Perception and Planning of Intelligent Vehicles Based on BEV in Extreme Off-Road Scenarios

IF 14 1区 工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Intelligent Vehicles Pub Date : 2024-04-23 DOI:10.1109/TIV.2024.3392753
Jingjing Fan;Lili Fan;Qinghua Ni;Junhao Wang;Yi Liu;Ren Li;Yutong Wang;Sanjin Wang
{"title":"Perception and Planning of Intelligent Vehicles Based on BEV in Extreme Off-Road Scenarios","authors":"Jingjing Fan;Lili Fan;Qinghua Ni;Junhao Wang;Yi Liu;Ren Li;Yutong Wang;Sanjin Wang","doi":"10.1109/TIV.2024.3392753","DOIUrl":null,"url":null,"abstract":"In extreme off-road scenarios, autonomous driving technology holds strategic significance for enhancing emergency rescue capabilities, reducing labor intensity, and mitigating safety risks. Challenges such as adverse conditions, complex terrains, unstable satellite signals, and lack of roads pose serious safety challenges for autonomous driving. This perspective first delves into a Bird's Eye View (BEV)-based perception-planning framework, aiming to enhance the adaptability of intelligent vehicles to their environment. Subsequently, this perspective further discusses key issues such as Cyber-Physical-Social Systems (CPSS), foundation models, and technologies like Sora for off-road scenario generation, vehicle cognitive enhancement, and autonomous decision-making. Ultimately, the discussed framework is poised to endow intelligent vehicles with the capability to perform challenging tasks in complex off-road scenarios, realizing a more efficient, safer, and sustainable transportation system, thereby providing better support for the low-altitude economy.","PeriodicalId":36532,"journal":{"name":"IEEE Transactions on Intelligent Vehicles","volume":"9 4","pages":"4568-4572"},"PeriodicalIF":14.0000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Intelligent Vehicles","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10507030/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In extreme off-road scenarios, autonomous driving technology holds strategic significance for enhancing emergency rescue capabilities, reducing labor intensity, and mitigating safety risks. Challenges such as adverse conditions, complex terrains, unstable satellite signals, and lack of roads pose serious safety challenges for autonomous driving. This perspective first delves into a Bird's Eye View (BEV)-based perception-planning framework, aiming to enhance the adaptability of intelligent vehicles to their environment. Subsequently, this perspective further discusses key issues such as Cyber-Physical-Social Systems (CPSS), foundation models, and technologies like Sora for off-road scenario generation, vehicle cognitive enhancement, and autonomous decision-making. Ultimately, the discussed framework is poised to endow intelligent vehicles with the capability to perform challenging tasks in complex off-road scenarios, realizing a more efficient, safer, and sustainable transportation system, thereby providing better support for the low-altitude economy.
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
基于 BEV 的智能车辆在极端越野场景中的感知与规划
在极端越野场景中,自动驾驶技术对于提高应急救援能力、降低劳动强度和减少安全风险具有重要的战略意义。恶劣的条件、复杂的地形、不稳定的卫星信号、缺乏道路等挑战给自动驾驶带来了严峻的安全挑战。本视角首先深入探讨了基于鸟瞰(BEV)的感知规划框架,旨在增强智能车辆对环境的适应性。随后,本视角进一步讨论了一些关键问题,如网络-物理-社会系统(CPSS)、基础模型以及用于越野场景生成、车辆认知增强和自主决策的 Sora 等技术。最终,所讨论的框架将赋予智能车辆在复杂越野场景中执行挑战性任务的能力,实现更高效、更安全和可持续的交通系统,从而为低空经济提供更好的支持。
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
IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization
CiteScore
12.10
自引率
13.40%
发文量
177
期刊介绍: The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.
期刊最新文献
Table of Contents Introducing IEEE Collabratec The Autonomous Right of Way: Smart Governance for Smart Mobility With Intelligent Vehicles TechRxiv: Share Your Preprint Research with the World! Blank
×
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