Schedule-Based Passenger Assignment for High-Speed Rail Networks considering the Ticket-Booking Process

Su, Huanyin; Shi, Feng; Xu, Guangming; Qin, Jin; Shan, Xinghua

doi:10.1155/2016/1650839

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…Hamdouch et al [25] proposed a schedule-based transit assignment model with travel strategies and loaded passengers on a first-come-first-served basis. However there are big differences between the urban transit systems and high-speed rail systems, which have been analyzed in detail by Su et al [26]. Considering the features of high-speed rail systems, Su et al [26] proposed a schedule-based passenger assignment method for high-speed rail networks by simulating the ticket-booking process, which can be used for a reference in this article.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A passenger assignment method can be constructed by simulating ticket-booking process because passengers' choices of trains are determined in this process [26]. As the ticket-booking process continues, some train legs become fully occupied and the alternative trains for the subsequent passengers' booking requests change.…”

Section: Passenger Assignment Considering Departure Periods and Capacity Constraintsmentioning

confidence: 99%

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Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

Peng

Deng

et al. 2021

Mathematical Problems in Engineering

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Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients ( ϕ ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ , increasing by 7%–21%.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Passenger Assignment Considering Departure Periods and Capacity Constraintsmentioning

confidence: 99%

Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

Peng

Deng

et al. 2021

Mathematical Problems in Engineering

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“…These features are essential differences from other public transit networks. Based on the above features, Su and Shi et al [20] proposed a schedule-based passenger assignment method for high-speed rail networks considering the ticketbooking process (SPAM-TBP). In the ticket-booking process, as time continues, the number of passengers having booked tickets increases; then some train segments become filled to their capacities and the travel paths with minimum cost change; hence subsequent passengers booking tickets may have to face higher travel costs.…”

Section: Problem Statement and Notationsmentioning

confidence: 99%

A Line Planning Approach for High‐Speed Rail Networks with Time‐Dependent Demand and Capacity Constraints

Tao

2019

Mathematical Problems in Engineering

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In high-speed rail networks, trains are operated with high speeds and high frequencies, which can satisfy passenger demand with different expected departure times. Given time-dependent demand, this paper proposes a line planning approach with capacity constraints for high-speed rail networks. In this paper, a bilevel optimization model is formulated and the constraints include track section capacity per unit time, train seat capacity, and the gap between the number of starting trains and that of ending trains at a station. In the upper level, the objective is to minimize train operational cost and passenger travel cost, and the decision variables include the line of each train, carriage composition of each train, train stop patterns, train start times, and train arrival and departure times at stops in the line plan. In the lower level, a schedule-based passenger assignment method, which assigns time-varying demand on trains with seat capacity constraints by simulating the ticket-booking process, is used to evaluate the line plan obtained in the upper level. A simulated annealing algorithm is developed to solve the model in which some strategies are designed to search for neighborhood solutions, including reducing train carriages, deleting trains, adding trains, increasing train carriages, and adjusting train start times. Finally, an application to the Chinese high-speed rail network is presented. The numerical results show that (i) the average time deviations between the expected departure times and the actual boarding times of passengers are within 30 min, (ii) the unserved passengers are less than 200, and (iii) the average load factors of trains are about 70%. Hence, line plan solutions meet time-dependent demand well and satisfy the capacity constraints for high-speed rail networks.

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“…The rooftop model [37,38] can be described based on the Assumption (A2) and (A3). If there was no itinerary at the time of , he/she would adjust his/her departure time to another itinerary.…”

Section: Rooftop Model and Ticket-booking Process Of Hsr Passengersmentioning

confidence: 99%

Estimation of Time‐Varying Passenger Demand for High Speed Rail System

Wei

Shi

2019

Complexity

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Passenger demand plays an important role in railway operation and organization, and this paper aims to estimate passenger time-varying demand by simulating the ticket-booking process for High Speed Rail (HSR) system. The ticket-booking process of each OD pair can be partition into discrete booking phases by the times when the tickets of any itinerary had sold out. The ticket booking volume of each itinerary is reversely assigned to its corresponding expected departure intervals to obtain the time-varying demand in each booking phase using the rooftop model, and the total time-varying demand are estimated by summing the time-varying demand distributions in all booking phases. Only with the data about the itinerary flow, the precedence relationship is introduced to constrain the ticket sold-out order of all itineraries for each OD pair. Based on the precedence relationships of itineraries, two typical situations are proposed, in which the Single Booking Phase Reverse Assignment (SBPRA) algorithm and the Multiple Booking Phases Reverse Assignment (MBPRA) algorithm are proposed to estimate the time-varying demand respectively. Case analysis on OD pair Beijing-Shanghai are presented, and the validity analysis demonstrates that the error rates of SBPRA algorithm and MBPRA algorithm are 8.64% and 6.37%, respectively.

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Schedule-Based Passenger Assignment for High-Speed Rail Networks considering the Ticket-Booking Process

Cited by 7 publications

References 14 publications

Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

A Line Planning Approach for High‐Speed Rail Networks with Time‐Dependent Demand and Capacity Constraints

Estimation of Time‐Varying Passenger Demand for High Speed Rail System

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