Assessment of architectures for Automatic Train Operation driving functions

被引:7
|
作者
Wang, Ziyulong [1 ]
Quaglietta, Egidio [1 ]
Bartholomeus, Maarten G. P. [2 ]
Goverde, Rob M. P. [1 ]
机构
[1] Delft Univ Technol, Dept Transport & Planning, POB 5048, NL-2600 GA Delft, Netherlands
[2] ProRail, Dept Automatic Train Operat, POB 2038, NL-3511 EP Utrecht, Netherlands
关键词
Automatic Train Operation; Connected Driver Advisory System; Train Path Envelope; Train trajectory generation; ATO-over-ETCS; SWOT; TRAFFIC MANAGEMENT; TRAJECTORY OPTIMIZATION; INTEGRATION; FRAMEWORK; RAILWAYS; SYSTEMS;
D O I
10.1016/j.jrtpm.2022.100352
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Automatic Train Operation (ATO) is well-known in urban railways and gets increasing interest from mainline railways at present to improve capacity and punctuality. A main function of ATO is the train trajectory generation that specifies the speed profile over the given running route considering the timetable and the characteristics of the train and infrastructure. This paper proposes and assesses different possible ATO architecture configurations through allocating the intelligent components on the trackside or onboard. The set of analyzed ATO architecture configurations is based on state-of-the-art architectures proposed in the literature for the related Connected Driver Advisory System (C-DAS). Results of the SWOT analysis highlight that different ATO configurations have diverse advantages or limitations, depending on the type of railway governance and the technological development of the existing railway signaling and communication equipment. In addition, we also use the results to spotlight operational, technological, and business advantages/limitations of the proposed ATO-over-ETCS architecture that is being developed by the European Union Agency for Railways (ERA) and provide a scientific argumentation for it.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Decentralized Model Predictive Control for Automatic Train Operation System
    Liu, Di
    Xu, Youxiong
    Zhu, Songqing
    Liu, Kun
    Qiao, Guifang
    2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (IEEE ICIA 2017), 2017, : 428 - 433
  • [42] Automatic adjustment for the train operation stage plan in Tianjin TDCS
    Xu, Wei
    Yang, Liya
    Qin, Yanyan
    Zhang, Nan
    Zhongguo Tiedao Kexue/China Railway Science, 2008, 29 (02): : 114 - 119
  • [43] Automatic adjustment system of train operation plan based on BPM
    Xing, Kejia
    Liu, Haowei
    Zhongguo Tiedao Kexue/China Railway Science, 2009, 30 (01): : 114 - 117
  • [44] CONTRACTION-BASED ADAPTIVE CONTROL FOR AUTOMATIC TRAIN OPERATION
    Wang, Longsheng
    Xu, Hongze
    Luo, Hengyu
    CONTROL AND INTELLIGENT SYSTEMS, 2016, 44 (01) : 1 - 9
  • [45] Formal Design and Validation of an Automatic Train Operation Control System
    Amendola, Arturo
    Barruffo, Lorenzo
    Bozzano, Marco
    Cimatti, Alessandro
    De Simone, Salvatore
    Fedeli, Eugenio
    Gabbasov, Artem
    Garrubba, Domenico Ernesto
    Girardi, Massimiliano
    Serra, Diana
    Tiella, Roberto
    Zampedri, Gianni
    RELIABILITY, SAFETY, AND SECURITY OF RAILWAY SYSTEMS: MODELLING, ANALYSIS, VERIFICATION, AND CERTIFICATION, RSSRAIL 2022, 2022, 13294 : 169 - 178
  • [46] Locomotive Driving Simulator for Multi-objective Train Operation and Movement
    Ding, Yong
    INFORMATION AND AUTOMATION, 2011, 86 : 404 - 410
  • [47] Verification of Optimized Energy-Saving Train Scheduling Utilizing Automatic Train Operation System
    Watanabe, Shoichiro
    Sato, Yasuhiro
    Koseki, Takafumi
    Mizuma, Takeshi
    Tanaka, Ryuji
    Miyaji, Yoshihiro
    Isobe, Eisuke
    IEEJ JOURNAL OF INDUSTRY APPLICATIONS, 2020, 9 (02) : 193 - 200
  • [48] Train scheduling and energy saving with pure electric braking and semi-automatic train operation
    Sone, S
    Suzuki, T
    Koseki, T
    COMPUTERS IN RAILWAYS VII, 2000, 7 : 517 - 525
  • [49] Model-based development of an Automatic Train Operation component for Communication Based Train Control
    Di Claudio, Mariano
    Fantechi, Alessandro
    Martelli, Giacomo
    Menabeni, Simone
    Nesi, Paolo
    2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 1015 - 1020
  • [50] Verification of optimized energy-saving train scheduling utilizing automatic train operation system
    Watanabe S.
    Sato Y.
    Koseki T.
    Mizuma T.
    Tanaka R.
    Miyaji Y.
    Isobe E.
    IEEJ Transactions on Industry Applications, 2019, 139 (06) : 580 - 587