The right turn: Modeling driver yielding behavior to e-scooter riders

IF 4.4 2区 工程技术 Q1 PSYCHOLOGY, APPLIED
Alexander Rasch , Alberto Morando , Prateek Thalya
{"title":"The right turn: Modeling driver yielding behavior to e-scooter riders","authors":"Alexander Rasch ,&nbsp;Alberto Morando ,&nbsp;Prateek Thalya","doi":"10.1016/j.trf.2025.103353","DOIUrl":null,"url":null,"abstract":"<div><div>Electric scooters (e-scooters) are a relatively new and popular means of personal transportation in many cities. Notably, they have been involved in crashes with other road users. Crashes with motorized vehicles are particularly critical since they result in more severe injuries or even fatalities. While previous work has highlighted the consequences of failed interactions, we know little about drivers’ interactions with e-scooters and how to improve them. In this paper, we conducted a test-track experiment to study how drivers negotiate a right turn at an intersection with an e-scooter. Using Bayesian regression, we modeled whether drivers yield to the e-scooter according to their approaching speed and the difference in time-to-arrival, and we were able to predict drivers’ intentions with an AUC of 0.94 and an accuracy of 0.82 in cross-validation. The model coefficients indicate that drivers yield less often when approaching the intersection at a higher speed or larger projected gap. We further modeled drivers’ braking timing (time-to-arrival) and strength (mean deceleration), yielding RMSEs of 1.42 s and 0.33 m/s<sup>2</sup>, respectively. As a reference for driver behavior when interacting with an e-scooter rider, the model can inform the development and evaluation of support systems to warn drivers more effectively.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"115 ","pages":"Article 103353"},"PeriodicalIF":4.4000,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part F-Traffic Psychology and Behaviour","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369847825003080","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

Electric scooters (e-scooters) are a relatively new and popular means of personal transportation in many cities. Notably, they have been involved in crashes with other road users. Crashes with motorized vehicles are particularly critical since they result in more severe injuries or even fatalities. While previous work has highlighted the consequences of failed interactions, we know little about drivers’ interactions with e-scooters and how to improve them. In this paper, we conducted a test-track experiment to study how drivers negotiate a right turn at an intersection with an e-scooter. Using Bayesian regression, we modeled whether drivers yield to the e-scooter according to their approaching speed and the difference in time-to-arrival, and we were able to predict drivers’ intentions with an AUC of 0.94 and an accuracy of 0.82 in cross-validation. The model coefficients indicate that drivers yield less often when approaching the intersection at a higher speed or larger projected gap. We further modeled drivers’ braking timing (time-to-arrival) and strength (mean deceleration), yielding RMSEs of 1.42 s and 0.33 m/s2, respectively. As a reference for driver behavior when interacting with an e-scooter rider, the model can inform the development and evaluation of support systems to warn drivers more effectively.
右转:模拟驾驶员对电动滑板车骑手的屈服行为
在许多城市,电动滑板车(e-scooters)是一种相对较新的流行的个人交通工具。值得注意的是,他们曾与其他道路使用者发生过车祸。机动车辆的碰撞尤其严重,因为它们会造成更严重的伤害甚至死亡。虽然之前的工作强调了失败互动的后果,但我们对司机与电动滑板车的互动以及如何改善它们知之甚少。在本文中,我们进行了一个测试轨道实验来研究驾驶员如何在十字路口与电动滑板车协商右转。利用贝叶斯回归,我们根据司机的接近速度和到达时间的差异,建立了司机是否屈服于电动滑板车的模型,我们能够预测司机的意图,交叉验证的AUC为0.94,准确率为0.82。模型系数表明,驾驶员以较高的速度或较大的预计间距接近十字路口时,退让的次数较少。我们进一步对驾驶员的制动时间(到达时间)和强度(平均减速)进行建模,得出rmse分别为1.42 s和0.33 m/s2。该模型可作为驾驶员与电动滑板车驾驶员互动时的行为参考,为支持系统的开发和评估提供信息,从而更有效地警告驾驶员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.60
自引率
14.60%
发文量
239
审稿时长
71 days
期刊介绍: Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信