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A tri-level Nested Logit choice model was developed to optimize regional transportation corridors allocation. From the perspective of users and by applying hierarchical ideas, uncertain programming theory and random utility theory, the traffic mode choice in corridors was discussed. Taking Beijing-Shanghai transportation corridor for instance, the model parameters were calibrated by using the Beijing-Shanghai maglev transit passenger forecast survey and other supplementary traffic survey data, and the rationality of the model was validated. Results show that the model could overcome the defects of Multinomial Logit Model and be a promising approach to improve the structure configuration of transportation modes in regional transportation corridors. [ABSTRACT FROM AUTHOR]

To get the volume forecasting method which can reflect the mechanism of regional transportation demand characteristics, and considering the limited data of regional transportation volume and the stochastic and uncontrollable of the inducing factors, a rolling forecasting model of regional transportation volume was developed based on the Support Vector Machine and the analysis of the characteristics of regional transportation demand and the defects of existing forecasting methods. Through continuous interaction between predictive value and statistical value to update the training samples, the model realized the rolling forecasts of the regional transportation volume, and avoided the process of establishment and calculation of the nonlinear function. Taking the transportation volume of Beijing - Tianjin - Hebei area for instance, the rationality of the model has been validated and the results indicate that the model enhances the forecasting accuracy of regional volume, and has better prospects. [ABSTRACT FROM AUTHOR]