Safety Promotion Pub Date : 2023-06-01 DOI:10.1080/17457300.2022.2164310
Fatma Outay, Muhammad Adnan, Uneb Gazder, Syed Fazal Abbas Baqueri, Hammad Hussain Awan
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引用次数: 2

Abstract

Motorcycle accident studies usually rely upon data collected from road accidents collected through questionnaire surveys/police reports including characteristics of motorcycle riders and contextual data such as road environment. The present study utilizes big data, in the form of vehicle trajectory patterns collected through GPS, coupled with self-reported road accident information along with motorcycle rider characteristics to predict the likelihood of involvement of a motorcyclist in an accident. Random Forest-based machine learning algorithm is employed by taking inputs based on a variety of features derived from trajectory data. These features are mobility-based features, acceleration event-based features, aggressive overtaking event-based features and motorcyclists socio-economic features. Additionally, the relative importance of features is also determined which shows that aggressive overtaking event-based features have more impact on motorcycle accidents as compared to other categories of features. The developed model is useful in identifying risky motorcyclists and implementing safety measures focused towards them.

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基于自然驾驶大数据的摩托车事故预测随机森林模型。
摩托车事故研究通常依赖于通过问卷调查/警方报告收集的道路事故数据,包括摩托车骑手的特征和道路环境等背景数据。本研究利用通过GPS收集的车辆轨迹模式形式的大数据,结合自我报告的道路事故信息以及摩托车骑行者的特征,来预测摩托车骑行者卷入事故的可能性。采用基于随机森林的机器学习算法,根据轨迹数据的各种特征进行输入。这些特征是基于机动性的特征、基于加速事件的特征、基于激进超车事件的特征和摩托车手的社会经济特征。此外,特征的相对重要性也被确定,这表明与其他类别的特征相比,基于侵略性超车事件的特征对摩托车事故的影响更大。开发的模型有助于识别危险的摩托车手并实施针对他们的安全措施。
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来源期刊
International Journal of Injury Control and Safety Promotion
International Journal of Injury Control and Safety Promotion PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
4.40
自引率
13.00%
发文量
48
期刊介绍: International Journal of Injury Control and Safety Promotion (formerly Injury Control and Safety Promotion) publishes articles concerning all phases of injury control, including prevention, acute care and rehabilitation. Specifically, this journal will publish articles that for each type of injury: •describe the problem •analyse the causes and risk factors •discuss the design and evaluation of solutions •describe the implementation of effective programs and policies The journal encompasses all causes of fatal and non-fatal injury, including injuries related to: •transport •school and work •home and leisure activities •sport •violence and assault
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