A Direct Demand Model of Departure Time and Mode for Intercity Passenger Trips

Travel demand is well announced as a crucial component of transportation planning. This paper aims to develop a direct demand model, denoting a more acceptable abstraction of reality, for intercity passengers in daily work and leisure trips in Tehran province. The model utilizes combined estimation across the data source, collected in 2011, of travelers originating from the city of Tehran and heading toward two destination clusters: intra-province and inter-province. The paper sketches a way to predict simultaneous choice of departure time and travel mode under the influence of zonal (origin, destination, and residence), individual and household socio-demographic, and trip-related variables. The time frame for analysis of departure time is [5-19] and available modes are auto, taxi, bus, and metro. Multinomial Logit (MNL) and Nested Logit (NL) models as behavioral models are selected from discrete choice family to provide appropriate direct demand structure. Besides, the paper discusses Independent Irrelative Alternative (IIA) assumption of the models and demonstrates choice order of NL; Travelers choose departure time prior to mode at first level and then decide on mode at second level. Finally, travel demand elasticity and marginal effect with respect to travel time, age, and auto cost are also highlighted.