地铁列车驾驶技术发展综述：从人工驾驶到智能无人驾驶

赖文柱; 陈德旺; 何振峰; 邓新国; GIUSEPPE CARLO Marano

doi:10.11959/j.issn.2096-6652.202204

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地铁列车驾驶技术发展综述：从人工驾驶到智能无人驾驶

综述与展望 | 更新时间：2024-06-05

- 地铁列车驾驶技术发展综述：从人工驾驶到智能无人驾驶
- Overview of metro train driving technology development:from manual driving to intelligent unmanned driving
- 智能科学与技术学报 2022年4卷第3期页码：335-343
- 作者机构：
  
  1. 福州大学计算机与大数据学院，福建福州 350108
  2. 福州大学智慧地铁福建省高校重点实验室，福建福州 350108
  3. 福建工程学院交通运输学院，福建福州 350118
  4. 都灵理工大学，意大利都灵 EI10129
- 作者简介：
  
  [ "赖文柱（1997- ），男，福州大学计算机与大数据学院硕士生，主要研究方向为深度强化学习与地铁无人驾驶" ]
  [ "陈德旺（1976- ），男，博士，福州大学计算机与大数据学院教授、博士生导师，福建工程学院交通运输学院院长，福州大学智慧地铁福建省高校重点实验室研究员，福建省“闽江学者”特聘教授。主要研究方向为人工智能、大数据、智慧轨道交通" ]
  [ "何振峰（1971- ），男，博士，福州大学计算机与大数据学院副教授，主要研究方向为数据挖掘、智能交通、农业信息技术" ]
  [ "邓新国（1975- ），男，博士，福州大学计算机与大数据学院副教授，主要研究方向为印刷电路板转移路由、印刷电路板总线布线/列车智能驾驶" ]
  [ "GIUSEPPE CARLO Marano（1967- ），男，博士，都灵理工大学结构、建筑和岩土工程系教授，主要研究方向为土木工程、智能建造和智能交通系统" ]
- 基金信息：
  
  国家自然科学基金项目(61976055);国家自然科学基金资助项目;The National Natural Science Foundation of China(61906043);福建省财政厅教育和科研专项资金项目(GY-Z21001);福州大学人才项目;Fuzhou University Talent Project(510809/GXRC-19037);福州大学人才项目;Fuzhou University Talent Project(510730/XRC-18075)
- DOI：10.11959/j.issn.2096-6652.202204
  中图分类号： TP273，TP314.41
- 网络出版日期：2022-09，
  
  纸质出版日期：2022-09-15
- 稿件说明：
移动端阅览
赖文柱, 陈德旺, 何振峰, 等. 地铁列车驾驶技术发展综述：从人工驾驶到智能无人驾驶[J]. 智能科学与技术学报, 2022,4(3):335-343.

Wenzhu LAI, Dewang CHEN, Zhenfeng HE, et al. Overview of metro train driving technology development:from manual driving to intelligent unmanned driving[J]. Chinese journal of intelligent science and technology, 2022, 4(3): 335-343.
赖文柱, 陈德旺, 何振峰, 等. 地铁列车驾驶技术发展综述：从人工驾驶到智能无人驾驶[J]. 智能科学与技术学报, 2022,4(3):335-343. DOI： 10.11959/j.issn.2096-6652.202204.

Wenzhu LAI, Dewang CHEN, Zhenfeng HE, et al. Overview of metro train driving technology development:from manual driving to intelligent unmanned driving[J]. Chinese journal of intelligent science and technology, 2022, 4(3): 335-343. DOI： 10.11959/j.issn.2096-6652.202204.

摘要

基于国内外地铁列车驾驶技术的发展现状，提出并阐述了地铁列车驾驶技术发展的4个阶段为人工驾驶、自动驾驶、无人驾驶、智能无人驾驶。概括了我国无人驾驶地铁列车的建设情况，针对目前基于神经网络这类机器学习方法的列车控制方法可解释性差的弊端，引入了深度模糊系统的概念，提出了基于人机混合智能的地铁智能无人驾驶基本框图，为将处理紧急情况的专家经验、人工智能算法和无人驾驶系统结合起来，实现智能无人驾驶提供了一种具有前景的解决思路。

Abstract

Based on the current development status of subway train driving technology in China and abroad

the four stages of subway train driving technology development were proposed and explained as manual driving

automatic driving

unmanned driving

and intelligent unmanned driving.After summarizing the construction situation of unmanned subway trains in China

the disadvantages of the current train control methods based on neural network-based machine learning methods were addressed.Then

the basic block diagram of metro intelligent unmanned driving based on man-machine hybrid intelligence was put forward and the deep fuzzy system was introduced.A promising solution for the combination of expert experience in dealing with emergency and interpretable AI algorithms for unmanned driving system to evolve into intelligent unmanned driving was provided.

关键词

Keywords

references

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