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Investigation and analysis of evidence of asymmetric churn in travel demand models

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  • Saleh, Wafaa
  • Farrell, Séona

Abstract

There is a large amount of research work that has been devoted to the understanding of travel behaviour and for the prediction of travel demand and its management. Different types of data including stated preference and revealed preference, as well as different modelling approaches have been used to predict this. Essential to most travel demand forecasting models are the concepts of utility maximisation and equilibrium, although there have been alternative approaches for modelling travel behaviour. In this paper, the concept of asymmetric churn is discussed. That is travel behaviour should be considered as a two way process which changes over time. For example over time some travellers change their mode of travel from car to bus, but more travellers change their mode from bus to car. These changes are not equal and result in a net change in aggregate travel behaviour. Transport planners often aim at producing this effect in the opposite direction. It is important therefore to recognise the existence of churns in travel behaviour and to attempt to develop appropriate policies to target different groups of travellers with the relevant transport policies in order to improve the transport system. A data set collected from a recent large survey, which was carried out in Edinburgh is investigated to analyse the variations in departure time choice behaviour. The paper reports on the results of the investigation.

Suggested Citation

  • Saleh, Wafaa & Farrell, Séona, 2007. "Investigation and analysis of evidence of asymmetric churn in travel demand models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(7), pages 691-702, August.
    • Handle: RePEc:eee:transa:v:41:y:2007:i:7:p:691-702
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    References listed on IDEAS

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    1. Saleh, Wafaa & Farrell, Séona, 2005. "Implications of congestion charging for departure time choice: Work and non-work schedule flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 773-791.
    2. Cirillo, C. & Axhausen, K.W., 2006. "Evidence on the distribution of values of travel time savings from a six-week diary," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(5), pages 444-457, June.
    3. Farrell, Séona & Saleh, Wafaa, 2005. "Road-user charging and the modelling of revenue allocation," Transport Policy, Elsevier, vol. 12(5), pages 431-442, September.
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    3. Chang, Hsin-Li & Wu, Shun-Cheng, 2008. "Exploring the vehicle dependence behind mode choice: Evidence of motorcycle dependence in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 307-320, February.
    4. Lyons, Glenn & Hammond, Paul & Mackay, Kate, 2020. "Reprint of: The importance of user perspective in the evolution of MaaS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 20-34.

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