Holiday travel behavior analysis under integrated multimodal travel information service

Abstract

Based on the RP-SP fusion data obtained from the holiday travel behavior survey in 2012, this paper takes the integrated multimodal travel information (IMTI) as the research condition and develops the Nested Logit model under IMTI based on the trip chain complexity and trip mode choices (Chain-Mode). The effectiveness of the model was identified by the inclusive value and dissimilarity parameter. The result shows that 9% of the travelers will cancel their travel in holidays and 13% will change their trip modes under the influence of IMTI. At the meantime, travel cost, parking fee, car ownership, gender, information demand, travel time and trip distance are dominant factors that influence the Chain-Mode choices in holidays. Higher parking fee and longer travel time and trip distance will encourage people to choose a complex chain. Besides, the trip mode with low travel cost and high information demand will have the high probability to be chosen.