Safety-centred analysis of transition stages to traffic with fully autonomous vehicles

E. Andreotti, Pinar Boyraz Baykas, Selpi Selpi
{"title":"Safety-centred analysis of transition stages to traffic with fully autonomous vehicles","authors":"E. Andreotti, Pinar Boyraz Baykas, Selpi Selpi","doi":"10.1109/ITSC45102.2020.9294644","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to highlight and investigate the effects of increasing presence rate of autonomous vehicles (AVs) in terms of traffic safety and traffic flow characteristics. For this purpose, using existing driver models in traffic simulator SUMO we identify and analyze those parameters that characterize and distinguish AVs’ driving from manual driving in a heterogeneous traffic context. While it is essential to identify the parameters for traffic flow characteristics of heterogeneous fleets compared to homogeneous ones comprising manually driven vehicles (MV) only (i.e. current status), the safety aspects must be also accounted for. In order to combine these two fundamental aspects of heterogeneous traffic, we used a complete description of a highway driving scenario. The scenario integrates the perceptions of different type of vehicles (i.e. AV and MV) involved and the reaction times of human drivers and decision-making units of autonomous vehicles, to explore the impact of both the rate of AV presence and the perturbation in perception capabilities in highway scenarios.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC45102.2020.9294644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

The aim of this paper is to highlight and investigate the effects of increasing presence rate of autonomous vehicles (AVs) in terms of traffic safety and traffic flow characteristics. For this purpose, using existing driver models in traffic simulator SUMO we identify and analyze those parameters that characterize and distinguish AVs’ driving from manual driving in a heterogeneous traffic context. While it is essential to identify the parameters for traffic flow characteristics of heterogeneous fleets compared to homogeneous ones comprising manually driven vehicles (MV) only (i.e. current status), the safety aspects must be also accounted for. In order to combine these two fundamental aspects of heterogeneous traffic, we used a complete description of a highway driving scenario. The scenario integrates the perceptions of different type of vehicles (i.e. AV and MV) involved and the reaction times of human drivers and decision-making units of autonomous vehicles, to explore the impact of both the rate of AV presence and the perturbation in perception capabilities in highway scenarios.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
以安全为中心的全自动驾驶交通过渡阶段分析
本文的目的是强调和研究自动驾驶汽车(AVs)的存在率在交通安全和交通流特征方面的影响。为此,我们利用交通模拟器SUMO中现有的驾驶员模型,识别并分析了在异构交通环境下表征和区分自动驾驶与人工驾驶的参数。虽然与仅由手动驾驶车辆(MV)组成的同质车队(即当前状态)相比,确定异质车队的交通流特征参数至关重要,但安全方面也必须考虑在内。为了将异构交通的这两个基本方面结合起来,我们使用了对高速公路驾驶场景的完整描述。该场景整合了不同类型车辆(即自动驾驶汽车和自动驾驶汽车)的感知,以及人类驾驶员和自动驾驶汽车决策单元的反应时间,以探索自动驾驶汽车存在率和感知能力扰动对高速公路场景的影响。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
CR-TMS: Connected Vehicles enabled Road Traffic Congestion Mitigation System using Virtual Road Capacity Inflation A novel concept for validation of pre-crash perception sensor information using contact sensor Space-time Map based Path Planning Scheme in Large-scale Intelligent Warehouse System Weakly-supervised Road Condition Classification Using Automatically Generated Labels Studying the Impact of Public Transport on Disaster Evacuation
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1