边缘智能在轨道交通中的应用：前景与展望

朱力; 龚泰源; 梁豪; 唐涛; 王悉; 王洪伟

doi:10.11999/JEIT220116

边缘智能在轨道交通中的应用：前景与展望

doi: 10.11999/JEIT220116

北京交通大学电子信息工程学院北京 100044

基金项目: 国家自然科学基金(61973026)

详细信息

作者简介:
朱力：男，教授，研究方向为交通智能控制与优化

龚泰源：男，博士生，研究方向为交通智能控制与优化

梁豪：男，博士生，研究方向为交通智能控制与优化

唐涛：男，教授，研究方向为轨道交通运行控制系统国产化

王悉：男，副教授，研究方向为交通智能控制与优化

王洪伟：男，副教授，研究方向为交通智能控制与优化

通讯作者:
朱力　lizhu@bjtu.edu.cm

中图分类号: TP18; TP39
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- 被引次数: 0
出版历程
- 收稿日期: 2022-01-27
- 修回日期: 2022-06-20
- 网络出版日期: 2202-06-29
- 刊出日期: 2023-04-10

Application of Edge Intelligence in Rail Transit: Prospects and Future Outlook

School of Electronic Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Funds: The National Natural Science Foundation of China (61973026)

摘要

摘要: 边缘智能作为一项新兴技术，正受到国内外学者的广泛关注，其作为人工智能技术与边缘计算技术的结合，有望促进人工智能技术在各行业的部署，加速产业智能化进程。该文首先介绍了边缘智能技术的基本原理、系统架构及其比较优势，梳理了边缘智能技术的国内外研究现状；分析了边缘智能在轨道交通建设工程、运维调度、智能控制、改造升级的全生命周期应用前景，详述了边缘智能技术在轨道交通过程管理控制、建设现场数据采集分析、信息共享、智能运维、智能调度、自动驾驶系统、列车协同控制及改造升级等全生命周期中的赋能作用。该文随后设计与实现了轨道交通智能运行控制为背景下的边缘智能平台，测试基于深度学习和强化学习的边缘智能应用的功能及性能。最后，归纳了边缘智能技术在轨道交通领域应用的问题与挑战。该文的研究期望为轨道交通领域的边缘智能应用提供有益的借鉴和实践基础。
- 边缘智能 /
- 轨道交通运输 /
- 人工智能 /
- 边缘计算
Abstract: As an emerging technology, edge intelligence is receiving extensive attention from scholars at home and abroad. As a combination of artificial intelligence technology and edge computing technology, it is expected to promote the deployment of artificial intelligence technology in various industries and accelerate the process of industrial intelligence. In this paper the basic principles, system architecture, and comparative advantages of edge intelligence technology, and sorts out the research status of edge intelligence technology at home and abroad are first introduced. The application prospects of the life cycle, the application of edge intelligence technology in the whole life cycle of rail transit process management and control, construction site data collection and analysis, information sharing, intelligent operation and maintenance, intelligent scheduling, automatic driving system, train coordination control, and transformation and upgrading are described in detail. Then the designs and implements an edge intelligent platform under the background of rail transit intelligent operation control, and tests the functions and performance of edge intelligence applications based on deep learning and reinforcement learning are discussed. Finally, the problems and challenges in the application of edge intelligence technology to the field of rail transit are summarized. The research in this paper is expected to provide a useful reference and practical basis for edge intelligence applications to the field of rail transit.
- Edge intelligence /
- Rail transportation /
- Artificial intelligence /
- Edge computing

HTML全文

图 1 边缘智能基础架构

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图 2 基于边缘智能的轨道交通信息共享

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图 3 基于边缘智能的轨道交通智能运维架构

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图 4 基于边缘智能的轨道交通智能调度架构

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图 5 基于边缘智能的列车协同控制架构

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图 6 基于边缘智能的轨道交通智慧化框架

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图 7 面向轨道交通沿线障碍物识别与测距的边缘智能系统

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图 8 边缘智能列车障碍物告警系统平台

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图 9 云、边、端3种计算模式时延测试

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图 10 卸载策略时延测试

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