Passenger Rail Research Articles

Development of a Virtual Reality Tool for Train Crew Training

(1) Background: The article presents the results of research carried out as part of one of the project’s tasks, aiming to develop training scenarios for selected workstations related to the operation of passenger rail transport. The article aims to present the results of a training experiment to verify the effectiveness of the developed training scenario for conductors regarding lift operations for people with disabilities. (2) Methods: The study used an analysis of the execution times of individual training tasks, accompanying observation, face-to-face interviews, and a comparative analysis of the effectiveness of various training strategies. The research was carried out following the developed five-stage research procedure. (3) Results: The obtained research results confirm the benefits of using virtual reality in training conductors and allow for determining the most effective training strategy. The measurements of the execution times of individual training operations made it possible to identify the tasks in the training program that were the most time-consuming or characterized by highly diversified execution times. (4) Conclusions: Based on the research, it was possible to develop recommendations regarding the changes that should be introduced in the training tool to better adapt to the real conditions of service operations. The effectiveness of using this form of training in relation to the improvement of a selected group of employees was confirmed.

Barriers to better bicycle parking for promoting intermodal journeys: An inter-organisational collaboration perspective

Organisational structures in the transport sector are often complex and fragmented, with different authorities responsible for different stages of a traveller's journey. In such circumstances, collaboration across organisational boundaries is required to facilitate intermodal journeys. This paper aims to provide empirically grounded insights into collaboration in transport planning, extending the literature to include cycling as an access and egress mode. This is done by examining the challenge of improving bicycle parking facilities at railway stations in Copenhagen, Denmark. Interviews with key actors involved in public transport and cycling planning reveal three main inter-organisational barriers to improving station bicycle parking in Copenhagen. First, station bicycle parking falls between the responsibilities of different organisations and levels of governance. Second, the absence of an established funding formula contributes to negotiation-oriented rather than collaborative interactions among the stakeholders. Third, the tension between cyclist satisfaction and rail passenger growth targets hinders collective action. In summary, despite Copenhagen's strong cycling identity and the prioritisation of this transportation mode in the city's political decision-making and transport planning, the issue of station bicycle parking highlights the complexity of multi-actor governance of intermodal journeys.

Long-distance rail in Europe: Comparing the forms of head-on competition across Europe

Europe is finally entering a season of liberalisation in the long-distance rail passenger market, which takes the form of on-track competition among public and private operators. The paper provides a broad-scope comparison of relevant European markets, belonging to liberalised and non-liberalised countries, aiming to point out the patterns in terms of supply, competition model and prices. The paper is based on a sample of heterogeneous 69 city-pairs, analysed in two fourteen days periods in 2019 (May/June and November). All available modes are observed, collecting info on companies, frequency of services, and cheapest price. The analysis starts from a schematisation of different business models, based on literature. Then, using the database, we study the country's supply structure, size, and level of intermodal and intra-modal competition through HHIs. Prices are analysed in two steps: the average prices and the price dispersion, searching for their main determinants, including but not limited to competition. Results show that a higher competition level is not always corresponding to low prices, which are instead determined by many other factors such as size of market, demand, socio-economic characteristics, subsidies, production costs, speed advantage, strength of the incumbent, etc. The competition level, instead, directly influences the quality, the supplied capacity, and the price dispersion.

Modeling cascading failures of urban rail transit network based on passenger spatiotemporal heterogeneity

To explore and alleviate large-scale failures under urban rail transit network accidents, cascading failures are usually investigated integrating the network topology and passenger flow. However, the impacts of the heterogeneity of travel demand and its interactions with the spatiotemporal heterogeneity of rail passenger flow on cascading failures are still left unknown. In this study, the dynamic changes of origin-destination travel demand under failures, the time-delay of cascading failures and the interaction between these dynamic properties and spatiotemporal heterogeneity of passenger flow are modeled and explored in an improved disaster spread theory model. The approach is applied to Shanghai urban rail transit network under different attack scenarios. Results show that the scale of cascading failures on Shanghai urban rail transit network importantly depends on the ratio of passengers changing travel demand and time-delay of cascading failures. Besides, large in-flow of stations adjacent to the failed station would not only cause fast spread of cascading failures at the early stage but also result in many failed stations in the end. The heterogeneity of passenger flows in different directions on the network would reduce the scales of cascading failures. It is also found out that the circle line could obviously prevent the spread of cascading failures.

Service Quality in Rail Systems: Listen to the Voice of Social Media

Service quality is essential to increase and maintain user loyalty to the railway system. In the literature, surveys have been used to measure user satisfaction, and mathematical methods have been applied to quantify the survey results. In recent years, user-generated content, including comments and complaints shared via social media, has been used to measure the quality of rail services. This content may provide important insights into the quality of the service provided with its dynamic structure. In this study, a SERVQUAL-based social-media analytics approach is used to measure railway service quality, placing special emphasis on the temporal variations in a national rail system. Topic modeling was used to assign each content item to the relevant service dimension and sentiment analysis was applied to measure the level of satisfaction. Importance–performance analysis was employed at the final stage to generate policy suggestions. Gathering more than 2.3 million social-media messages posted from 2011 to 2021, we examined the temporal evolution of service quality of the Turkish rail system. The results reveal the most and least important services and the satisfaction level of each dimension. The differences between the priorities of conventional and high-speed rail passengers are defined, and policy recommendations are presented.

The relationship between freight and passenger train noise levels and distance on the Sydney Metropolitan Rail Network across 281 measurement sites

Transport for NSW undertakes noise monitoring at a range of distances and locations around the NSW Government-managed rail network. The monitoring quantifies noise levels from freight and passenger train operations and informs delivery of noise reduction programs including the Transport for NSW’s Freight Noise Attenuation Program, which was launched in 2015. Comprehensive noise monitoring over a typical period of two weeks has been undertaken at 281 representative locations adjacent the passenger and freight rail network around Sydney. Results were analyzed to determine the LAE noise levels from each freight and passenger train passby, and the average weekday LAeq(15hour) daytime and LAeq(9hour) night-time levels. Curves of best fit are presented that illustrate the relationship between freight and passenger train noise levels and the distance to the near track. These curves of best fit can be utilised by Government agencies and acoustic practitioners to quantify the potential noise impact of freight and passenger train operations at a range of distances and locations close to the NSW Government-managed rail network and identify appropriate noise mitigation measures.

Prediction of railroad track geometry change using a hybrid CNN-LSTM spatial-temporal model

Track geometry is highly important for ensuring railroad safety. Predicting track geometry degradation can support preventive maintenance by identifying and prioritizing track segments that are more prone to potential track geometry defects. This paper develops a novel machine learning approach that can simultaneously geospatially align track geometry data from multiple inspections accounting for positional errors, and also predict foot-by-foot track geometry change over time. The proposed position correction method considers multiple geometry parameters to provide highly accurate positional information for geometry measurements, which is a prerequisite for foot-by-foot track geometry prediction. A hybrid CNN (convolutional neural network)-LSTM (long short-term memory neural network) machine learning model is developed to account for spatial–temporal dependence with respect to foot-by-foot track geometry change. Specifically, CNN is used to incorporate spatial dependence of track geometry on adjacent segments. LSTM is applied to learn dynamic changes in track geometry data over time to consider the temporal dependence. The hybrid CNN-LSTM model is validated using track inspection data provided by one major freight railroad in the United States. The results show that our positional error correction method can reduce the relative positional error to less than 1 foot with a 99% confidence interval. Our proposed CNN-LSTM model outperforms four other models, including a naïve model (using the last observation), multi-layer perceptron (MLP), plain CNN, and plain LSTM, for both short-term and long-term prediction periods. The proposed hybrid machine learning methodology can be adapted to various other freight and passenger rail lines. The predictive track geometry change information can be used by the industry to plan and prioritize resources for preventative maintenance, yielding benefits in safety and operational efficiency.

Coupling development of high-speed rail network and innovative cooperation based on travel behavior of depressed passengers

Background Depression is a common mental illness. Patients with depression show somatization symptoms such as loss of appetite, insomnia and low mood. The etiology and pathogenesis of depression are still unclear, and the pathogenesis is related to biochemical, neuroendocrine, sleep and brain electrophysiological abnormalities. This study takes depressed passengers as the research object to explore the intervention and influence of innovative high-speed rail services on patients with depressive episodes when they travel, so as to provide ideas for the coupling development of high-speed rail network and innovative cooperation.Subjects and Methods38 cases of high-speed rail passengers with depression were randomly divided into the experimental group and the control group. The experimental group was treated with innovative psychological services of high-speed rail. Hamilton Depression Scale (HAMD) was used to evaluate the degree of depression before and after treatment, and Hamilton Anxiety Scale (HAMA) was used to evaluate the degree of anxiety.ResultsThe scores of HAMD and HAMA in the experimental group after innovative psychological intervention services were lower than those before participation (P<0.05), and the difference was statistically significant.ConclusionsThe innovative high-speed rail depression psychological intervention service has a positive impact on depressed passengers. After the intervention, depressed passengers’ depressed mood and pessimistic thoughts are improved, they no longer resist others, and their discomfort symptoms are significantly reduced. At the same time, this intervention mode opens new ideas for the coupling development of high-speed rail network and innovative cooperationAcknowledgementFoundation: National Natural Science Foundation of China (No. 41301104); Foundation: National Natural Science Foundation of China (No. 41871108).

Goodbye monopoly: The effect of open access passenger rail competition on price and frequency in France on the high-speed paris-Lyon line

The Paris-Lyon line is the busiest High-Speed Line in Europe and has been open to competition in open access since December 18, 2021. The main objective of the paper is to explore the effects for users with respect to price and frequency compare with the existing literature. The analysis is based on a large database (n = 1243) collected by web scraping from September 2019 to October 2022. The method relies on a descriptive analysis with a similar route without competition (Paris-Bordeaux) in the comparison group. The results highlight an increase of frequency by 15% and a decrease in price by 23%. The prices charged by the newcomer are lower than those of the incumbent (−30% to −50%). The comparison with the control route suggests a positive effect on price that moderates the economic catch-up effect following the COVID-19 pandemic in an inflationary context. More specifically, SNCF appears to take a wait and see attitude to competitive pressure from Trenitalia. It has moderated its prices since the new offer was introduced and has maintained its trains.

ALGORITHM FOR ASSESSING THE ECONOMIC EFFICIENCY OF THE ORGANIZATION OF MULTIMODAL LONG-DISTANCE PASSENGER TRANSPORTATION

One of the directions of development of the transport complex of the Russian Federation is the development of multimodal transport technologies and infrastructure to ensure multimodal transportation. The article presents an economic assessment of measures for the organization of multimodal long-distance passenger transportation. It is shown that the proposed methodology is aimed at meeting the basic requirements for the organization of passenger transportation, which are to obtain the maximum income when performing multimodal transportation in the direction, and to maximize the number of passengers transported in order to better meet passenger demand.
 Purpose is to study the impact of multimodal transportation on the increase of passenger turnover at the landfill of JSC “FPC”. Since modern requirements for the passenger transportation system dictate the need to create a multimodal transport system based on the integration of passenger rail transport with other modes of transport, it is necessary to show the importance of organizing multimodal transportation in accordance with passenger demand. To consider the matter of necessity to determine the main parameters that affect the choice of multimodal routes.
 Methodology. Complement existing approaches to the organization of multimodal transportation. Methods of economic theory for determining the effectiveness of the organization of long-distance multimodal passenger transportation.
 Results. The criteria of multimodal transportation have been defined.An algorithm for assessing the economic efficiency of the organization of a multimodal route is proposed, which allows to estimate the expected profit from transportation organization, as well as predicting transportation impact on transportation process indicators.
 Practical implication. The recommendations and approaches proposed in the algorithm developed by the author can be used for the development of multimodal routes. The proposed algorithm allows performing a preliminary analysis of its economic feasibility yet at the preliminary selection stage for multimodal long-distance passenger transportation organization.

Freight transport using additional railcars attached to intercity passenger trains with transshipment and railcar circulation: Tabu-search-based Lagrangian heuristic

Developing under-exploited passenger rail networks is emerging as an alternative for freight transport. In light of this, we investigate a long-haul freight mode in which additional railcars for carrying shipments are attached to passenger trains, and the shipments can transfer among the trains at intermediate stops. To coordinate space–time schedules of shipments and railcars, we construct a two-level space–time network: one level captures the departure, transshipment, and arrival of shipments; whereas the other level depicts the holding, reshuffling, and repositioning of railcars. Incorporating variables of space–time arc selection and constraints concerning shipment (un-) loading, locomotive pulling capacity, supply–demand coupling, and flow conservation on networks, a binary integer model is established to minimize the total travel cost of both railcars and shipments. The primal problem is decomposed using Lagrangian relaxation. Lagrangian multipliers and dual bounds are approximated by solving the Lagrangian dual. We devise a primal heuristic based on tabu search for expediting high-quality solutions. Numerical experiments demonstrate computational performance and managerial insights.

Switching intention, WOM and quality of public transport services: A case of the Kuala Lumpur conurbation

Despite spending billions of dollars on urban transport infrastructure, Malaysia has a poor reputation for its public transit service. Consequently, the majority of urban residents continue to rely on their cars. Hence, this paper aims to understand commuters’ intention to switch from private vehicles to public transit and spread word-of-mouth (WOM) about its services and assess the roles of satisfaction and service quality as antecedents. A cross-sectional survey of 421 rail and bus passengers was undertaken in Kuala Lumpur's urban and sub-urban areas, and the data was analyzed using SmartPLS. According to the data, empathy is the strongest predictor of satisfaction with transit services. Except for reliability, the service quality characteristics influence satisfaction and yield positive indirect effects on both switching intention and WOM. Transit operators and planners should take into account that providing a pleasant and hassle-free riding experience has a substantial impact on commuter satisfaction and long-term commitment. This study contributed to the body of knowledge by exploring the intervention role of satisfaction in the relationship between service quality and switching intention, as well as WOM.

Ranking methodology to prioritize high-speed railway corridors

Abstract The purpose of this article is to create and calibrate a high-speed rail passenger traffic-based ranking model using historical high-speed rail ridership data from Spain. The existing literature is scarce, and the models used have several main issues, such as arbitrariness, and not representing the real relations of variables. These models are analysed using real-world high-speed rail data; and improved by calibration with the data. Based on the results, I demonstrate the strengths and weaknesses of these models and propose a new model by combining the strong aspects of these models. I also show the importance of intermediate cities for the estimated ridership of an HSR corridor. The study develops our understanding of the ranking models and provides a more promising ranking solution as a contribution to high-speed rail planning.

Modelling and Dynamic Analysis of Adaptive Neuro-Fuzzy Inference System-Based Intelligent Control Suspension System for Passenger Rail Vehicles Using Magnetorheological Damper for Improving Ride Index

The ride comfort and safety of passenger rail vehicles depend on the performance of the suspension system in attenuating vibrations induced by track irregularities. This paper investigates the effectiveness of an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based semi-active controlled suspension system using a magnetorheological fluid damper in reducing nonlinear lateral vibrations of a passenger rail vehicle. A complete rail vehicle model is developed, including the carbody, front and rear bogies, and the passive suspension system’s nonlinear stiffness and damping characteristics are considered from experimental data. The passive suspension model is validated through experiments, and an ANFIS-based controller is incorporated with the secondary vertical suspension system to improve ride behavior. Three semi-active suspension strategies are considered under varying speeds and track irregularities, and their effectiveness is compared to the nonlinear passive suspension system in terms of rms acceleration, rms displacement, ride quality, and comfort. The results shows that the ANFIS-based semi-active suspension system with a magnetorheological fluid damper outperforms the passive suspension system and semi-active strategies in all tested conditions. There is a reduction in rms acceleration by approximately 11.11% to 23.64% and rms displacement by about 5.36% to 32.06%. Moreover, it significantly improves ride quality (9.20% to 31.02%) and comfort (9.96% to 31.50%). The rms acceleration and displacement are reduced, and the Sperling ride index and Percentage Reduction Index values demonstrate that the ANFIS-based semi-active suspension effectively minimizes the impact of rail irregularities and vibrations, resulting in a significant gain in ride quality and passenger comfort.

A latent auction model of firm establishment location choice in the Greater Toronto Area

We present a maximum bid model for business establishments in the Greater Toronto Area (GTA). The model is based on a latent auction approach, wherein price and utility are jointly modeled in a random utility-maximizing framework. Structural relationships between establishments by their industry classification and type (i.e., headquarters, subsidiary, branch, or single location) are explored through a generalized nesting correlation structure. This structure provides a mechanism for differentiating between branch and single-location establishments, having seemingly similar functions, but differing in their allocation between industry and type nests. Maximum bid models are estimated for the full establishment population in the GTA at the level of individual buildings. The model scope allows us to provide a range of insights into establishment location choice behavior, which was previously infeasible due to data limitations. We find that professional service establishments tend to locate near passenger rail stations (i.e., subway and LRT), while industrial establishments tend to locate near major highway interchanges. We confirm the finding by Kenworthy and Laube (1999) that Canadian cities are less auto-dependent than US cities, albeit from the perspective of establishment location rather than individual vehicle travel data.

How has the Covid-19 pandemic affected wheelchair users? Time-series analysis of the number of railway passengers in Tokyo

The Coronavirus disease 2019 (COVID-19) has posed ‘new barriers’ to people with disabilities (PwDs) who have already experienced many barriers to using public transportation. However, there is limited quantitative knowledge of how PwDs have been affected by the COVID-19 pandemic. This study investigated the impact of the COVID-19 pandemic on the use of public transportation by PwDs over time. Specifically, we analysed time-series data on wheelchair rail passenger numbers and all rail passenger numbers in Tokyo from April 2012 to December 2021. The impact of COVID-19 was more accurately assessed by excluding seasonal variations in the time-series, and two key findings were obtained. First, the change point for the decline in the number of passengers owing to the COVID-19 pandemic was March 2020, one month earlier than the declaration of the state of emergency. Second, using the time-series model, the actual and estimated values were compared, and we found that wheelchair rail passenger numbers reduced by approximately 20 percentage points on average compared with all rail passengers. Wheelchair rail passengers were more severely affected by the COVID-19 pandemic than all rail passengers. Based on previous studies, these findings demonstrated that opportunities to participate in society were disproportionately reduced for PwDs during the COVID-19 pandemic. This study’s quantitative data and the resulting conclusions on wheelchair users are useful for inclusive planning for mitigating the pandemic’s impact by national administrations and public transport authorities.

An Approach for Quick Method of Estimating Passenger And Aircraft Demand for Feeder Air Services in India

The recent and the proposed entry of new airlines both in the ‘no-frills’ and in the "full service" categories has completely changed the aviation scenario in India. Obviously this explosive increase in capacity will have a profound effect on the economy of the airlines both in the short term as well as in the long-term period. A growth of over 25% per annum in passenger traffic may not be sustainable for long; thus galloping increase in capacity may result in mergers and strategic alliances of airlines on one side and closing down of some of the airlines on the other side. A point, which is to be noted is that, most of the new entrants also operate in the major trunk routes and serve the metros and the major cities. What appears to have not been tapped is the equally large potential in the regional and short haul sectors, which serve major, and small city pairs and also act as feeders to the major hubs.Realizing the importance of this, the government in its new civil aviation policy has given thrust to regional/ short-haul air travel. In this paper, an attempt is made to review the hierarchy of airline networks in India with respect to trunk, major and feeder routes. The air passenger traffic carried in terms of revenue passenger kilometers (RPK) is compared with upper class rail traffic. The present status of feeder airline services in India is outlined. It is pertinent to study the passenger traffic demand in these feeder routes as compared to upper class rail traffic as some percentage of upper class rail passengers are willing to shift to air travel due to marginal difference between airfare and upper class rail fare and time factor. The future RPKs are forecasted based on the actual RPKs data and the estimated RPKs of earlier market survey. A suitable aircraft size for airline operations in these feeder routes is arrived at based on existing air traffic data by a simplified approach from the basic principles of airline business. A macroscopic measure is used to determine the aircraft demand by assuming average block speed and utilization for each aircraft type. A sensitivity analysis was carried out for various levels of traffic growth keeping in view the sharp increase of air travel in recent years and further growth in air traffic fuelled by feeder sector as the hinterland opens up industry, services and tourism.

Legal and Technological Aspects of Life Cycle Contract Implementation in the Long-Distance Passenger Rail Transportation

The analysis and the experience gained in shaping contractual relations in the LCC format, both on the part of foreign companies and in the domestic market, have resulted in the conclusion that it is beneficial for the customer to conclude LCC. Ultimately, the costs are reduced by about 10-15 % compared to the traditional form of contractual relations (separate contracts for manufacturing and, respectively, service maintenance). LCC is also advantageous since it eliminates the need to search for and subsequently contract the contractors at the stage of operation.When concluding LCC contract, both purchase and subsequent maintenance of rolling stock can be carried out through a concession agreement in compliance with legislation regulating the procurement procedure. When purchasing, it is necessary to be guided by the requirements of federal law in terms of mandatory tender procedures and selection of potential suppliers.The analysis of existing models for formation of contractual relations for maintenance of rolling stock under the LCC contract has shown that it is advisable to consider the possibility of extending it to newly manufactured passenger rolling stock used in long­distance passenger transportation.

Communication challenges faced by customers who are less proficient in English and Afrikaans at two South African state-owned enterprises

The Use of Official Languages Act (No. 12 of 2012) applies to all national departments and state-owned enterprises (SOEs) in South Africa and stipulates that they should promote multilingualism when interacting with members of the public and/or customers. The main aim of this study was to investigate how two SOEs, that is, the South African Post Office (SAPO) and Passenger Rail Agency of South Africa (PRASA), manage communication with their customers, particularly those who cannot communicate in English and Afrikaans. Data for this study were gathered through a mixed method approach. Quantitative data (i.e., a Likert-type scale) were gathered from 120 participants who were customers of the two SOEs, and qualitative data (i.e., face-to-face interviews) were gathered from 20 interviewees who were drawn from the 120 participants. The researcher was based in Gauteng, and conducted the study in that province because it was convenient and practical. The data were gathered in Tshwane, Ekurhuleni, Johannesburg, and the West Rand. The study found that customers believed that those who could not communicate in English and Afrikaans did not receive adequate information from the SOEs because of this shortcoming. The study also revealed that the marginalisation of Black South African Languages (BSALs) by SOEs was regarded as justified by some respondents because these SOEs provided services to customers who speak different languages. The study also found that other participants felt that it was necessary for SOEs to continue to use English as the main language of communication with customers because it is an international language, which also promotes unity among the people of South Africa, including customers of SOEs.Contribution: The major contribution of this article to scientific knowledge is that it dwells deeper into how customers of the two SOEs who are less proficient in English and Afrikaans felt excluded in communication with all customers, and this is the first article to do so. Through this article, there is potential that the SOEs will appreciate that customers who are less proficient in English and Afrikaans want major adjustments to be made so they too can feel a sense of belonging and also fully appreciate what is being communicated to all customers, regardless to their proficiency in the two languages.

Identifying emissions hotspots and strategies to reduce real-world fuel use and emissions for passenger rail: A spatially resolved approach

The objectives of this work are to model spatially resolved passenger locomotive fuel use and emission rates, locate emissions hotspots, and identify strategies to reduce trip train fuel use and emissions. Train fuel use and emission rates, speed, acceleration, track grade, and track curvature were quantified based on over-the-rail measurements, using portable emission measurement systems, for diesel and biodiesel passenger rail service on the Amtrak-operated Piedmont route. Measurements included 66 one-way trips and 12 combinations of locomotives, consists, and fuels. A locomotive power demand (LPD) based emissions model was developed based on the physics of resistive forces opposing train motion, taking into account factors such as speed, acceleration, track grade, and curvature. The model was applied to locate spatially-resolved locomotive emissions hotspots on a passenger rail route, and also identify train speed trajectories with low trip fuel use and emissions. Results show that acceleration, grade, and drag are the major resistive forces affecting LPD. Hotspot track segments have 3 to 10 times higher emission rates than non-hotspot segments. Real-world trajectories are identified that reduce trip fuel use and emissions by 13 % to 49 % compared to the average. Strategies for reducing trip fuel use and emissions include dispatching energy-efficient and low-emitting locomotives, using a 20 % blend of biodiesel, and operating on low-LPD trajectories. Implementing these strategies will not only decrease trip fuel use and emissions but reduce the number and intensity of hotspots and, thus, lowering the potential for exposure to train-generated pollution near railroad tracks. This work provides insights on reducing railroad energy use and emissions, which would lead to a more sustainable and environmental-friendly rail transportation system.