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

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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.

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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。

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来源期刊

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.