Vehicle maneuver evaluation in emergency condition

Q1 Engineering
Maryam Khodabakhshloo, Alireza Fatehi
{"title":"Vehicle maneuver evaluation in emergency condition","authors":"Maryam Khodabakhshloo,&nbsp;Alireza Fatehi","doi":"10.1016/j.treng.2024.100230","DOIUrl":null,"url":null,"abstract":"<div><p>Emergency vehicles getting stuck in traffic jams have always been a great concern in the cities. This would be more concern when the car is autonomous. So, evaluating the vehicle's maneuver in the presence of an emergency vehicle is required. This problem has been questioned in different ways. This paper attempts to deal with the performance of the vehicle in front of the emergency vehicle by considering the emergency vehicle's right-of-way. To evaluate the behavior of such a vehicle, we propose an algorithm that comprises three parts. In the first part, using a decision tree model, all feasible maneuvers that can be done by the front vehicle in the presence of an emergency vehicle are predicted. In the next part, the performed maneuver is detected using Hidden Markov Model. Finally, the best possible maneuver is compared with the performed maneuver. The proposed algorithm is implemented on a simulator, also developed in this research. The simulator generates different driving behaviors to train the models and evaluate the proposed algorithm.</p></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"16 ","pages":"Article 100230"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666691X24000058/pdfft?md5=da26799fb71401507abb14e48af150ce&pid=1-s2.0-S2666691X24000058-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666691X24000058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

Emergency vehicles getting stuck in traffic jams have always been a great concern in the cities. This would be more concern when the car is autonomous. So, evaluating the vehicle's maneuver in the presence of an emergency vehicle is required. This problem has been questioned in different ways. This paper attempts to deal with the performance of the vehicle in front of the emergency vehicle by considering the emergency vehicle's right-of-way. To evaluate the behavior of such a vehicle, we propose an algorithm that comprises three parts. In the first part, using a decision tree model, all feasible maneuvers that can be done by the front vehicle in the presence of an emergency vehicle are predicted. In the next part, the performed maneuver is detected using Hidden Markov Model. Finally, the best possible maneuver is compared with the performed maneuver. The proposed algorithm is implemented on a simulator, also developed in this research. The simulator generates different driving behaviors to train the models and evaluate the proposed algorithm.

紧急情况下的车辆机动评估
紧急救援车辆陷入交通堵塞一直是城市中的一大隐患。如果汽车是自动驾驶的,这种情况就会更加令人担忧。因此,需要评估车辆在紧急车辆出现时的机动性。这个问题一直受到不同的质疑。本文试图通过考虑紧急车辆的通行权来处理车辆在紧急车辆前的表现。为了评估这种车辆的行为,我们提出了一种由三部分组成的算法。第一部分,使用决策树模型,预测前方车辆在紧急车辆出现时可以采取的所有可行机动措施。在下一部分中,使用隐马尔可夫模型检测已执行的操作。最后,将最佳可行机动与已执行的机动进行比较。本研究还在一个模拟器上实施了所提出的算法。模拟器会生成不同的驾驶行为,用于训练模型和评估所提出的算法。
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
Transportation Engineering
Transportation Engineering Engineering-Automotive Engineering
CiteScore
8.10
自引率
0.00%
发文量
46
审稿时长
90 days
×
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