意图感知运动规划与道路规则

J. Karlsson, Jana Tumova
{"title":"意图感知运动规划与道路规则","authors":"J. Karlsson, Jana Tumova","doi":"10.1109/CASE48305.2020.9217037","DOIUrl":null,"url":null,"abstract":"We present an approach for intention-aware motion planning in an autonomous driving scenario, where a vehicle aims to traverse a road segment as quickly as possible, while constrained by road rules encoded in syntactically co-safe linear temporal logic. We show that by combining the RRTx algorithm with trajectory prediction using Mixed Observable Markov Decision Processes (MOMDP), we can achieve least-violating behavior wrt. mission completion time and the road rules, while ensuring that the likelihood of collisions remains below a user specified threshold. We illustrate the validity of our approach using simulations of a variety of traffic scenarios.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intention-aware motion planning with road rules\",\"authors\":\"J. Karlsson, Jana Tumova\",\"doi\":\"10.1109/CASE48305.2020.9217037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an approach for intention-aware motion planning in an autonomous driving scenario, where a vehicle aims to traverse a road segment as quickly as possible, while constrained by road rules encoded in syntactically co-safe linear temporal logic. We show that by combining the RRTx algorithm with trajectory prediction using Mixed Observable Markov Decision Processes (MOMDP), we can achieve least-violating behavior wrt. mission completion time and the road rules, while ensuring that the likelihood of collisions remains below a user specified threshold. We illustrate the validity of our approach using simulations of a variety of traffic scenarios.\",\"PeriodicalId\":212181,\"journal\":{\"name\":\"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE48305.2020.9217037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE48305.2020.9217037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

我们提出了一种在自动驾驶场景中进行意图感知运动规划的方法,在自动驾驶场景中,车辆的目标是尽可能快地穿越一段道路,同时受到以句法共安全线性时间逻辑编码的道路规则的约束。通过将RRTx算法与使用混合可观察马尔可夫决策过程(MOMDP)的轨迹预测相结合,我们可以实现最小违反行为wrt。任务完成时间和道路规则,同时确保碰撞的可能性保持在用户指定的阈值以下。我们通过各种交通场景的模拟来说明我们方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intention-aware motion planning with road rules
We present an approach for intention-aware motion planning in an autonomous driving scenario, where a vehicle aims to traverse a road segment as quickly as possible, while constrained by road rules encoded in syntactically co-safe linear temporal logic. We show that by combining the RRTx algorithm with trajectory prediction using Mixed Observable Markov Decision Processes (MOMDP), we can achieve least-violating behavior wrt. mission completion time and the road rules, while ensuring that the likelihood of collisions remains below a user specified threshold. We illustrate the validity of our approach using simulations of a variety of traffic scenarios.
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
自引率
0.00%
发文量
0
×
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