Supervised learning: Predicting passenger load in public transport

Leonie Heydenrijk-Ottens, Viktoriya Degeler, Ding Luo, Niels van Oort, Hans van Lint

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

381 Downloads (Pure)

Abstract

In this extended abstract, we show the supervised learning approach to
predicting passenger load of trams, based on historical passenger load patterns. We look at two different cases: predicting long-term passenger load of any given day and time, and predicting short-term passenger load at a particular public transport vehicle.
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 pages8
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

Conference

ConferenceCaspt 2018: 14th Conference on Advanced Systems in Public Transport and TransitData 2018
Abbreviated titleCASPT 2018
Country/TerritoryAustralia
CityBrisbane
Period23/07/1825/07/18

Keywords

  • Public transport
  • Hubs
  • passenger load
  • supervised learning
  • prediction

Fingerprint

Dive into the research topics of 'Supervised learning: Predicting passenger load in public transport'. Together they form a unique fingerprint.

Cite this