Search Results (5)

In the transportation organization optimization of high-speed railway (HSR), optimizations such as line planning, ticket pricing, and seat allocation are generally studied separately. However, in reality, when passengers choose trains, they need to consider multiple factors such as train routes, stop plans, seat prices, seat availability, and departure times. Therefore, there is an urgent need for an integrated optimization method to simultaneously make decisions regarding these multiple factors. This study constructs a nonlinear optimization model of line planning integrating differentiated pricing and seat allocation decisions for HSR under elastic demand. To efficiently solve the model, an improved heuristic algorithm based on the simulated annealing framework combined with a linear passenger flow allocation method is proposed. Finally, case analysis proves that the improved algorithm can effectively solve the model under the input conditions of an actual Y-shaped HSR network composed of 13 stations, with a potential for a 106.54% improvement from the initial solution to the final solution. The uniqueness of our study lies in the joint optimization of three critical HSR operations, which has not been comprehensively explored in prior studies and is of great significance for improving the level of HSR train operations and passenger services. Full article

Busy, complex railway stations that serve as origin and termination points for a significant proportion of trains are essential to regional railway networks. Resolving conflicts between arrival–departure operations and shunting operations of cross-line trains and originating or terminating passenger trains in the throat area is important for safety in these multidirectional stations. The main task of this paper is to study the train platforming problem, and we consider the integration of track and route allocation with shunting route allocation on the basis of the traditional TTP problem, so as to formulate a strong anti-interference track allocation plan for busy, complex railway stations. Therefore, in view of the complex characteristics of train operation in busy, complex railway stations, we extensively examine the technical operational characteristics of various trains in multidirectional stations, which are the key constraints of the model, and establish a mixed-integer linear programming model. This model aims to balance the buffer time for track occupation and optimize the routing and scheduling of trains in stations. Furthermore, an improved genetic algorithm is proposed to effectively implement the developed model. In the case study of Guangzhou Station, the occupation analysis after the optimization of the method in this paper indicates that the shunting operations significantly interfere with arrival–departure operations in throat areas. The optimization of buffer times and track utilization times resulted in notable reductions of 30.55% and 77.82%, respectively, in quadratic differences. These outcomes provide empirical evidence supporting the feasibility of the proposed model and algorithm for addressing train platforming problems, particularly in complex, multidirectional, and heavily trafficked railway stations. Full article

Travel mode selection is a crucial aspect of traffic distribution and forecasting in a comprehensive transportation system, which has significant implications for resource allocation and optimal management. As commuters are the main part of urban travel, studying the factors that affect their choice of transport mode plays a crucial role in urban traffic management and planning. Based on public transport operation data, a travel chain is created by identifying boarding stations, alighting stations, and transfer behaviors, and includes detailed travel information. The regression and correlation coefficients of departures and arrivals at stations are confirmed to be 0.98 and 0.92 in the presented data, indicating the viability of the recognition method. Then, multiple travel modes are identified based on the origin and destination, and the proportion of mode selection is determined by the actual travel chain. Using maximum likelihood estimation (MLS) and NLOGIT software, the random parameter logit (RPL) mode is used to estimate the relationship between travel mode selection and characteristic variables such as travel time, distance, cost, comfort, walking distance, and waiting time. The results indicate that walking distance, travel distance, and comfort have a greater influence on travel choice, and that walking distance is a random parameter with a normal distribution, reflecting the diversity of commuters. In addition, this paper discusses the influence degree of the change of characteristic variables of a transport mode on the choice between it and other modes. These results can be used as reference for relevant departments to make measures to improve the overall efficiency of the urban transportation system. Full article

At the peak of passenger flow, some passengers extend travel sections, which will be likely to lead to overcrowding of high-speed railway (HSR) trains. Therefore, the problem of train overcrowding control needs to be considered in ticket allocation. Firstly, by simulating the passenger demand function and utility function, an optimization model of ticket allocation for multiple trains and multiple stops with the goal of maximizing revenue is constructed. Secondly, the concepts of the travel extension coefficient and risk coefficient are introduced, the number of passengers is estimated under the risk coefficient as the probability, and the total number of passengers on the train arriving at any station is obtained. Thus, preventing the number of passengers on the train from exceeding the train capacity is introduced to the ticket allocation optimization model of multiple trains and multiple stops as a constraint. Finally, this model is solved by the particle swarm optimization algorithm (PSO). The research results show that the idea of controlling passenger numbers so as not to exceed train capacity based on ticket allocation proposed in this paper has strong practical feasibility. By reasonably and accurately allocating the tickets to the departure terminal section and long-distance terminal sections, it can ensure that, even if there are some passengers extending their travel section, the train will not be overcrowded under a certain probability, improving the train safety and passenger travel experiences. Full article

As a result of transportation integration, the role of highway passenger transport hubs has changed dramatically; these nodes act as important links to construct a seamless regional comprehensive passenger transport system which reflects the coordination and symmetry of public transportation and the integrated transportation system. In order to optimise the efficiency of transportation organisation and improve the quality of passenger transport services, in this study we developed an optimisation method for the allocation of passenger transport hubs based on the analysis of passenger flow demand and spatial distribution. Configuration models of the departure sites of single-station and multi-station hub lines were established according to the service scope of the stations and the relative generalised travel cost, respectively. The overall optimisation method of the route allocation scheme was proposed by checking and optimising the passenger volume of each station. The developed methodology was successfully validated by applying it to the highway passenger transport hub system of Nanjing, China. The proposed methodology is expected to help management agencies and business operators to optimise existing highway passenger bus lines, thereby improving the quality of their services. Full article