Modelling Route Choice Behaviour in Multi-Modal Transport Networks
infrastructure - station, infrastructure - interchange/transfer, planning - route design, planning - surveys, ridership - modelling, ridership - commuting, ridership - behaviour, place - urban, mode - rail
Travel time, Travel behavior, Transfers, Surveys, Route selection, Route choice, Revealed preferences, Railroad stations, Passengers, Origin and destination, O&D, Netherlands, Multimodal transportation, Multimodal systems, Logits, Logit models, Journey time, Interurban transportation, Intercity travel, Intercity transportation, Generalized extreme value models, Feeder services, Choice models
Few studies on interurban train journeys have models that specifically reflect the route choice behavior of interurban train users. This paper presents findings from model estimations using revealed choice data giving detailed insights into interurban multimodal choice behavior of train users. The study also seeks to determine the influence of trip attributes on the quality and competitiveness of multimodal alternatives. The analysis covers the entire trip from origin to destination, including access and egress legs to and from the train network. The focus is on preferences for different feeder modes, railway station types and train service types as well as on the relative influence of time elements and transfer penalties. Data from dedicated surveys are used including individual objective choice sets of 235 multi-modal homebound trips in which train is the main transport mode. The observed trips have origins and destinations within the Rotterdam-Dordrecht region in the Netherlands with an average total trip time of 50 minutes. Hierarchical nested logit models are estimated to take account of unobserved similarities between alternatives at the home-end and the activity-end of the trip respectively, resulting in two-level nesting structures which differentiate between intercity and non-intercity railway station types at the upper level and between transit and private access modes at the lower level. In order to reflect the multi-dimensional structure of the data, a more advanced so-called multi-nested generalized extreme value model according to the principles of differentiation has been estimated. This significantly improves the explanatory power and stresses the importance of the home-end of the multimodal trip. Findings show that the average traveler attaches different weights to the observable trip resistance attributes.
Bovy, Piet, Hoogendoorn-Lanser, Sascha. (2005). Modelling Route Choice Behaviour in Multi-Modal Transport Networks. Transportation: Planning, Policy, Research, Practice, Volume 32, Issue 4, pp 341-368.