Automatic bottleneck detection using AVL data: A case study in Amsterdam

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In daily practice, public transport authorities and operators are constantly searching for improvements in public transport operations. To this end, it is necessary to identify inefficiencies and bottlenecks in the current public transport services. In this paper, we propose a method to automatically detect bottlenecks in the public transport network, using Automatic Vehicle Location data. A tool is developed to automatically process AVL data to identify bottlenecks for the current situation. This tool is applied to Amsterdam, capital of the Netherlands, where a new metro line will come into operation in the summer of 2018. The results show that bottlenecks are mainly found on radial lines and in the inner city. Therefore we expect that the operations of the tram network will improve in terms of operating speed and reliability due to the opening of the metro line, since the tram lines are expected to become less crowded and fewer lines will traverse the inner city.
Original languageEnglish
Title of host publicationProceedings of Conference on Advanced Systems in Public Transport (CASPT) 2018
Subtitle of host publication23-25 July, Brisbane, Australia
Number of pages14
Publication statusPublished - 2018
EventCaspt 2018: 14th Conference on Advanced Systems in Public Transport and TransitData 2018 - Brisbane Convention and Exhibition Centre, Brisbane, Australia
Duration: 23 Jul 201825 Jul 2018
Conference number: 14


ConferenceCaspt 2018: 14th Conference on Advanced Systems in Public Transport and TransitData 2018
Abbreviated titleCASPT 2018


  • AVL data
  • Bottleneck detection
  • Performance indicators
  • Service Reliability

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