Abstract
Studying the interaction between demand forecasting and train stop planning is important, as it ensures the sustainable development of high-speed rail (HSR). Forecasting the demand for high-speed rail (HSR), which refers to modal choice or modal split in this paper, is the first step in high-speed rail (HSR) planning. Given the travel demand and the number of train trips on each route, the train stop planning problem (TSPP) of line planning involves determining the stations at which each train trip stops, i.e., the stop-schedule of each train trip, so that the demand can be satisfied. To integrate and formulate the two problems, i.e., the modal choice problem (MCP) and train stop planning problem (TSPP), a nonlinear model is presented with the objective of maximizing the total demand captured by a high-speed rail system. To solve the model, a heuristic iterative algorithm is developed. To study the relationship between the demand and the service, the Beijing–Shanghai high-speed rail (HSR) corridor in China is selected. The empirical analysis indicates that combining modal choice and train stop planning should be considered for the sustainable design of high-speed rail (HSR) train services. Furthermore, the model simulates the impact of the number of stops on its mode share by reflecting changes in travelers’ behaviors according to HSR train stop planning, and it also provides a theoretical basis for the evaluation of the adaptability of the service network to travel demand.
Highlights
As an emerging transportation mode, high-speed rail (HSR) has attracted attention from passengers and operators due to its rapidity, safety, and comfort when compared to other modes
We present our integrated model for the modal choice and train stop planning problem (MC-TSPP)
Passenger flow variable specifying the number of passengers from station p to station q that is served by train trip g on route r, which depends on the stop-schedule variable
Summary
As an emerging transportation mode, high-speed rail (HSR) has attracted attention from passengers and operators due to its rapidity, safety, and comfort when compared to other modes. For the sustainable development of both high-speed rail and travel demand, demand forecasting, travel behavior or modal choice, must be integrated into the train stop planning dependsincluding on the HSR train services provided. An integrated model for the modal choice train stop planning problem (MC-TSPP). All abbreviations used in this paper are summarized in Table the stop-schedule plan for HSR train trips. Traditional rail algorithm is proposed, and (3) a detailed analysis of travel behavior and train services is provided. The contributions of this paper are as follows: (1) an integrated model simultaneously considering mode choice and train stop planning is presented, (2) a decomposition-based heuristic iterative algorithm is proposed, and (3) a detailed analysis of travel behavior and train services is provided.
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