Development of bus intelligent dispatching system based on reinforcement learning

被引:0
|
作者
Zou, L [1 ]
Xu, LM [1 ]
Zhu, LX [1 ]
机构
[1] S China Univ Technol, Coll Traff & Commun, Guangzhou 510640, Peoples R China
关键词
bus dispatching; reinforcement learning; intelligent transportation systems;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The Bus Intelligent Dispatching System (BIDS) is established according to the status of bus operating including vehicle location and number of passengers, making the best use of Reinforcement Learning (RL). The information about vehicle location can be got by Global Position System (GPS) receivers installed on buses. The infrared beams on buses can get the number of passengers on buses. We use a team of RL agents, each of which is responsible for controlling one route. Finally, the developed algorithm is implemented with ten bus routes of Guangzhou City. The results demonstrate the power of RL on bus dispatching problem.
引用
收藏
页码:372 / 376
页数:5
相关论文
共 50 条
  • [31] An Intelligent IoT Based Traffic Light Management System: Deep Reinforcement Learning
    Damadam, Shima
    Zourbakhsh, Mojtaba
    Javidan, Reza
    Faroughi, Azadeh
    SMART CITIES, 2022, 5 (04): : 1293 - 1311
  • [32] SmartGantt - An intelligent system for real time rescheduling based on relational reinforcement learning
    Palombarini, Jorge
    Martinez, Ernesto
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (11) : 10251 - 10268
  • [33] Intelligent Anti-Jamming Relay Communication System Based on Reinforcement Learning
    Zhang, Zixuan
    Wu, Qinhao
    Zhang, Bo
    Peng, Jinlin
    PROCEEDINGS OF 2019 2ND INTERNATIONAL CONFERENCE ON COMMUNICATION ENGINEERING AND TECHNOLOGY (ICCET 2019), 2019, : 52 - 56
  • [34] A Recommendation Module based on Reinforcement Learning to an Intelligent Tutoring System for Software Maintenance
    Francisco, Rodrigo Elias
    Silva, Flavin de Oliveira
    CSEDU: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED EDUCATION - VOL 1, 2022, : 322 - 329
  • [35] Intelligent Adjustment for Power System Operation Mode Based on Deep Reinforcement Learning
    Hu, Wei
    Mi, Ning
    Wu, Shuang
    Zhang, Huiling
    Hu, Zhewen
    Zhang, Lei
    IENERGY, 2024, 3 (04): : 252 - 260
  • [36] Industrial General Reinforcement Learning Control Framework System based on Intelligent Edge
    Kim, Kwihoon
    Hong, Yong-Geun
    2020 22ND INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): DIGITAL SECURITY GLOBAL AGENDA FOR SAFE SOCIETY!, 2020, : 414 - 418
  • [37] Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning
    Urban, R.
    Drexler, P.
    PIERS 2014 GUANGZHOU: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2014, : 2322 - 2325
  • [38] Reinforcement learning and blockchain-based intelligent and secure vaccine recommender system
    Sreenu, M.
    Gupta, Nitin
    Jatoth, Chandrashekar
    Gupta, Deepak
    EXPERT SYSTEMS, 2024, 41 (01)
  • [39] MobiRescue: Reinforcement Learning based Rescue Team Dispatching in a Flooding Disaster
    Yan, Li
    Mahmud, Shohaib
    Shen, Haiying
    Foutz, Natasha Zhang
    Anton, Joshua
    2020 IEEE 40TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS), 2020, : 111 - 121
  • [40] A reinforcement learning and deep learning based intelligent system for the support of impaired patients in home treatment
    Naeem, Muddasar
    Paragliola, Giovanni
    Coronato, Antonio
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 168