Passenger Transfer Research Articles

Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow

To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed. Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified. Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow. Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input. Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established. Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy. The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.

Day-to-day market evaluation of modular autonomous vehicle fleet operations with en-route transfers

This study extends the two-sided day-to-day learning framework to simulate the performance of a mobility service using modular autonomous vehicles (MAVs) capable of en-route passenger transfers. An insertion heuristic is used to assign trips to a fleet of vehicles and to determine whether engaging in an en-route transfer is advantageous. The operator acts as an endogenous decision maker, updating the relative weight of the operator cost and user cost within the routing algorithm after each simulation day to optimize profit. Real transit ridership data from the United Arab Emirates are used for an empirical study of three operating strategies: door-to-door service within an urban core, commuter first/last mile service and a hub-and-spoke service. Results are compared with and without en-route transfers to quantify the advantage of the en-route transfer capability for each strategy.

Multistation coordinated and dynamic passenger inflow control for a metro line

Passenger inflow control is an efficient way to relieve peak passenger flow and reduce security risks in metro networks. However, station operators develop passenger inflow control strategies independently, thus ignore the interactions among stations and lines in the actual operation. Subsequently, the single-fixed control intensity usually fails to satisfy dynamic temporal passenger demand, resulting in great stranded passengers. To address this problem, a coordinated and dynamic inflow control method is proposed to generate an optimal demand-driven control pattern in metro systems. First, a mixed integer programming model with the concept of the equivalent time interval is formulated to minimise the total number of stranded passengers on one line. Second, special consideration is paid to the transfer passengers with the aim of ensuring the safety of transfer stations. Finally, an actual passenger flow and train operation data in Beijing Batong line is conducted to test the performance of the approach. Compared with the non-coordinated and dynamic inflow control method, results show that the proposed model can balance the utilisation of transportation capacity and reduce the total number of stranded passengers by 20.6%. Sensitivity analysis results indicate that both transportation capacity and transfer capability are the main factors affecting the inflow control.

Scheduling synchronization in urban rail transit networks: Trade-offs between transfer passenger and last train operation

The scheduling synchronization problem in this paper is to obtain an optimal schedule by optimizing running time, departure time, dwell time and arrival time of the last train in urban rail transit networks. Operators are often faced with multiple conflicting requirements simultaneously such as high passenger’s service quality and less cost, smooth transfer events and less passenger’s travel time, and high accessibility and less operation time. Thus, researchers in this industry concentrate on utilizing operations and management decisions to solve the scheduling problem while balancing the service trade-offs. In this paper, we formulate a mixed integer programming approach for the last train schedule planning, and passengers benefit from smoother transfer in the form of maximizing the transfer synchronization events, while operators simultaneously can benefit with lower operation costs by minimizing the worst big difference between last trains. We propose an improved non-dominated sorting approach embedded in a genetic algorithm to obtain close-to-optimal solutions in a much shorter time for a sophisticated, real-world and large-scale Beijing subway network. Results demonstrate that significant service performance gains (76.33% for Just-missed, 32.01% for successful transfer, 15.39% for non-equity for last trains and 45.25% for variance indicators, etc.), which indicate the effectiveness of the proposed modeling framework and solution algorithm. The operator formulates an efficient schedule for the actual operation of the urban rail transit network by the proposed application method, and it also would be applicable to solving schedule problems among a large-scale network in other industries.

Research on the integration of rail transit and conventional public transport—Taking Chongqing as an example

In order to achieve the urban development pattern led by rail transit and give full play to the role of rail transit, it must rely on the connection of conventional public transport. In this paper, the integration of urban rail transit in Chongqing is discussed from six aspects: bus stop, bus terminal, bus line network, transfer passenger flow, stop and go point and convenient service facilities. Based on the in-depth analysis of the current problems, combined with the requirements of existing integration standards and actual conditions, the improvement plan, implementation plan and construction mechanism are proposed Face.

Optimising flight connection times in airline bank structure through Simulated Annealing and Tabu Search algorithms

In hub and spoke airline networks, flight arrivals and departures generally have a bank structure to increase connections among spoke cities through a hub airport in order to provide cheaper service for higher volumes of air traffic. In this study, we introduce the airline bank optimisation problem with a novel mathematical model for improving flight connection times. The mathematical model aims to minimise the total connection times for transfer passengers and generates flight schedules regarding slot capacities in the hub airports. Since the problem is a combinatorial optimisation problem NP-hard and computational complexity increases rapidly for real-world problems, we employ the simulated annealing and the tabu search algorithms to achieve better solutions in a reasonable time. We generate sub-problems using real-world data and investigate the effectiveness of the algorithms. Finally, we present the results of a real case study of a Turkish airline company which has a hub airport connecting the flights between Middle Eastern and European cities.

APPLICATION OF PASSENGER FLOW ANALYSIS METHODS TO RESTRUCTURING THE PASSENGER TRANSPORT SYSTEM OF THE LEVOBEREZHNY DISTRICT OF MOSCOW

One of the key problems when ensuring the quality of life of residents of large cities of the world is to raise the transport services standards. Among the main aspects of solving this problem is the search for the optimal distribution of flows of personal and ground public municipal passenger transport. In this regard the planning, design, and localization of multifunctional transport interchange hubs (hereinafter – TIH) take on great significance. The experience of their arrangement has received wide acceptance in many countries of the world. In recent years Moscow has also been actively working on the design and construction of TIH; large-scale projects of transport infrastructure facilities construction are being developed. The TIH system should be capable of flexible response to changing transport needs of the population and to their realistic transformation to effectively ensure transport mobility of the population.The objective of the study is to test the passenger flow analysis methods and their application for simulation of the organization and planning of the transport interchange hub in a large district of the city, planning of the route network of municipal passenger transport.The route network of suburban and intercity transport of Northern Administrative District of Moscow has been reviewed. The passenger traffic within the TIHs Rechnoy vokzal and Khovrino has been analyzed.Based on the study, the authors propose to change the route network of ground urban passenger transport. The implementation of route network changing proposals can shorten the time spent on passenger travel and transfer. It is the authors’ opinion that the developed route network is more effective than the existing one and meets the design standards and requirements approved by local city regulations.

The development of long-haul low-cost networks in the North Atlantic airline market: An exploratory data approach

For almost two decades, discussion in the literature has continued regarding the viability of the long-haul low-cost carrier (LHLCC) business model in the North Atlantic market. From 2015 onward, LHLCC operations gained some steam, mainly due to the expansion of Norwegian's North Atlantic network. A detailed analysis of the traffic developments on the North Atlantic shows that LHLCCs have a tendency to operate on parallel routes while serving an aggregate North Atlantic network that is less seasonal than that of full-service network carriers (FSNCs). In addition, analysis of passenger flows shows that Norwegian's North Atlantic flights from its Scandinavian bases and, to a lesser extent, from London Gatwick carry substantial shares of transfer passengers. Furthermore, both in the North Atlantic market as a whole and in specific individual city pair markets there are signs that the entry of LHLCCs has a positive impact in terms of competition. Strategic responses by FSNC incumbents can be detected as well. For example, British Airways shows a larger increase in traffic (both in seats offered and in flight frequency) on routes contested by Norwegian than on North Atlantic routes not contested by Norwegian. Next to that, the British flag carrier is able to substantially undercut Norwegian's air fares on most of its contested routes. All in all, after more than a decade of EU-US and EU-Canada Open Skies agreements LHLCC operations on the North Atlantic are dominated by a single airline in financial dire straits. As a result, the long-term viability of the LHLCC business model on the North Atlantic is not a fait accompli yet.

Timetable optimization of high-speed railway hub based on passenger transfer

Timetable optimization of high-speed railway hub based on passenger transfer

Delay propagation cellular automata model based on max-plus algebra for robustness evaluations of non-periodic train operation plans

Based on discrete-event dynamic system theory, train operation events in high-speed railway transportation systems are regarded as the basic elements of these dynamic systems. For non-periodic timetable railways in China, based on a max-plus algebra method, a delay propagation cellular automata model is proposed to evaluate the robustness of high-speed train operation plans. The cellular automata evolution rules that can reproduce the delay propagation state of trains mainly consider train safety headway constraints, passenger transfer constraints, and electric multiple unit (EMU) connection constraints. A simulation analysis of actual cases is performed. The simulation results show that the model can be used to evaluate the robustness of the train operation plan. The numerical results show that in the preparation of train operation plans, the proposed model can predict which trains have significant influences on delays in advance and improve the possibility of reducing the occurrence of delays to maintain high-quality service.

First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction

This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.

Bilevel programming model and algorithms for flight gate assignment problem

ABSTRACTConsidering the decision-making requirements of airport, airlines and passengers, a bilevel programming model which contains two parts was proposed in this paper. One part is to improve the utilization of gates of the airport (upper level), so the objective function of the upper level to the minimum overall variance of slack time between two consecutive air crafts at the same gate. The other part looks at maximize the airline revenue and passengers more conveniently and comfortably (lower level). The lower level has two objective functions — the minimum passenger transfer failure and the minimum passenger average transfer time, respectively. According to the latest data of an airport in Eastern China, the adaptive genetic algorithm is used to solve the above-mentioned bilevel optimisation problems. The numerical experiment shows that the model not only reduces the variance of the relaxation time, but also optimises the flight gate allocation and achieves the initial goal.

Simulation-based assessment methodology to improve ground service operations at a hub airport

ABSTRACT Airport terminals are dynamic environments and security/passport services generally constitute costly bottlenecks in terminals. Increases in the number of airline passengers compels airport terminals to provide more efficient services to its customers under space and resource limitations. This study examines the level of service of passenger processes at Istanbul Atatürk Airport by constructing a comprehensive simulation model. It focuses mainly on passport control services and passenger transfer security services because of the airport's hub status and the strategy of Turkish Airlines. The increasing number of transfer passengers may cause disruptions in departure flight schedules due to slow passenger processes. After validating the model, we investigate the consequences of three main alternative solutions, including 17 sub-scenarios, to capture target quality levels. Finally, we provide the results for each scenario to investigate the optimum allocation of resources to terminal operations.

A trade-off method for timetable rescheduling considering transfer connections in subway networks

This study is devoted to handle disturbances occurring in a subway network during the off-peak period. By dissecting the relationship of transfer connections between connected lines, transfer passengers and non-transfer passengers as well as operating agencies are taken into consideration, respectively, and a trade-off method for timetable rescheduling is proposed to minimize the waiting time of all transfer passengers as well as the deviation from the planned timetable. We adopt the [Formula: see text]-constraint method to convert the bi-objective model to an integer linear programing model with single objective, which can be solved by CPLEX within seconds. The method is validated by some numerical experiments based on a real-world case derived from the Beijing Subway network. Results show that the proposed method is able to generate approximate Pareto optimal solutions and to provide decision support for dispatchers.

Optimizing flight equencing and gate assignment considering terminal configuration and walking time

Operating airline hub-and-spoke networks (HSN) rather than direct flights among city pairs may significantly reduce supplier cost; however, passengers' travel time may significantly increase due to increased transfer and in-flight time. The costs considered in this study are hub-related and incurred by passengers and aircraft (i.e., passenger transfer, flight dwelling, and gate occupancy). The objective is to minimize the total cost by optimizing flight sequence (i.e., arrivals and departures) and gate assignment, while considering transfer speed, transfer demand, flight size, gate size and terminal configuration. A real-world HSN whose hub airport (HA) is located at Xianyang International Airport (XIY) in Xi'an, China is analyzed. The optimized solutions and their relations to various model parameters are explored.

Service replanning in urban rail transit networks: Cross-line express trains for reducing the number of passenger transfers and travel time

Reducing the number of transfers and improving the operating speed are key factors in enhancing the competitiveness of urban rail transit (URT) systems. This paper proposes an integrated optimization with tactical cross-line planning and an operational express train mode to fully utilize line capacities and reduce the total trip time without additional operating costs and investments. In this paper, a new mixed integer non-linear programming (MINLP) model is proposed for systemically exploring the benefits of cross-line express trains to achieve both passenger travel time and operation cost savings; in this model, the frequencies, stopping patterns and operation zones of cross-line express trains and local trains are simultaneously optimized. The characteristics of same-line trips (SLT) and cross-line trips (CLT) under various stopping patterns are investigated. Additionally, a genetic algorithm (GA) is developed based on the MINLP model. Finally, the effectiveness of the proposed model and heuristic algorithm is verified through a set of real-life instances based on the Beijing URT network. The results show that the number of transfers can be reduced by 78%, with a 3.34% savings of travel time and a 4.66% savings of operating costs, when the cross-line express operating mode is properly adjusted.

Walking Time Distribution of Transfer Passengers Based on Proportional Hazard Model

Walking time distribution of Transfer Passengers is the theoretical basis for studying passengers’ transfer behaviour characteristics, for specific passengers transfer, transfer distance is the main factors affecting passengers transfer walking time. The Proportional Hazard Model (PHM) is adopted to analyse the impact of transfer distance on walking time of transfer passengers. To verify the applicability of PHM in walking time distribution, the sampling method which is characterized by fixed time, sex ratio and age proportion is created to infer transfer walking time distribution. Five transfer stations of Beijing subway are selected to conduct the numerical experiment. Through the analysis of 5 channel samples, the probabilities of passenger transfer walking time follow the logarithmic normal PHM (LNPHM). It is shown by regression analysis that there is mathematical relation among the passenger flow impact level, the average passengers’ walking time and the transfer distance.

A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules

Precise estimation of passenger spatial-temporal trajectory is the basis for urban rail transit (URT) passenger flow assignment and ticket fare clearing. Inspired by the correlation between passenger tap-in/out time and train schedules, we present a method to estimate URT passenger spatial-temporal trajectory. First, we classify passengers into four types according to the number of their routes and transfers. Subsequently, based on the characteristic that passengers tap-out in batches at each station, the K-means algorithm is used to assign passengers to trains. Then, we acquire passenger access, egress, and transfer time distribution, which are used to give a probability estimation of passenger trajectories. Finally, in a multi-route case of the Beijing Subway, this method presents an estimation result with 91.2% of the passengers choosing the same route in two consecutive days, and the difference of route choice ratio in these two days is 3.8%. Our method has high accuracy and provides a new method for passenger microcosmic behavior research.

Estimation of passenger waiting time using automatically collected transit data

Among the many ways to improve a transit system is a reduction in travel time as experienced by the passenger. Hence, passenger waiting times remain a topic of interest among transit planners. In this study, the effects of transit vehicle delays on passenger waiting time is investigated, as well as the effects of transfer status, boarding location, time of day, and rider travel frequency. The data used in this study were collected using automatic fare collection (AFC) and automatic vehicle location (AVL) technology. A trip chaining algorithm is used to infer the trajectory of each passenger, and as a result produce measures of passenger waiting time and vehicle delay. An analysis of an arterial Bus Rapid Transit (aBRT) line in Saint Paul, Minnesota reveals a waiting time model consistent with previous literature, a positive relationship between vehicle delay and passenger waiting time, and an insignificant relationship between transfer status and passenger waiting time. Finally, a simple model relating waiting time and vehicle delay is provided for the purpose of transit planning and waiting time estimation.

An integrated optimization model of metro energy consumption based on regenerative energy and passenger transfer

Energy consumption by metro trains has attracted considerable attention due to economic and environmental concerns. Passengers want convenient travel that takes less time. Based on the requirements of reduced train costs and more passenger comfort, the train control strategy and time parameters need to be adjusted properly. This paper proposes an integrated method for the minimum energy consumption of metro trains and minimum transfer waiting time cost for transfer passengers. First, we used a four-stage control strategy to optimize the train trajectory and generated a power matrix. Then, a tab encoding method was established for the regenerative energy calculation on the basis of the power matrix. To obtain the transfer waiting time of passengers, an arrival time matrix was built that was inspired by the matching operation of the regenerative energy. The genetic algorithm was employed for optimization because of its good searching ability, and the matrix form in this model was suitable for computer programming. Finally, two metro lines from the Nanning rail transit system were selected for the case study. The results show that the proposed method has good efficiency for energy conservation and decreased the transfer waiting time between two metro lines. Further research can be conducted by considering more kinds of passengers from the travel flow in the future.