Public Transport

, Volume 10, Issue 3, pp 427–453 | Cite as

Visualisation of trip chaining behaviour and mode choice using household travel survey data

  • Günter Wallner
  • Simone Kriglstein
  • Edward ChungEmail author
  • Syeed Anta Kashfi
Original Paper


Planning for transport infrastructure requires forecasting of future travel demand. Various factors such as future population, employment, and the travel behaviour of the residents drive travel demand. In order to better understand human travel behaviour, household travel surveys—which require participants to record all their trips made during a single day or over a whole week—are conducted. However, the daily travel routines of people can be very complex, including routes with multiple stops and/or different purposes and often may involve different modes of transport. Visualisations that are currently employed in transport planning are, however, limited for the analysis of complex trip chains and multi-modal travel. In this paper, we introduce a unique visualisation approach which simultaneously represents several important factors involved in analysing trip chaining: number and type of stops, the quantity of traffic between them, and the utilised modes of transport. Moreover, our proposed technique facilitates the inspection of the sequential relation between incoming and outgoing traffic at stops. Using data from the South-East Queensland Travel Survey 2009, we put our developed algorithm into practice and visualise the journey-to-work travel behaviour of the residents of inner Brisbane, Australia. Our visualisation technique can assist transport planners to better understand the characteristics of the trip data and, in turn, inform subsequent statistical analysis and the development of travel demand models.


Trip chain Multi-modal travel Trip scheduling Human travel behaviour Visualisation Household travel survey 

JEL Classification

R29 R41 R42 



We would like to thank the Queensland Department of Transport and Main Roads for providing the HTS data.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute for Design and Assessment of TechnologyVienna University of TechnologyViennaAustria
  2. 2.Center for Technology ExperienceAIT Austrian Institute of Technology GmbHViennaAustria
  3. 3.Department of Electrical Engineering, Faculty of EngineeringHong Kong Polytechnic UniversityKowloonHong Kong
  4. 4.Queensland University of TechnologyBrisbaneAustralia

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