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Accurate passenger flow forecasting in urban rail transit (URT) could provide a vital reference for operators' timely operation management. However, due to the enormous scale of the metro network, it is unwise to forecast passenger flows at the station scale individually. In this paper, a forecasting framework is proposed for network-scale forecasting tasks considering both accuracy and efficiency. There are mainly three stages in the forecasting framework. Firstly, three kinds of similarity measurements are presented regarding the adjacent similarity, geographic location similarity, and trend similarity. Secondly, three similarity graphs are formed by combining the three kinds of similarity measurements and flow time series. Thirdly, the multigraph network is applied to perform passenger flow forecasting. The experimental results indicated that the proposed method performs relatively accurately for the network-scale prediction with economic time costs. Specifically, the proposed model could acquire the feasible forecasts compared with the best disaggregate model using less than half of calculation costs, and above 10% reduction in root-mean squared error (RMSE) compared with the best aggregate model in the benchmark trials. Extensive contrast experiments were conducted to investigate the sensitivity and interpretability of the proposed model. [ABSTRACT FROM AUTHOR]

Railway disturbance management is inherently a multi-objective optimization problem that concerns both the operators' cost and passenger's service level. This study proposes a multi-objective simulation-based optimization framework to effectively manage the train conflicts after the occurrences of a disturbance caused by a temporary line blockage. The simulation model enhanced with a dynamic priority dispatching rule in order to speed up the optimization procedure. A multi-objective variable neighborhood search meta-heuristic is proposed to solve the train rescheduling model. The obtained Pareto optimal solutions for disturbance management model support the decision maker to find a trade-off between both user and operator viewpoints. The proposed approach has been validated on a set of disruption scenarios covering a large part of the Iranian rail network. The computational results prove that the proposed model can generate good-quality timetables with the minimum passenger delay and deviation from the initial timetable. The outcomes indicate that the developed simulation-based optimization approach has substantial advantages in producing practical solution quickly when compared to currently accepted solutions. Abbreviation: MOVNS: multi-objective variable neighbourhood search; DES: discrete-event simulation; SO: simulation-optimization; AG: Alternative Graph; FCFS: First Come First Served; MIP: mixed integer programming; MILP: mixed-integer linear programming; B&B: branch and bound algorithm; VND: Variable Neighborhood Descent; NSGA-II: Non-dominated Sorting Genetic Algorithm–II; CD: crowding distance; DP: dynamic priority; EDD: earliest due date first; SRTT: shortest remaining traveling time; LST: least slack time first [ABSTRACT FROM AUTHOR]

One of the main infrastructures in rail transportation is metro station. Obviously, analyzing and improving the capacity of the stations will ultimately lead to improved performance of the overall network. The capacity of metro station is the ability of the station and its associated spaces to create safety and comfort for the number of passengers expected to use the station. In this research, volume of passengers in the Shohada Square metro station has been used and simulated using VISSIM software. By the results of the simulation and regarding TCRP manual, six scenarios were analyzed in this research and different conditions were evaluated. Two main solutions for improving the performance of station were considered. It shows that the decision to remove the manual ticket purchase location will result in a 43% improvement in the performance of control space section and the approach to reducing the headway of trains from 240 s to 180 s will increase the amount of accessible space for each pedestrian in the platform to 35%. The method presented in this study can be used to evaluate and analyze other metro stations and even other transportation network stations. [ABSTRACT FROM AUTHOR]

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Abstract The present paper deals with optimizing optimal operation interaction for GCUM 1st and 2nd lines by proposing a methodology based on field survey of travel time, actual headway, passenger waiting time, alighting and boarding passengers to determine the actual passenger density on platform, passenger density in train and target headway, consequently the ideal operation and the corresponding operational costs savers. Using four alternatives (change headway, divide the line into definite links, uses of suitable metro units and overflow of some through stations) under 5 restrictions (Passenger intensity into train, Passenger intensity on platform, Passenger exchange time at metro door, Factor of safety for metro headway and headway at the end of links) and without needing to any additional capital costs, the results show a valuable cost saving for both operation costs and rolling stock capital costs. This paper recommends this methodology to be applied on any metro lines worldwide. [ABSTRACT FROM AUTHOR]

The boarding/alighting process at railway platforms is an important determinant of the railway system performance and depends on the characteristics of passengers, the layout of the platform, and the rolling stock. This research aims to increase the understanding of the process, providing a methodological approach to model the passengers’ behaviour when boarding at railway platforms. Adequate criteria were selected to define the so called “boarding cluster” and an easy mechanism was developed to select the boarding clusters. Passenger flow data collected at Bern railway station in Switzerland was used to test the proposed approach. The results show that (a) the clusters near the doors grow in the longitudinal direction with a rate of 6:1 between the length and width of clusters, and that (b) the growth curves rise quickly when clusters are still small, i.e., at the beginning of the boarding/alighting activity. Further research is needed to extend the validation of the model, considering other variables, such as critical pedestrian densities which occur at specific hot spots near obstacles at platforms. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated discrete-event simulation (DES) using phase-type (PH) distribution and optimization method for the performance assessment, as well as optimal configuration of metro rail transit (MRT) station service facilities. The MRT facilities (including ticket facilities and elevator) are represented as a queuing network system with the passengers’ arrival flow and the service time based on the PH distribution, which considers the flow and service time fluctuation. The necessary performance measures include facility utilization, mean number of passengers and waiting time of passengers in the facilities are obtained by PH-based DES model of service facilities. The model is then coupled with a genetic algorithm that works simultaneously to give the optimal configuration of service facilities. The results of PH-based DES model are first verified by existing PH-based analytical models and then compared with other existing exponential-based and deterministic-based queuing models. The results reveal that increase in squared coefficient of variation of arrival interval causes an increase in the performance measure values and high number of ticket facilities compared to existing models. The existing models therefore underestimate the results. The squared coefficient of variation is an important parameter and cannot be ignored in analysis and design of service facilities. This research provides a more realistic and novel PH-based DES, as well as PH-based simulation-optimization method that will assist the planners and designers of MRT stations to make intelligent decisions regarding analysis and design. [ABSTRACT FROM AUTHOR]

Subway is an important transportation means for residents, since it is always on schedule. However, some temporal management policies or unpredicted events may change passenger flow and then affect passengers requirement for punctuality. Thus, detecting anomaly event, mining its propagation law, and revealing its potential impact are important and helpful for improving management strategy; e.g., subway emergency management can predict flow change under the condition of knowing specific policy and estimate traffic impact brought by some big events such as vocal concerts and ball games. In this paper, we propose a novel anomalies detection method of subway passenger flow. In this method, an improved robust principal component analysis model is presented to detect anomalies; then ST-DBSCAN algorithm is used to group the station-level anomaly data on space-time dimensions to reveal the propagation law and potential impact of different anomaly events. The real flow data of Beijing subway are used for experiments. The experimental results show that the proposed method is effective for detecting anomalies of subway passenger flow in practices. [ABSTRACT FROM AUTHOR]

In order to optimize the passenger flowlines and improve the operation capacity of Zhongchuan high-speed railway station, the simulation model of passenger flowlines is established based on the simulation software of Anylogic. The simulation of the passenger flowlines during peak and off-peak hours of the station are carried out respectively. The organization problems of passenger flowlines during peak hours are found out, and the optimization methods are put forward. The station capacity after optimization is compared with the original by employed the simulation model. The result shows, after optimization, although the walking distance of passengers who are entering the ticket hall to buy ticket is increased but the flowline separation effect is achieved, the flowlines become more clear, the cross interferences are reduced, and the station capacity is increased. [ABSTRACT FROM AUTHOR]

Optimising stopping patterns in railway schedules is a cost-effective way to reduce passengers’ generalised travel costs without increasing train operators’ costs. The challenge consists in striking a balance between an increase in waiting time for passengers at skipped stations and a decrease in travel time for through-going passengers, with possible consequent changes in the passenger demand and route choices. This study presents the formulation of the skip-stop problem as a bi-level optimisation problem where the lower level is a schedule-based transit assignment model that delivers passengers’ route choices to the skip-stop optimisation model at the upper level, and where the upper level in return provides an improved timetable to the lower level. A heuristic method for large-scale urban networks is presented to solve this extremely complex bi-level problem, where the skip-stop optimisation is a mixed-integer problem, whereas the route choice model is a non-linear non-continuous mapping of the timetable. The method was tested on the suburban railway network in the Greater Copenhagen Region (Denmark): the reduction in railway passengers’ in-vehicle travel time was 5.5%, the reduction in passengers’ generalised travel cost was 3.2% and, at the system level, the yearly consumer surplus amounted at 76.7 million DKK (about 10.3 million EUR or 12.7 million USD) when compared to the existing stopping patterns. [ABSTRACT FROM AUTHOR]

This study presents a fuzzy Bayesian network (FBN) method to analyze the influence on the safety risk of railway passenger transport applying different risk control strategies. Based on the fuzzy probability of the basic event determined by the expert group decision method, the proposed FBN method can reasonably predict the probability of railway passenger safety risk. It is also proven that control the risk in the safety management of railway passenger transport will be the most effective way to reduce the risk probability of the railway passenger transport safety. [ABSTRACT FROM AUTHOR]

The direction in research of the efficiency of decision-making units in this paper is an efficient→multi-inefficient→multi-efficient unit. So, the general purpose of this paper is twofold: (1) identification of «hidden» inefficient units within a multi-set, among efficient units of the basic set, and (2) achieving the efficiency in such identified inefficient units. This indicates (warns of!) a negative efficient→inefficient process, so as to provide a timely response and thereby prevent multi-inefficiency. The specific goal is to assess the efficiency of the Serbian railway passenger stations, first within the basic set of the Passenger Transport Section Belgrade, then in the multi-set of the Passenger Transport Sections, and finally in the superset, the Passenger Transport Sector. This is achieved by means of the multi-set DEA (Data Envelopment Analysis) method, which is a system for: (i) relative efficiency assessment, in the first iteration, through the basic set analysis, and (ii) decrease in efficiency of potentially inefficient units, in subsequent iterations, through the multi-set analysis. The result is that the efficient stations Požarevac and Pančevo Bridge are at the initial level, and the (newly) efficient Požarevac, Novi Sad and Inđija at the final level. The best practice station remains the Požarevac Station, which is multi-efficient, and therefore the role model to inefficient stations. The conclusion is drawn that the solution resulting from the multi-set DEA analysis is more realistic, and less relative, because it applies to a wider analysed set of decision-making units, i.e., a larger coverage when considering the issue. This is important for fitting into the new era of growing globalization, and therefore our recommendation is the integral multi-set, as opposed to the individual single set approach. [ABSTRACT FROM AUTHOR]

Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the total, multi-level public transport network and to quantify the societal costs of link vulnerability for these identified links. Contrary to traditional single-level network approaches, we consider the integrated, total multi-level PT network in the identification and quantification of link vulnerability, including PT services on other network levels which remain available once a disturbance occurs. We also incorporate both exposure to large, non-recurrent disturbances and the impacts of these disturbances explicitly when identifying and quantifying link vulnerability. This results in complete and realistic insights into the negative accessibility impacts of disturbances. Our methodology is applied to a case study in the Netherlands, using a dataset containing 2.5 years of disturbance information. Our results show that especially crowded links of the light rail/metro network are vulnerable, due to the combination of relatively high disruption exposure and relatively high passenger flows. The proposed methodology allows quantification of robustness benefits of measures, in addition to the costs of these measures. Showing the value of robustness, our work can support and rationalize the decision-making process of public transport operators and authorities regarding the implementation of robustness measures. [ABSTRACT FROM AUTHOR]

The use of double-unit trains is becoming a common means of increasing passenger capacity for a rail network. However, their expanded usage may create additional aerodynamic challenges. The present work obtains the characteristics of the slipstream caused by single and double unit trains using the detached eddy simulation (DES) method for 1/20th scaled models. The numerical results are verified by full-scale experiments. The slipstream velocities and pressures obtained by the two train models at different distances from the center of track (COT) and the top of rail (TOR) are compared. The coupling structure of the double-unit train model is found to produce a velocity peak that is much greater than that of the single-unit train model in the same position. At the area away from the COT and close to the TOR, the velocity of the far wake region is larger for the double-unit train model. The coupling structure also leads to a positive pressure change in the coupling region, and its value is comparable to or even much greater than that caused by the nose. It is considerable that the subsequent pressure criteria could take the positive pressure on the coupling region into account for the double-unit train. [ABSTRACT FROM AUTHOR]

Introduction This study aims to understand the trip characteristics of private and public transport users in Kuala Lumpur, and the intention of private motor vehicle users to shift to rail transport if available. Method We conducted a travel survey in the corridor of an upcoming mass rapid transit line in Kuala Lumpur. We then analyse the characteristics of the trips recorded from the survey on a weekday and weekend. We used binary logistic regression to find the association between the trip characteristics and the intention to shift from private motor vehicles to rail transport if available. Results There were less than 15% of public transport users among the survey respondents. However, 48% of the weekday trips and 39% of the weekend trips were intended to shift to rail transport if available. Regression for the weekday trips showed that trip duration, distance, purpose, vehicle occupancy, and presence of child passengers were significantly associated with the intention to shift. For weekend trips, only the trip duration and presence of child passengers were significantly associated with the intention to shift. Conclusion This study shows that the population's intention to shift from private motor vehicle to rail transport could be influenced by the trip characteristics. [ABSTRACT FROM AUTHOR]

The article deals with the issue of railway transport safety from a strategic aspect. In turn, the concept of developing railway transport safety and the possibility of transferring model solutions to the economic field are presented. The article also focuses on highlighting the most significant criteria in terms of the development of railway safety. All stages in the realization of a relevant strategy are characterized, with a particular emphasis on the conditions for their efficient implementation. [ABSTRACT FROM AUTHOR]

Short-term forecasting of OD (origin to destination) passenger flow on high-speed rail (HSR) is one of the critical tasks in rail traffic management. This paper proposes a hybrid model to explore the impact of the train service frequency (TSF) of the HSR on the passenger flow. The model is composed of two parts. One is the Holt-Winters model, which takes advantage of time series characteristics of passenger flow. The other part considers the changes of TSF for the OD in different time during a day. The two models are integrated by the minimum absolute value method to generate the final hybrid model. The operational data of Beijing-Shanghai high-speed railway from 2012 to 2016 are used to verify the effectiveness of the model. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of the TSF. [ABSTRACT FROM AUTHOR]

Transit oriented development (TOD) has been an important topic for urban transportation planning research and practice. This paper is aimed at empirically examining the effect of rail transit station-based TOD on daily station passenger volume. Using integrated circuit (IC) card data on metro passenger volumes and cellular signaling data on the spatial distribution of human activities in Shanghai, the research identifies variations in ridership among rail transit stations. Then, regression analysis is performed using passenger volume in each station as the dependent variable. Explanatory variables include station area employment and population, residents’ commuting distances, metro network accessibility, status as interchange station, and coupling with commercial activity centers. The main findings are: (1) Passenger volume is positively associated with employment density and residents’ commuting distance around station; (2) stations with earlier opening dates and serving as transfer nodes tend to have positive association with passenger volumes; (3) metro stations better integrated with nearby commercial development tend to have larger passenger volumes. Several implications are drawn for TOD planning: (1) TOD planning should be integrated with rail transit network planning; (2) location of metro stations should be coupled with commercial development; (3) high employment densities should be especially encouraged as a key TOD feature; and (4) interchange stations should be more strategically positioned in the planning for rail transit network. [ABSTRACT FROM AUTHOR]

An urban subway network with a number of service lines forms the backbone of the public transport system for a large city of high population, such as Singapore, Hong Kong and Beijing. Passengers in these large cities heavily rely on urban subway networks for their daily life. The departure times of the last trains running on different lines of an urban subway network should be well coordinated in order to serve more passengers who can successfully transfer from one line to another, which is referred to as the last train departure time choice problem. This study aims to develop a global optimization method that can solve the last train departure time choice problem for large-scale urban subway networks. To do so, it first formulates a mixed-integer linear programming (MILP) model by introducing auxiliary binary and integer decision variables. For the real-life and large-scale instances, however, the formulated MILP model cannot be solved directly by the global optimization methods such as branch-and-bound algorithm invoked by CPLEX – one of the powerful optimization solvers because of the instance sizes. An effective two-phase decomposition method is thus proposed to globally solve the large-scale problems by decomposing the original MILP into two MILP models with small sizes. Finally, a real case study from the Beijing subway network is conducted to assess the efficiency and applicability of the two-phase decomposition method and perform the necessary sensitivity analysis of the operational parameters involved in the last train departure time choice problem. [ABSTRACT FROM AUTHOR]

Tram drivers have a difficult task in controlling one of the heaviest vehicles on the road whilst negotiating a complex road environment with multiple road users. Like all public transport drivers, tram drivers need to ensure passenger safety and to run on time. However, very little research has been conducted evaluating tram driving tasks and even less on evaluating tram drivers opinion on how other road users are affecting tram road safety. Therefore, the aim of this study is to investigate the key tram driving challenges, to identify the key road user factors affecting tram road safety as well as to explore the potential safety improvement initiatives on tram routes from the tram drivers’ viewpoint. The study incorporated five focus groups involving thirty tram drivers in Melbourne. The key themes emerged inductively from focus groups were identified through a data coding process. Outcomes of the focus groups revealed seven major challenges in tram driving: ensuring safety for all people in and around the tram, pressure for running on-time, maintaining constant concentration on roads, predicting other road users’ behavior in advance to avoid any crash incident, preventing passenger falls on board, accepting the operational constraints of trams and managing fatigue workloads. Tram drivers identified that other road users are unaware of safety issues around trams, have a poor understanding of road rules about driving with trams and often violate road rules around trams, and they mentioned this road user behaviors as the key challenges for safe tram driving. Tram drivers proposed rendering greater law enforcement on the tram network to penalize road users who are violating road rules around trams, introducing more safety campaigns and safety education to increase awareness among road users to improve tram road safety. Findings of this research enhance understanding of tram driving challenges, provide an in-depth knowledge of road user factors affecting tram road safety and suggest effective planning strategies for transit agencies to improve road safety. [ABSTRACT FROM AUTHOR]

Railways are required to operate with a high level of reliability and safety for transporting passengers within a certain budget. One important way of meeting these requirements is to implement proper maintenance activities. However, maintenance cost is always under pressure for operating company. Considering the main maintenance activities for rail, this paper discusses a model for systematic and holistic cost analysis using a Petri nets (PN) methodology. By developing sub-models including: deterioration, inspection, lubrication, maintenance and renewal, a whole model of rail maintenance process is developed based on PN. The Monte Carlo method is applied to the model to simulate the maintenance process and to evaluate the related cost. The application of the model is demonstrated by an example. The model is solved, and the maintenance cost during the rail’s life cycle is presented. The costs resulting from different maintenance activities are also simulated and discussed. [ABSTRACT FROM AUTHOR]

As train passengers expect a high degree of reliability from a railway network with minimal delays, during the timetabling process planners need to balance the goals of maximizing the offered capacity and delay resistance. This is often done in a two-step process where first a feasible timetable is found for a given line structure, and consecutively the stability of this timetable is evaluated and local modifications are performed to the timetable. This paper describes an optimization method to find a feasible periodic timetable that also ensures maximum stability for heterogeneous railway networks. The model is capable to handle flexible train orders, running and dwell times, and overtaking locations. We use the minimum cycle time of the periodic timetable as an indicator for stability, and define an optimization problem with this minimum cycle time as the objective function to be minimized. We also present dimension reduction methods and an iterative optimization approach to improve the mathematical optimization process. We show the applicability of the approach with case studies on the central part of the Dutch railway network. [ABSTRACT FROM AUTHOR]

Currently the rail transport is marked by a clear predominance of passenger traffic, due to its safety and its comfort. However, with new high-speed trains’ technologies and significant movement frequencies, the rails are particularly more solicited. Therefore, the quality of the rail is an important element of the comfort felt by passengers and especially the safety of traffic. This quality is degraded by the presence of defects in the welding of the rails. Depending on the criticality of the defects, damaging processes can disable the rail. The control of these defects seems to be necessary for a better prevention of any breakdown risk. This is what motivated our research, through which we had developed a method to control the angles’ selection of ultrasonic waves’ propagation, for a better visualization of internal rail defects with their measurements/sizes and locations. Thanks to our method, we were able to improve the control and afterward the maintenance; knowing that the former method is limited only to the anomaly detection. [ABSTRACT FROM AUTHOR]

Among today’s vast data availability, traffic probe data in particular offer exceptional new opportunities for examining multistate mobility. Invaluable resources such as the National Performance Management Research Data Set (NPMRDS) allow users to assess mobility performance toward improving transportation operations and reliability at a megaregion scale. In this study performance measures are developed for interstate freight mobility consistent across Mid-America, followed by an anomaly scanner that detects significant impacts to mobility such as those from major incidents, work zones, or winter weather. The scanner functions through a process control algorithm developed to scan tens of thousands of interstate kilometers each month to identify major disruptions to passenger and freight mobility. The scanner was validated against several known disruptions, and now provides monthly feedback to coalitions collaborating on multistate mobility performance improvement. [ABSTRACT FROM AUTHOR]

Freight railroads contribute to the national economy by moving over 40% of intercity ton-miles of freight. Meanwhile, train accidents can damage infrastructure and rolling stock, disrupt operations, and possibly cause casualties and harm the environment. Understanding major accident causes is the first step in developing and prioritizing effective accident prevention strategies. The literature has predominantly focused on nationwide train accident cause analysis, without accounting for possible variation in accident cause distributions by railroad and season. This research develops a log-linear statistical model that can estimate the number of freight-train derailments accounting for railroad, accident cause, season, and traffic volume. The analysis shows that broken rails and track geometry defects are the two leading freight-train derailment causes on four major U.S. freight railroads. Fall and winter appear to have a higher likelihood of a broken-rail-caused derailment than spring and summer, given the same railroad and traffic level. By contrast, track-geometry-defect-caused derailments occur more frequently in spring and summer than in fall and winter, given all else being equal. The statistical modeling techniques in this paper can be adapted to other types of train accidents or accident causes, ultimately leading to the prioritization of train safety improvement resources on various spatial and temporal scales. [ABSTRACT FROM AUTHOR]

We have compared Swedish national forecasts for passenger transport produced from 1975 to 2009 with the actual outcomes, and we found substantial differences between forecasts of passenger kilometers by mode and actual outcomes. In forecasts produced since the early 1990 s, road and air traffic growth rates have generally been overpredicted. Aggregate railway growth has been fairly accurate, but commercial long-distance railway growth has been overpredicted, and the growth of subsidized intra-regional railway travel has been underpredicted (following vast unanticipated supply increases). Focusing on car traffic forecasts, we show that a very large share of forecast errors can be explained by input variables turning out to be different than what was assumed in the forecasts. Even the original forecasts are much closer to actual outcomes than simple trendlines would have been, and once the input assumptions are corrected, the forecasts vastly outperform simple trendlines. The potential problems of using cross-sectional models for forecasting intertemporal changes thus seem to be limited. This tentative conclusion is also supported by the finding that elasticities from the cross-sectional models are consistent with those from a time-series model. [ABSTRACT FROM AUTHOR]

The objective of the study is to examine the impact of air transportation, railways transportation, travel and transport services on international inbound and outbound tourism in a panel of 19 tourists - oriented countries, over a period of 1990–2014. By applying principal component analysis, the study constructs travel and tourism competitiveness index for inbound and outbound tourism. The main constructs of inbound tourism index include international tourists' arrival, tourism receipts, receipts of passengers' transports items and travel items while the constructs of the outbound index include international tourists' departure, tourism expenditures, and expenditures for passengers transport and travel items. The result of panel Fully Modified OLS (FMOLS) regression shows that the presence of air transportation, railways transportation, and trade openness positively affect inbound tourism index, while travel and transport services negatively affect tourism competitiveness index. The causality results confirm the bidirectional relationship between inbound tourism, air transportation, railways passengers carried, trade openness and travel and transport services, while there is a unidirectional causality running from inbound index to railway goods transported, from air transport freight to trade factor, and from travel services to air transport freight. Outbound tourism index confirmed the bidirectional causality relationship with air transportation, railways transportation, and travel and transport services, while the causality running from outbound index to trade factor, from air transport passenger carried to travel services, and from railway goods transported to trade and transport services, which support the unidirectional causality relationship between them. The variance decomposition results show that air transportation freight is the contributor that largely influences inbound-outbound tourism, while railways passengers carried and trade openness has the least share to influence inbound and outbound tourism index for the next 10-year period. The impulse response function indicates that air transportation, railways transportation, trade openness and travel services will positively impact on inbound truism while travel and transport services will positively affect outbound tourism for the next 10-year period. The study concludes with the importance of transportation sector that deem desirable to promote tourism worldwide. The concentration of different modes of transportation including air transportation, railways transportation, and travel and transport system would helpful to advance international tourism. [ABSTRACT FROM AUTHOR]

In the last decade the number of rail passenger journeys in Great Britain has increased by half and car trips per person are down by a tenth. Meanwhile there has been significant growth in internet use and ownership of smartphones. Travel patterns are changing in tandem with adoption of digital age innovations. At a time when Britain is also poised to invest tens of billions of pounds in high speed rail, this paper examines how the experience of rail passengers has changed from 2004 to 2014. It draws upon questions concerning travel time use designed by its first two authors that have been included in the National Rail Passenger Survey waves conducted in Autumn 2004, 2010 and 2014, yielding over 80,000 survey responses in total. The data reveal an ongoing decline of paper-based materials accompanying travellers in the face of increasing adoption of digital alternatives. The latter can, for many, make their journey time experience better. However, the significant increase from 2004 to 2010 in the proportion of passengers considering their time use to have been very worthwhile has not continued on to 2014. This appears to be attributable (in part) to increased crowding and reduced passenger satisfaction associated with rising demand for rail travel. The paper sets out empirical insights, drawing them together in the form of a diagrammatic depiction of the interplay of factors involved in rail passenger experience. This depiction is then used to consider the implications for the future of rail travel. While mobile technologies appear to be placing more control of passenger experience in the hands of the passengers themselves, there remain important imperatives for the rail industry to support positive use of travel time. [ABSTRACT FROM AUTHOR]

We propose a Mixed Integer Non-Linear Programming (MINLP) model in order to determine optimal line frequencies and capacities in dense railway rapid transit (RRT) networks in which typically several lines can run over the same open tracks. Given a certain demand matrix, the model determines the most appropriate frequency and train capacity for each line taking into account infrastructure capacity constraints, allocating lines to tracks while assigning passengers to lines. The service provider and the user points of view are simultaneously taken into account. The first one is considered by selecting the most convenient set of frequencies and capacities and routing passengers from their origins to their destinations while minimizing the average trip time. The second one by minimizing operation, maintenance and fleet acquisition costs. Due to the huge number of variables and constraints appearing in real size instances, a preprocessing phase determining the best k-paths linking origin and destination stations is followed. Then, the best paths are used to define sparse index sets in order to drastically reduce the size of the problem. As illustration, the model is applied to a simplified version of the Madrid Metropolitan Railway network. [ABSTRACT FROM AUTHOR]

Analysis of the state of technical equipment and railway infrastructure in the example section of the Tashkent-Andijan shows the possibility of increasing the speed of passenger trains. The results can be used in the reconstruction of railways operating under similar conditions, in order to increase train speed. [ABSTRACT FROM AUTHOR]

This paper proposes a highly integrated solution approach for rolling stock planning problems in the context of long distance passenger traffic between cities. The main contributions are a generic hypergraph-based mixed-integer programming model for the considered rolling stock rotation problem and an integrated algorithm for its solution. The newly developed algorithm is able to handle a large spectrum of industrial railway requirements, such as vehicle composition, maintenance constraints, infrastructure capacities, and regularity aspects. We show that our approach has the power to produce rolling stock rotations that can be implemented in practice. In this way, the rolling stock rotations at the largest German long distance operator Deutsche Bahn Fernverkehr AG could be optimized by an automated system utilizing advanced mathematical programming techniques. [ABSTRACT FROM AUTHOR]

We present the literature's first mixed-integer linear programming model of a cyclic, combined train timetabling and platforming problem. The model's objectives are to minimize (1) the cycle length and (2) the total journey time of all trains dispatched during one cycle. The model falls outside the framework of the well-known periodic event scheduling problem and explicitly considers the minimization of cycle length using linear constraints and a linear objective function. We define the model, propose methods for obtaining bounds on the optimal objective value, and describe preprocessing techniques for reducing the number of variables and constraints. Numerous life-size problem instances are solved to optimality using IBM ILOG CPLEX. Results show the model's effectiveness in pursuing objectives 1 and 2, the benefits of deciding the cyclic train order versus assuming a given order, and the model's ability to calculate railway capacity without bias. [ABSTRACT FROM AUTHOR]

This paper proposes a schedule-based passenger assignment method for high-speed rail networks considering the ticket-booking process. Passengers book tickets to reserve seats during the presale period in high-speed rail systems and passengers on trains are determined during the ticket-booking process. The ticket-booking process is modeled as a continuous and deterministic predecision process. A solution algorithm is designed using the discretization of the continuous process by partitioning the ticket-booking time and the optimal paths remain constant in any partition interval. Finally, an application to the Chinese high-speed rail network is presented. A comparison of the numerical results with the reality is conducted to validate the efficiency and precision of the method and algorithm. Based on the results, the operating efficiency of the current train schedule is evaluated and some specific improvement measures are proposed. [ABSTRACT FROM AUTHOR]