利用分布式模拟研究驾驶员与行人之间的互动和运动学线索:对自动驾驶汽车行为和通信的影响

IF 3.5 2区 工程技术 Q1 PSYCHOLOGY, APPLIED
Yue Yang , Yee Mun Lee , Amir Hossein Kalantari , Jorge Garcia de Pedro , Anthony Horrobin , Michael Daly , Albert Solernou , Christopher Holmes , Gustav Markkula , Natasha Merat
{"title":"利用分布式模拟研究驾驶员与行人之间的互动和运动学线索:对自动驾驶汽车行为和通信的影响","authors":"Yue Yang ,&nbsp;Yee Mun Lee ,&nbsp;Amir Hossein Kalantari ,&nbsp;Jorge Garcia de Pedro ,&nbsp;Anthony Horrobin ,&nbsp;Michael Daly ,&nbsp;Albert Solernou ,&nbsp;Christopher Holmes ,&nbsp;Gustav Markkula ,&nbsp;Natasha Merat","doi":"10.1016/j.trf.2024.08.027","DOIUrl":null,"url":null,"abstract":"<div><p>As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers’ control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians’ crossing decisions were also analysed. We found that the distribution of drivers’ average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 84-97"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1369847824002341/pdfft?md5=3556bd963730d2fe523bb74942ee37d1&pid=1-s2.0-S1369847824002341-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Using distributed simulations to investigate driver-pedestrian interactions and kinematic cues: Implications for automated vehicle behaviour and communication\",\"authors\":\"Yue Yang ,&nbsp;Yee Mun Lee ,&nbsp;Amir Hossein Kalantari ,&nbsp;Jorge Garcia de Pedro ,&nbsp;Anthony Horrobin ,&nbsp;Michael Daly ,&nbsp;Albert Solernou ,&nbsp;Christopher Holmes ,&nbsp;Gustav Markkula ,&nbsp;Natasha Merat\",\"doi\":\"10.1016/j.trf.2024.08.027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers’ control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians’ crossing decisions were also analysed. We found that the distribution of drivers’ average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs.</p></div>\",\"PeriodicalId\":48355,\"journal\":{\"name\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"volume\":\"107 \",\"pages\":\"Pages 84-97\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1369847824002341/pdfft?md5=3556bd963730d2fe523bb74942ee37d1&pid=1-s2.0-S1369847824002341-main.pdf\",\"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/S1369847824002341\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part F-Traffic Psychology and Behaviour","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369847824002341","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

摘要

随着未来自动驾驶汽车(AV)融入当前的交通系统,了解驾驶员与行人之间的互动至关重要,以便加强自动驾驶汽车的设计和优化。以前在这一领域的研究主要采用自然观察或单人虚拟现实模拟,但由于缺乏真实的人与人之间的互动,无法得出因果结论,因而受到限制。我们的研究采用了高保真分布式模拟装置,将运动模拟器中的驾驶员与 CAVE 环境中的行人联系起来,从而解决了这些局限性。通过这种方法,可以在一系列过马路场景中检查实时和相互的互动。我们使用了 32 对驾驶员和行人,研究了斑马线的存在和接近车辆的不同时间间隙等不同因素对驾驶员行为和行人过马路决策的影响。此外,我们还分析了司机在过马路时对车辆的控制(如刹车行为和横向偏离)对行人过马路决策的影响。我们发现,驾驶员的平均减速值呈双峰分布,驾驶员要么明显礼让行人,要么继续沿着行人的路线行驶,中间行为的情况很少。我们还发现,行人的决定似乎受到了驾驶员所采取的不同制动策略的影响,在软制动和早制动或晚制动和硬制动的情况下,行人会先于车辆通过,而晚制动和软制动则往往导致车辆先行通过。我们还观察到,当驾驶员不礼让行人时,车辆会略微横向偏离行人,但当礼让行人时,车辆会更多地横向偏向行人。这可能是因为驾驶员会下意识地将步行时的互动习惯转移到驾驶行为中,以避免与行人发生碰撞。最后,我们的研究结果表明,与斑马线相比,这些运动学线索对行人过马路决策的影响更大。这项研究不仅强调了研究车辆与行人互动的新方法的价值,还说明了车辆线索如何帮助行人做出决定,为未来的自动驾驶汽车开发类人行为提供了新的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using distributed simulations to investigate driver-pedestrian interactions and kinematic cues: Implications for automated vehicle behaviour and communication

As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers’ control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians’ crossing decisions were also analysed. We found that the distribution of drivers’ average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信