An Application of New Pedestrian Tracking Sensors for Evaluating Platform Safety Risks at Swiss and Dutch Train Stations

Jeroen van den Heuvel (), Jasmin Thurau (), Martin Mendelin, Rik Schakenbos (), Marcel van Ofwegen () and Serge P. Hoogendoorn ()
Additional contact information
Jeroen van den Heuvel: Delft University of Technology, Department of Transport and Planning, Faculty of Civil Engineering and Geosciences
Jasmin Thurau: Swiss Federal Railways AG (SBB)
Martin Mendelin: Swiss Federal Railways AG (SBB)
Rik Schakenbos: NS Stations, Netherlands Railways (NS)
Marcel van Ofwegen: ProRail
Serge P. Hoogendoorn: Delft University of Technology

A chapter in Traffic and Granular Flow '17, 2019, pp 277-286 from Springer

Abstract: Abstract Due to rapid rail passenger growth in the last years, crowding challenges have risen at several stations in Switzerland and The Netherlands. Particularly at platforms, safety risks can increase when a station is operated near or at pedestrian capacity. Therefore, Swiss and Dutch station managers started several initiatives to measure crowding-related safety risks. Recently, pedestrian measurement technology has improved substantially. New technology is capable of anonymously tracking individual pedestrians within a predefined area under high intensity conditions. This technology has not been implemented at train stations before. Therefore the Swiss and Dutch station managers have developed and applied a methodology to determine the validity of the data which are generated by the newest generation of pedestrian measurement systems at the stations of Bern (CH), Amsterdam Zuid, and Utrecht Centraal (NL). This paper presents the results of the tests in both countries and their (first) implications for science and practice.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-11440-4_31

Ordering information: This item can be ordered from
http://www.springer.com/9783030114404

DOI: 10.1007/978-3-030-11440-4_31

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().