Riding safety Evaluation of food delivery motor scooters based on Associating Sensor-based riding behavior and road traffic characteristics

IF 5.7 1区工程技术 Q1 ERGONOMICS

Accident; analysis and prevention Pub Date : 2024-12-07 DOI:10.1016/j.aap.2024.107871

Yeseo Gu , Eunsol Cho , Cheol Oh , Gunwoo Lee

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引用次数: 0

Abstract

The safety of motor scooters used to deliver food has come under scrutiny due to the growing popularity of food delivery services in Republic of Korea. Policymakers have been tasked with investigating and identifying the factors associated with scooter safety to prevent accidents and develop mitigating strategies. A comprehensive analysis of the components of road traffic influencing the safety of motor scooters has received little attention to date. This study aims to identify the road- and traffic-related factors that affect the safety of such vehicles through GIS-based geographically weighted regression (GWR) analysis. First, it assesses safety by analyzing the riding characteristics of delivery scooters using naturalistic study data, including speed, acceleration, and direction. Second, it evaluates safety through the hazardous riding behavior rate, offering a proactive measure for preventing accidents. Third, it uses GWR analysis to examine safety factors at the scale of the individual road segments (referred to as ’links’), identifying hazardous road segments and proposing customized measures. The results show that number of lanes, signal density, speed limit, and average speed on road segments are key factors influencing motor scooter safety. A thorough interpretation of the geographical regression coefficients for the two most hazardous links suggests useful policy implications. Notably, the effects of speed limits and riding speeds on safety vary by link. We propose effective speed-management strategies by analyzing the relationship between speed limit and the average speed of delivery motor scooters. Our research provides valuable insights on how to improve the safety of delivery motor scooters.

查看原文本刊更多论文

基于关联传感器骑行行为和道路交通特征的送餐摩托车骑行安全性评价。

随着外卖服务在国内的普及，外卖摩托车的安全性受到了关注。政策制定者的任务是调查和确定与滑板车安全相关的因素，以防止事故发生并制定缓解策略。对影响摩托车安全的道路交通因素的综合分析迄今为止很少受到关注。本研究旨在通过基于gis的地理加权回归（GWR）分析，识别影响此类车辆安全的道路和交通相关因素。首先，它通过使用自然研究数据（包括速度、加速度和方向）分析送货滑板车的骑行特性来评估安全性。第二，通过危险骑行行为率对安全性进行评价，为预防事故的发生提供主动措施。第三，它使用GWR分析来检查单个路段（称为“链接”）的安全因素，识别危险路段并提出定制措施。结果表明，车道数、信号密度、限速和路段平均速度是影响摩托车安全的关键因素。对这两个最危险环节的地理回归系数进行彻底的解释，可以提供有益的政策启示。值得注意的是，速度限制和骑行速度对安全的影响因路段而异。通过分析配送摩托车限速与平均速度的关系，提出了有效的速度管理策略。我们的研究为如何提高送货摩托车的安全性提供了有价值的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accident; analysis and prevention Multiple-

CiteScore

11.90

自引率

16.90%

发文量

264

审稿时长

48 days

期刊介绍： Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.