SHORT. This paper deals with mode choice behaviour for extra-urban journeys, with several approaches: Dogit, Box-Cox transformation, Cross-Nested Logit or Probit, as well as ANN as benchmark. Results of applications to real test-sites will be presented. LONG. This paper deals with the simulation of mode choice behaviour for extra-urban journeys. They are generally home-based, and the mode choice behaviour is greatly affected by user socio-economic characteristic, whilst the effect of level of service (LoS) attributes can be significantly non-linear, and a relevant fraction of users may be captive to a specific mode. Moreover, the zoning as well as the access and egress to the transit system can often be modelled only at an aggregate level, due to data availability. Finally, the structure of dispersion matrix among the perceived utility may likely be quite complex also due to unusual modes, such as car-pool, dial-a-ride, …. . These considerations are not in favour of models used for urban journeys, which turn out quite rigid with respect to LoS attributes, and are often greatly determined by alternative specific attributes (ASA) when applied to extra-urban journeys. This paper follows a random utility approach and focuses on the effects of hypotheses and data on the efficiency (how satisfactorily the real phenomenon is simulated) of the resulting model as well as its effectiveness (how easy to use the model is, and which data it requires). The Dogit model will be used to simulated user captivity to any alternatives, and Box-Cox transformation to test non-linearity of utility with respect to LoS attributes, whilst Cross-Nested Logit or Probit models to allow complex structures of the dispersion matrix. Spatial ASA will be adopted to avoid detailed zoning and access and egress representation. Some indices will also be presented and discussed to compare model effectiveness. The effectiveness will also be tested against artificial neural network models as a benchmark. Results of applications to real test-sites will be presented to support general considerations.

Modelling choice behaviour for intercity journeys

CANTARELLA, Giulio Erberto;DE LUCA, STEFANO
2002-01-01

Abstract

SHORT. This paper deals with mode choice behaviour for extra-urban journeys, with several approaches: Dogit, Box-Cox transformation, Cross-Nested Logit or Probit, as well as ANN as benchmark. Results of applications to real test-sites will be presented. LONG. This paper deals with the simulation of mode choice behaviour for extra-urban journeys. They are generally home-based, and the mode choice behaviour is greatly affected by user socio-economic characteristic, whilst the effect of level of service (LoS) attributes can be significantly non-linear, and a relevant fraction of users may be captive to a specific mode. Moreover, the zoning as well as the access and egress to the transit system can often be modelled only at an aggregate level, due to data availability. Finally, the structure of dispersion matrix among the perceived utility may likely be quite complex also due to unusual modes, such as car-pool, dial-a-ride, …. . These considerations are not in favour of models used for urban journeys, which turn out quite rigid with respect to LoS attributes, and are often greatly determined by alternative specific attributes (ASA) when applied to extra-urban journeys. This paper follows a random utility approach and focuses on the effects of hypotheses and data on the efficiency (how satisfactorily the real phenomenon is simulated) of the resulting model as well as its effectiveness (how easy to use the model is, and which data it requires). The Dogit model will be used to simulated user captivity to any alternatives, and Box-Cox transformation to test non-linearity of utility with respect to LoS attributes, whilst Cross-Nested Logit or Probit models to allow complex structures of the dispersion matrix. Spatial ASA will be adopted to avoid detailed zoning and access and egress representation. Some indices will also be presented and discussed to compare model effectiveness. The effectiveness will also be tested against artificial neural network models as a benchmark. Results of applications to real test-sites will be presented to support general considerations.
2002
0-86050-340-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/1659273
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