基于人机混合智能的地铁列车无人驾驶系统研究

doi:10.11959/j.issn.2096-6652.202205

智能科学与技术学报 ›› 2022, Vol. 4 ›› Issue (4): 584-591.doi: 10.11959/j.issn.2096-6652.202205

基于人机混合智能的地铁列车无人驾驶系统研究

黄本遵¹^,², 陈德旺¹^,³, 何振峰¹^,², 邓新国¹^,², GIUSEPPE CARLO Marano⁴

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

修回日期:2021-03-20 出版日期:2022-12-15 发布日期:2022-12-01
作者简介:黄本遵（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
基金资助:
国家自然科学基金资助项目(61976055);国家自然科学基金资助项目(61906043);福建省财政厅教育科研专项资金(GY-Z21001);福州大学人才项目(510809/GXRC-19037);福州大学人才项目(510730/XRC-18075)

Research on metro train driverless system based on man-machine hybrid intelligence

Benzun HUANG¹^,², Dewang CHEN¹^,³, Zhenfeng HE¹^,², Xinguo DENG¹^,², Marano GIUSEPPECARLO⁴

¹ College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
² Key Laboratory of Intelligent Metro of Universities in Fujian, Fuzhou University, Fuzhou 350108, China
³ School of Transportation, Fujian University of Technology, Fuzhou 350118, China
⁴ Politecnico di Torino, Turin EI10129, Italy

Revised:2021-03-20 Online:2022-12-15 Published:2022-12-01
Supported by:
The National Natural Science Foundation of China(61976055);The National Natural Science Foundation of China(61906043);Special Fund of Education and Scientific Research of Fujian Provincial Department of Finance(GY-Z21001);Fuzhou University Talent Project(510809/GXRC-19037);Fuzhou University Talent Project(510730/XRC-18075)

摘要/Abstract

摘要：

基于国内外地铁列车驾驶技术的发展现状，阐述了地铁列车智能驾驶发展及研究的必要性。针对当前无人驾驶采用的机器学习算法可解释性差的缺陷，引入模糊系统，提出了基于人机混合智能的地铁列车无人驾驶系统，以两种方式实现人机混合智能。探索了结合认知系统的地铁列车无人驾驶系统，为实现真正意义上的强人工智能地铁列车无人驾驶系统提供了一种面向未来的解决方案。

关键词: 地铁, 无人驾驶, 人机混合智能

Abstract:

Based on the development status of subway train driving technology at home and abroad, the necessity of subway train intelligent driving development and research was expounded.In view of the poor interpretability of machine learning algorithms used in current unmanned driving, with an introduction of fuzzy system, a metro train unmanned driving system based on man-machine hybrid intelligence was proposed, which realized man-machine hybrid intelligence in two ways.The subway train driverless system combined with cognitive system was explored, which a future-oriented solution for the realization of strong artificial intelligence subway train driverless system in the real sense was provided.

Key words: metro, unmanned driving, man-machine hybrid intelligence

中图分类号:

TP311.1，TP18

黄本遵, 陈德旺, 何振峰, 等. 基于人机混合智能的地铁列车无人驾驶系统研究[J]. 智能科学与技术学报, 2022, 4(4): 584-591.

Benzun HUANG, Dewang CHEN, Zhenfeng HE, et al. Research on metro train driverless system based on man-machine hybrid intelligence[J]. Chinese Journal of Intelligent Science and Technology, 2022, 4(4): 584-591.

图/表 5

参考文献 29

[1]	刘涛, 杨帆 . 浅谈我国地铁发展现状及展望[J]. 中小企业管理与科技(上旬刊), 2014(2): 129-130.
	LIU T , YANG F . On the present situation and prospect of subway development in China[J]. Management ＆ Technology of SME, 2014(2): 129-130.
[2]	朱建峰 . 我国智慧地铁发展现状与展望[J]. 佛山科学技术学院学报(自然科学版), 2019,37(4): 6-9.
	ZHU J F . Development status and prospect of smart metro in China[J]. Journal of Foshan University (Natural Science Edition), 2019,37(4): 6-9.
[3]	叶浪 . 我国地铁现状及发展的必要性研究[J]. 才智, 2013(3): 309.
	YE L . The necessity research of our country subway present situation and development[J]. Intelligence , 2013(3): 309.
[4]	李子钧 . 基于模糊自适应PID控制的列车自动驾驶系统的研究[D]. 北京:北京交通大学, 2010.
	LI Z J . Research of automatic train operation system based on fuzzy self-adaptive PID[D]. Beijing:Beijing Jiaotong University, 2010.
[5]	冷勇林 . 基于专家经验和机器学习的列车智能驾驶算法研究[D]. 北京:北京交通大学, 2013.
	LENG Y L . Intelligent train operation algorithm based on expert knowledge and machine learning[D]. Beijing:Beijing Jiaotong University, 2013.
[6]	康太平 . 基于模糊预测控制的列车自动驾驶系统研究[D]. 成都:西南交通大学, 2006.
	KANG T P . Study on automatic train operation based on fuzzy prediction control[D]. Chengdu:Southwest Jiaotong University, 2006.
[7]	宗明, 郜春海, 何燕 . 基于 CBTC 控制的全自动驾驶系统[J]. 都市快轨交通, 2006,19(3): 34-36.
	ZONG M , GAO C H , HE Y . Fully automatic operation system based on CBTC[J]. Urban Rapid Rail Transit, 2006,19(3): 34-36.
[8]	张强 . 基于遗传算法的列车自动驾驶系统研究与实现[D]. 北京:北京交通大学, 2008.
	ZHANG Q . Research and implementation of automatic train operation system based on genetic algorithm[D]. Beijing:Beijing Jiaotong University, 2008.
[9]	张淼 . 基于强化学习的列车自动驾驶方法研究[D]. 北京:中国铁道科学研究院, 2020.
	ZHANG M . Research on automatic train operation based on reinforcement learning[D]. Beijing:China Academy of Railway Sciences, 2020.
[10]	国际电工委员会. 铁路应用设施.都市自动化有轨运输(AUGT).安全性要求:IEC 62267-2009[S]. 2009.
	International Electrotechnical Commission. Railway applications automated urban guided transport (AUGT)-safety requirements:IEC 62267-2009[S]. 2009.
[11]	杨苑斐, 申永勇, 王子超 . 上海轨道交通15号线全自动驾驶列车设计概述[J]. 上海电气技术, 2020,13(4): 43-47.
	YANG Y F , SHEN Y Y , WANG Z C . Overview of design of self-driving train on Shanghai rail transit line 15[J]. Journal of Shanghai Electric Technology, 2020,13(4): 43-47.
[12]	张崔中 . 我国首条全自动驾驶地铁“上岗”[J]. 新长征(党建版), 2017(5): 60.
	ZHANG C Z . Chinese first fully autonomous subway train begins work[J]. Xin Chang Zheng, 2017(5): 60.
[13]	陈荣武, 刘莉, 诸昌钤 . 基于 CBTC 的列车自动驾驶控制算法[J]. 计算机应用, 2007,27(11): 2649-2651.
	CHEN R W , LIU L , ZHU C Q . Automatic train operation and its control algorithm based on CBTC[J]. Journal of Computer Applications, 2007,27(11): 2649-2651.
[14]	吴飞, 廖彬兵, 韩亚洪 . 深度学习的可解释性[J]. 航空兵器, 2019,26(1): 39-46.
	WU F , LIAO B B , HAN Y H . Interpretability for deep learning[J]. Aero Weaponry, 2019,26(1): 39-46.
[15]	唐振韬, 邵坤, 赵冬斌 ,等. 深度强化学习进展:从 AlphaGo到AlphaGo Zero[J]. 控制理论与应用, 2017(12): 1529-1546.
	TANG Z T , SHAO K , ZHAO D B ,et al. Recent progress of deep reinforcement learning:from AlphaGo to AlphaGo Zero[J]. Control Theory ＆ Applications, 2017(12): 1529-1546.
[16]	郑南宁 . 人工智能新时代[J]. 智能科学与技术学报, 2019,1(1): 1-3.
	ZHENG N N . The new era of artificial intelligence[J]. Chinese Journal of Intelligent Science and Technology, 2019,1(1): 1-3.
[17]	SASAKI K , EGUCHI Y , SUZUKI K . Step-climbing wheelchair with lever propelled rotary legs[C]// Proceedings of 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway:IEEE Press, 2015: 6354-6359.
[18]	SU H , YANG C G , FERRIGNO G ,et al. Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery[J]. IEEE Robotics and Automation Letters, 2019,4(2): 1447-1453.
[19]	ROZO L , BRUNO D , CALINON S ,et al. Learning optimal controllers in human-robot cooperative transportation tasks with position and force constraints[C]// Proceedings of 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway:IEEE Press, 2015: 1024-1030.
[20]	HUANG R , CHENG H , GUO H L ,et al. Learning cooperative primitives with physical human-robot interaction for a human-powered lower exoskeleton[C]// Proceedings of 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway:IEEE Press, 2016: 5355-5360.
[21]	BENDERIUS O , BERGER C , MALMSTEN LUNDGREN V . The best rated human-machine interface design for autonomous vehicles in the 2016 grand cooperative driving challenge[J]. IEEE Transactions on Intelligent Transportation Systems, 2018,19(4): 1302-1307.
[22]	STRICKLAND M , FAINEKOS G , AMOR H B . Deep predictive models for collision risk assessment in autonomous driving[C]// Proceedings of 2018 IEEE International Conference on Robotics and Automation. Piscataway:IEEE Press, 2018: 4685-4692.
[23]	BARABáS I , TODORU? A , CORDO? N ,et al. Current challenges in autonomous driving[J]. IOP Conference Series:Materials Science and Engineering, 2017,252:012096.
[24]	吴超仲, 吴浩然, 吕能超 . 人机共驾智能汽车的控制权切换与安全性综述[J]. 交通运输工程学报, 2018,18(6): 131-141.
	WU C Z , WU H R , LYU N C . Review of control switch and safety of human-computer driving intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2018,18(6): 131-141.
[25]	王述彦, 师宇, 冯忠绪 . 基于模糊PID控制器的控制方法研究[J]. 机械科学与技术, 2011,30(1): 166-172.
	WANG S Y , SHI Y , FENG Z X . A method for controlling a loading system based on a fuzzy PID controller[J]. Mechanical Science and Technology for Aerospace Engineering, 2011,30(1): 166-172.
[26]	陈德旺, 蔡际杰, 黄允浒 . 面向可解释性人工智能与大数据的模糊系统发展展望[J]. 智能科学与技术学报, 2019,1(4): 327-334.
	CHEN D W , CAI J J , HUANG Y H . Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data[J]. Chinese Journal of Intelligent Science and Technology, 2019,1(4): 327-334.
[27]	程洪, 黄瑞, 邱静 ,等. 人机智能技术及系统研究进展综述[J]. 智能系统学报, 2020,15(2): 386-398.
	CHENG H , HUANG R , QIU J ,et al. A survey of recent advances in human-robot intelligent systems[J]. CAAI Transactions on Intelligent Systems, 2020,15(2): 386-398.
[28]	张力平 . 非凡的认知计算[J]. 电信快报, 2017(8): 28.
	ZHANG L P . Extraordinary cognitive computing[J]. Telecommunications Information, 2017(8): 28.
[29]	陈霖 . 新一代人工智能的核心基础科学问题:认知和计算的关系[J]. 中国科学院院刊, 2018,33(10): 1104-1106.
	CHEN L . The core basic scientific problem of the new generation of artificial intelligence:the relationship between cognition and computation[J]. Bulletin of Chinese Academy of Sciences, 2018,33(10): 1104-1106.

基于人机混合智能的地铁列车无人驾驶系统研究

Research on metro train driverless system based on man-machine hybrid intelligence

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 29

相关文章 3

Metrics

推荐阅读 0

[1]	赖文柱, 陈德旺, 何振峰, 邓新国, GIUSEPPE CARLO Marano. 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.
[2]	芦玉琦, 陈德旺, 赵钊林. 基于AlphaZero的地铁列车大量速度曲线自动生成算法[J]. 智能科学与技术学报, 2021, 3(2): 179-184.
[3]	苏宏业, 周泽, 刘之涛, 张立炎. 电动汽车智能动态无线充电系统的研究现状与展望[J]. 智能科学与技术学报, 2020, 2(1): 1-9.