A Study On Intercity Transport Mode Choice Based On Rank Logit And Fusion Data Model

Intercity transport is growing more crucial in urban development, which plays a significant role to support economic development and to improve people’s livelihoods. Optimization of intercity transport modes spilt is a key point for economic development and efficient use of resource. Meanwhile new policies and operation strategy from optimization can reduce conflicts of different modes to pursue benefit maximization. Especially after a huge funding from economic stimulus program of central government, China has developed the world’s longest High Speed Rail (HSR) network. Mode market share changes dramatically with the new mode. HSR brings more competition to airplane in long distance travel and influence passenger choice of highway transport and common railway in short distance travel. So we analyze the intercity transport mode choice as this aspect.We analyze the mode spilt based on Logit model. This paper starts with a brief introduction of Logit model and survey theory, and then demonstrates Rank logit model and its advantage based on the rank survey choice. To cover the shortage of single RP or SP data, we combine the RP data and SP data with fusion data model. This is followed by algorithm test in different utility function of fusion data Rank Logit model. The results indicate that linear utility function and Box-Cox utility function have better fitness.To analyze the modal share of intercity passenger transportation modes, we design travel mode choice survey and collected data from passengers on Guangzhou-Wuhan corridor. We conducted the survey at Guangzhou HSR station, Guangzhou airport and Guangzhou railway station in May,2011.300valid Revealed Preference survey (RP) and297valid Stated Preference survey (SP) samples of307were obtained. In survey we require passengers to rank the modes with the choice probability so that we can build Rank Logit model rather than Multinomial Logit model. Taking trunk time, trunk fee, feeder time and feeder time into consideration in the model, results indicate passengers care more about feeder time and fee rather than trunk information. Finally we test10policy scenarios by developing mode choice model to finish sensitive analysis. The scenarios include policy changes such as speed-down or price discount, and operation changes like picking bus service or highway to station opening. The model assesses the changes as the aspect of market share. Our findings prove the discount war earn little from the market. Providing more service or changes in feeder travel is suggested and effective.