Modeling parking choices considering user heterogeneity

Abstract. The examination of car driver behavior deciding which parking space to choose. The application of various logit models has led to an insight of selecting between the available alternatives: free on-street parking, paid on-street parking and parking in an underground car park. Several logit models allowing for correlation between random taste parameters calculate coefficients using stated choice data. The main purpose of this paper is to extend a Mixed Multinomial Logit (M-MNL) model to similar models which can also implement the correlation between random parameters. This leads to the following: Nested Logit (NL), Nested Generalized Extreme Value (NGEV), Cross-Nested Logit (CNL) and Mixed-Mixed Multinomial Logit (MM-MNL) models to approach modeling parking choice models. The estimated coefficients are used to compute subjective-value of time (SVT) when looking for a parking space.