Are the Modes of Transport Independent? Assessing Multimodal Mobility at the Individual Level

Multimodality is a concept that has received increasing attention in urban mobility. It involves considering all modes of transport as complementary options for travelling and is systematically presented as a key means of reducing car dependency and making transportation more sustainable. However, few tools have been developed to support this new concept. Most of the related policies are focused on technological devices, but prior knowledge about multimodal behaviours and associated motivations is relatively limited (Gebhardt et al., 2016). Interactions between modes remain poorly understood since each mode of transport is most often analyzed independently. Furthermore, methods for quantifying multimodality are needed to inform policy makers (Diana & Pirra, 2016). Therefore, this paper aims at highlighting and measuring dependencies between modes of transport at the individual level. To this end, the daily travel diaries collected in the 2013 regional household survey of Montreal (Canada) were harnessed. Several indicators were first developed to assess the diversity of use of different modes of transport (“modal variability”) of each respondent in the weighted sample of data. Based on these indicators, a latent class cluster analysis was then conducted to identify different patterns of multimodal travellers. Moreover, various socio-demographic attributes were tested in the model to predict class membership. In this way, this paper provides a better understanding of multimodal mobility behaviours in urban transportation.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 10p
  • Monograph Title: Planning in Times of Unprecedented Change and Uncertainty

Subject/Index Terms

Filing Info

  • Accession Number: 01877214
  • Record Type: Publication
  • Source Agency: Transportation Association of Canada (TAC)
  • Files: ITRD
  • Created Date: Mar 27 2023 9:33AM