Abstract
It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.
Highlights
With the development of city agglomerations and regional economic integration, with the improvement of urbanization and mechanization on transportation, great change is taking place in the connections between cities in the regional area quantitatively and qualitatively
With the conventional four-step method, it is difficult to measure the changes in trip generation due to improved travel conditions, because the conventional trip generation methods are not sensitive to changes in the level of service and are not able to capture the effects of such travel time reductions [1]
Based on the idea of model system construction, the author built an intercity travel demand analysis model system based on disaggregate model
Summary
With the development of city agglomerations and regional economic integration, with the improvement of urbanization and mechanization on transportation, great change is taking place in the connections between cities in the regional area quantitatively and qualitatively. With the conventional four-step method, it is difficult to measure the changes in trip generation due to improved travel conditions, because the conventional trip generation methods are not sensitive to changes in the level of service and are not able to capture the effects of such travel time reductions [1] These models that were taken for urban transportation demand analysis cannot be directly used in intercity demand analysis. He, and Luo conducted the research on intercity split model based on disaggregate model, and they get good results with its application in the projects including passenger volume forecasting for Guangzhou-Shenzhen railway, plan of Beijing-Taiyuan highspeed railway, and plan of Hangzhou external transportation system. Tang and his research team predicted the development direction of urban external travel spatial demand of Longnan city by force model.
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