Abstract
Under the condition that ticket fare for high-speed train could fluctuate around a benchmark price in China, aimed at predicting how the passengers will distribute among different trains given a ticket fare, the passenger flow assignment method for high-speed trains is studied. Different from the classical researches on the passenger flow assignment, by introducing a variable that represents the value of time, this research allows passengers to make their personalized choice between the principles of time minimization and expense minimization, so as to demonstrate how the passengers holding different time values respond to each ticket fare scheme. An equilibrium passenger flow assignment model based on personalized choice is built and an improved Monte-Carlo random simulation algorithm is designed for solving the model. The actual ticket sale data for Beijing-Shanghai high-speed railway are used to verify the feasibility of the proposed model and algorithm. The passenger flow assignment results under various fare schemes show how the distribution of passenger flow changes with the adjustment of ticket fare.
Highlights
China’s high-speed train has achieved tremendous results during the last decade, passenger flow is generally unevenly distributed between trains due to different departure and arrival time, travel time, and stopping schedule. e published prices of high-speed train tickets may be properly adjusted based on actual demands to effectively regulate passenger flow distribution among trains, enhance resource utilization, and increase transport enterprises’ revenues
After the continual iteration and feedback between ticket fare adjustment and passengers’ itinerary choice, an optimal fare scheme is eventually formulated to meet the needs of both transport enterprises and passengers. erefore, passenger flow assignment at a certain ticket fare is a key link in adjusting and optimizing ticket fare
On the basis of the theory and method of traffic flow distribution for urban roads [1, 2], China’s scholars studied passenger flow assignment for railway network, aiming to evaluate and optimize operation schemes [3,4,5]. It is a spatial transfer network based on operation schemes
Summary
China’s high-speed train has achieved tremendous results during the last decade, passenger flow is generally unevenly distributed between trains due to different departure and arrival time, travel time, and stopping schedule. e published prices of high-speed train tickets may be properly adjusted based on actual demands to effectively regulate passenger flow distribution among trains, enhance resource utilization, and increase transport enterprises’ revenues. On the basis of the theory and method of traffic flow distribution for urban roads [1, 2], China’s scholars studied passenger flow assignment for railway network, aiming to evaluate and optimize operation schemes [3,4,5]. In some researches, it is a spatial transfer network based on operation schemes. A time-fare bi-criteria equilibrium passenger flow assignment model was proposed in this paper based on passengers’ personalized itinerary choice and transport features, and an improved MonteCarlo random simulation algorithm was designed to solve the model. The actual data of Beijing-Shanghai highspeed railway were introduced to verify the proposed method, based on which how passenger flow distribution changes with the adjustment of ticket fare is discussed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
