Map-Matching Techniques for Train Localization: A Taxonomic Survey

被引:0
|
作者
Millan-Jimenez, Iker [1 ]
Zabalegui, Paul
de Miguel, Gorka
Mendizabal, Jaizki
Marcos, Inigo Adin
机构
[1] CEIT Basque Res & Technol Alliance BRTA Res Ctr, Donostia San Sebastian 20018, Spain
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Surveys; Rail transportation; Sensors; Geometry; Classification algorithms; Accuracy; Databases; Tracking; Global navigation satellite system; Splines (mathematics); Algorithm classification; digital map; mapmatching; train localization;
D O I
10.1109/ACCESS.2024.3516933
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Precise localisation of rail vehicles is a key element towards the development and deployment of novel train control systems. Localisation of trains can be considered as a 1-D localisation problem, as trains only move on tracks, easing the localisation approach. Localisation with maps makes a great choice as the maps describe unambiguously train tracks, easing the train localisation and making it an effective choice. On top of that, train localisation with a map requires just onboard sensors making it a low-cost alternative to localisation with track-side equipment, as this equipment makes train localisation costs increase with the reach of the use. Even though this topic has been widely studied in the literature, there has not been a classification of the used methodologies for map-matching for train localisation. Therefore, the purpose of this paper is to make a classification of the state-of-the-art map-matching algorithms for train localisation. On top of that, this paper also discusses how to build a digital map from a set of coordinates. Three main categories have been identified in the literature for map-matching: geometric, similarity and hypothesis. And mainly three types of digital maps have been observed in the literature: interpolation, splines and geometric. This paper helps practitioners and researchers have a comprehensive foundation on map-matching for train localisation.
引用
收藏
页码:192328 / 192340
页数:13
相关论文
共 50 条
  • [1] A Survey on Map-Matching Algorithms
    Chao, Pingfu
    Xu, Yehong
    Hua, Wen
    Zhou, Xiaofang
    DATABASES THEORY AND APPLICATIONS, ADC 2020, 2020, 12008 : 121 - 133
  • [2] EVALUATION OF MAP-MATCHING TECHNIQUES
    MORISUE, F
    IKEDA, K
    CONFERENCE RECORD OF PAPERS PRESENTED AT THE FIRST VEHICLE NAVIGATION AND INFORMATION SYSTEMS CONFERENCE ( VNIS 89 ), 1989, : 23 - 28
  • [3] Post-processing of fingerprint localization using Kalman filter and map-matching techniques
    Takenga, Claude
    Peng, Tao
    Kyamakya, Kyandoghere
    9TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY: TOWARD NETWORK INNOVATION BEYOND EVOLUTION, VOLS 1-3, 2007, : 2029 - +
  • [4] Particle Filter Vehicle Localization and Map-Matching Using Map Topology
    Peker, Ali Ufuk
    Tosun, Oguz
    Acarman, Tankut
    2011 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2011, : 248 - 253
  • [5] A Localization Method Based on Map-Matching and Particle Swarm Optimization
    Andry M. Pinto
    António P. Moreira
    Paulo G. Costa
    Journal of Intelligent & Robotic Systems, 2015, 77 : 313 - 326
  • [6] A Localization Method Based on Map-Matching and Particle Swarm Optimization
    Pinto, Andry M.
    Moreira, Antonio P.
    Costa, Paulo G.
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2015, 77 (02) : 313 - 326
  • [7] Multi-Hypothesis Based Map-Matching Algorithm for Precise Train Positioning
    Gerlach, Katrin
    Rahmig, Christian
    FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2009, : 1363 - 1369
  • [8] Map-matching methods in agriculture
    Silva, Anibal
    Mendes-Moreira, Joao
    Ferreira, Carlos
    Costa, Nuno
    Dias, Duarte
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 216
  • [9] Integrity of map-matching algorithms
    Quddus, Mohammed A.
    Ochieng, Washington Y.
    Noland, Robert B.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2006, 14 (04) : 283 - 302
  • [10] From driving trajectories to driving paths: a survey on map-matching Algorithms
    Jiang, Linli
    Chen, Chaoxiong
    Chen, Chao
    Huang, Hongyu
    Guo, Bin
    CCF TRANSACTIONS ON PERVASIVE COMPUTING AND INTERACTION, 2022, 4 (03) : 252 - 267