Passenger Trains Research Articles

Novel empty train return strategy and passenger control strategy to satisfy asymmetric passenger demand: A joint optimization with train timetabling

Big cities’ bi-directional metro lines often have unbalanced passenger demand, i.e., up-directional passenger demand is oversaturated but down-directional passenger demand is unsaturated. In recent years, the method to relieve congestion in oversaturated direction has attracted much attention, but many problems in the unsaturated direction have not gotten as much attention, e.g., the waste of transportation resources caused by low loading rate, and the insufficient utilization of platform space resources caused by less waiting passengers. To address these problems, this paper introduces a new collaborative optimization model for the train timetable, passenger control and rolling stock schedule on a bi-directional metro line with unbalanced passenger demand. With consider the real-time state of bi-directional platform passengers, a platform passenger control strategy is designed to promote the utilization of platform resources, and an empty train return strategy is proposed to transfer transportation resources to oversaturated direction. To characterize the problem mathematically, a multi-objective mixed-integer nonlinear programming model (MINLP) is formulated to minimize the passengers’ waiting time, the difference of bi-directional platform passenger density and the use cost of trains. An effective heuristic algorithm based on the non-dominated sorting genetic algorithm (NSGA-II) and the adaptive large neighborhood search (ALNS) is designed to find high-quality solutions for the proposed model. Finally, five sets of numerical examples based on the Beijing metro Batong line, are conducted to validate the performance of the proposed method in this paper. The experimental results demonstrate the method can fully utilize the transportation and platform resources of the unsaturated direction, to improve transport efficiency and relieve platform congestion of oversaturated direction.

Statistical Analysis of Train Operation and Passenger Distribution Based on Real Records: A Case Study of Wuhan-Guangzhou HSR

This paper summarizes the results of an effort aimed at improving train operation schedules on Wuhan-Guangzhou high-speed railway (WG-HSR). The real-record train operation and passenger tickets-booking records of WG-HSR are used for statistical analysis on the train service quality and passenger distribution. More specifically, the train service frequency and interval time at each station are analyzed. Based on this, the temporal and spatial distribution of capacity utilization in each section are investigated. In order to get a holistic view of passenger flow characteristics, the passenger volume during different time periods and between several origin and destination (OD) pairs are investigated to characterize travellers’ spatial-temporal preferences. The passenger distributions on some long-distance trains are shown to get the number and proportion of cross-line passengers travelling on the WG-HSR. Moreover, for a better understanding of the seat capacity utilization of trains, the load rates of trains in various sections and time periods are investigated. Specifically, the relationship between the average load rate of trains and trains’ running distance is explored, finding that the longer the non-cross-line train travels is, the higher the average load rate is. This study provides insightful findings that help understanding HSR operation and conducting further research.

Sniffing Drones: A Promising Solution for Measuring Railroad Emissions in Urban Environments

Locomotive emissions from railroads can particularly impact air pollution, making it crucial to understand their impacts on human health and the environment and develop strategies to reduce them. The potential of drone technology equipped with a “sniffing” system for detecting air pollution emissions is promising and can be a valuable tool for assessing dynamic emissions. This research utilized sensor-equipped drones to measure gaseous emissions from cargo and passenger trains on a railway in Curitiba, Brazil. Reference equipment evaluated the accuracy of NO2, SO2, and O3 concentrations. The results showed that before the passage of trains, the average SO2 concentration was 20 µg/m³, with a maximum concentration of 110 µg/m³ detected during transit. The average increase in NO2 concentrations was from 30 µg/m³ to 120 µg/m³, and the average increase in O3 concentrations was from 80 µg/m³ to 135 µg/m³. The vertical profiles were evaluated before and after the passage of locomotives, indicating an accumulation of pollutants above the railroad. These findings demonstrate the potential of sniffing drones to measure railroad emissions in urban environments. They also highlight the need to regulate emissions from diesel-powered locomotives to minimize atmospheric pollution and its negative impact on public health in emerging and developing countries.

The cost differential for an optimal train journey on level track

The classic optimal train control problem is to drive a train on a track with known gradient over a fixed distance and within a specified time in such a way as to minimize tractive energy consumption. On level track the optimal strategies take two basic forms—a truncated strategy of optimal type with phases of maximum acceleration, coast and maximum brake which is typical of shorter metropolitan journeys, and an extended strategy of optimal type with phases of maximum acceleration, speedhold at the optimal driving speed, coast to the optimal braking speed, and maximum brake which is typical of longer journeys by freight trains and intercity passenger trains. The cost of these optimal strategies is uniquely determined by the journey distance and journey time. In this paper we extend a previously known formula for the partial rate of change of cost with respect to journey time to a formula for the full rate of change of cost that also incorporates the partial rate of change of cost with respect to journey distance.

ENERGY SAVING AND DISTANCE TRAVELED OF THE RAILWAY TRAIN FROM ITS BIRTH TO THE FOURTH INDUSTRIAL REVOLUTION MODELING

The simulation of railway systems plays a key role in the design of the supply of the railway network but also in the functionality of the train itself. Various studies have been carried out to understand the railway network and by extension the operation of the trains. [1,2] The history of the railway is an everlasting history of speed. The rail mode is a guided and low grip transit mechanism. Since the beginning of the Industrial Revolution at the start of the 19th century, when rail first emerged in Europe, passenger train speed has been crucial for competition—not necessarily with other kinds of transportation, but with other rail firms. Additionally, it gave verifiable proof of technological advancement in the time's most developed nations. In this work, an approach is studied for the modeling and simulation using Anylogic PLE regarding saving the energy and the distance traveled for five distinct time periods.

PERAMALAN JUMLAH PENUMPANG KERETA API DI PULAU JAWA MENGGUNAKAN METODE HOLT WINTERS EXPONENTIAL SMOOTHING DAN FUZZY TIME SERIES MARKOV CHAIN

One of the public transportation choices by the public is the train. The number of train passengers on the island of Java often increases and decreases in certain months. PT.KAI can monitor the number of train passengers by forecasting. Forecasting aims to predict the number of train passengers so that PT.KAI is ready to provide the best service. This study uses monthly data on the number of train passengers on Java Island from January 2015 to February 2020. This study uses multiplicative holt winters exponential smoothing and fuzzy time series markov chain. The multiplicative Holt Winters exponential smoothing method is used on data that contains trend and seasonal elements that experience data fluctuations simultaneously. The fuzzy time series markov chain method is a combination of the fuzzy time series with the markov chain which aims to obtain the greatest probability using the transition probability matrix. Based on the analysis results, it can be concluded that the multiplicative holt winters exponential smoothing method is better at predicting the number of train passengers on Java Island because the value of sMAPE multiplicative holt winters exponential smoothing is smaller, it is 3,0643% and the sMAPE fuzzy time series markov chain value is 5,2955%.

Virtual Coupling in Railways: A Comprehensive Review

The current mobility situation is constantly changing as people are increasingly moving to urban areas. Therefore, a flexible mode of transport with high-capacity passenger trains and a high degree of modularity in the trains’ composition is necessary. Virtual coupling (VC) is a promising solution to this problem because it significantly increases the capacity of a line and provides a more flexible mode of operation than conventional signaling systems. This novel review, in which approximately 200 papers were analyzed, identifies the main topics of current railway-related VC research, and represents the first step toward the implementation of VC in future railways. It was found that industry research has mainly focused on the feasibility of VC implementation and operation, whereas in academia, which is coordinated with industry, research has focused on control and communication systems. From a technological perspective, the main challenges for VC were identified with regard to aspects such as safety, control technology, interlocking, vehicle-to-vehicle communication, cooperative train protection and control, and integrated traffic management. The important directions for future research that have been identified for future development include complete dynamic models, real-time controllers, reliable and secure communication, different communication topologies, cybersecurity, intelligent control, reinforcement learning, and Big Data analytics.

Statistical learning for train delays and influence of winter climate and atmospheric icing

This study investigated the climate effect under consecutive winters on the arrival delay of high-speed passenger trains. Inhomogeneous Markov chain model and stratified Cox model were adopted to account for the time-varying risks of train delays. The inhomogeneous Markov chain modelling used covariates weather variables, train operational direction, and findings from the primary delay analysis through stratified Cox model. The results showed that temperature, snow depth, ice/snow precipitation, and train operational direction, significantly impacted the arrival delay. Further, by partitioning the train line into three segments as per transition intensity, the model identified that the middle segment had the highest chance of a transfer from punctuality to delay, and the last segment had the lowest probability of recovering from delayed state. The performance of the fitted inhomogeneous Markov chain model was evaluated by the walk-forward validation method, which indicated that approximately 9% of trains may be misclassified as having arrival delays by the fitted model at a measuring point on the train line. With the model performance, the fitted model could be beneficial for both travellers to plan their trips reasonably and railway operators to design more efficient and wiser train schedules as per weather condition.

Collaborative optimization for train stop planning and train timetabling on high-speed railways based on passenger demand.

In recent years, with increasing passenger travel demand, high-speed railways have developed rapidly. The stop planning and timetabling problems are the core contents of high-speed railway transport planning and have important practical significance for improving efficiency of passenger travel and railway operation Dong et al. (2020). This study proposes a collaborative optimization approach that can be divided into two phases. In the first phase, a mixed-integer nonlinear programming model is constructed to obtain a stop plan by minimizing the total passenger travel time. The constraints of passenger origin-destination (OD) demand, train capacity, and stop frequency are considered in the first phase. In the second phase, the train timetable is optimized after the stop plan is obtained. A multiobjective mixed-integer linear optimization model is formulated by minimizing the total train travel time and the deviation between the expected and actual departure times from the origin station for all trains. Multiple types of trains and more refined headways are considered in the timetabling model. Finally, the approach is applied to China's high-speed railway, and the GUROBI optimizer is used to solve the models in the above two stages. By analyzing the results, the total passenger travel time and train travel time decreased by 2.81% and 3.34% respectively. The proposed method generates a more efficient solution for the railway system.

Factors affecting state railway of Thailand (SRT) passenger train service use decision: A structural equation model

The State Railway of Thailand's (SRT) rail passenger ridership has dropped from a peak of 88 million rides in 1994 to less than 23 million in 2022, with the reasons for this collapse being numerous. Therefore, the authors set out to examine how organizational image (OI), service quality (SQ), service motivation (SM), and service satisfaction (SS) affect SRT use decision (SUD) making. From August–October 2022, multiple-stage random sampling was used to select a sample of 1,250 SRT passengers from five regional rail lines and their associated 25 stations. A confirmatory factor analysis goodness-of-fit was used to confirm the model's fit. A structural equation model (SEM) using LISREL 9.10 was then used to analyze the ten hypothesized relationships. The quantitative research used a 5-level questionnaire to measure the study's five constructs and 22 observed variables. The reliability of the items ranged from 0.86 to 0.93. The data analysis included calculating various statistical measures. Results showed that the model's causal variables positively affected passenger SRT use decision, with an R2 of 71%. When ranked by total effect (TE) values, service quality (SQ = 0.89) was viewed by the surveyed passengers as most important, followed by service satisfaction (SS = 0.67), organizational image (OI = 0.63), and service motivation (SM = 0.53). Additionally, all ten hypotheses were supported, with service satisfaction judged the most essential to SRT Use Decisions. The study's novelty is the ever-growing requirement for the SRT to serve as a regional hub in a more extensive East Asian rail and infrastructure strategy. The paper contributes significantly to the academic literature on factors affecting rail transportation use intent.

Unsupervised rail vehicle running instability detection algorithm for passenger trains (iVRIDA)

Intelligently identifying rail vehicle faults instigating running instability from carbody floor acceleration is essential to ensure operational safety and reduce maintenance costs. However, the vehicle-track interaction's nonlinearities and scarcity of running instability occurrences complicate the task. The running instability is an anomaly in the vehicle-track interaction. Thus, we propose unsupervised anomaly detection and clustering algorithms based iVRIDA framework to detect and identify running instability and corresponding root cause. We deploy and compare the performance of the PCA-AD (baseline), Sparse Autoencoder (SAE-AD), and LSTM-Encoder-Decoder (LSTMEncDec-AD) model to detect the running instability occurrences.Furthermore, we deploy a k-means algorithm on latent space to identify clusters associated with root causes instigating instability. We deployed the iVRIDA framework on simulated and measured accelerations of European high-speed rail vehicles where SAE-AD and LSTMEncDec-AD models showed 97% accuracy. The proposed method contributes to smart maintenance by intelligently identifying anomalous vehicle-track interaction events.

Passengers’ Perception of Satisfaction and Its Relationship with Travel Experience Attributes: Results from an Australian Survey

Rail, one of the most sustainable modes of transport, is vital in carrying mass passengers in many urban cities. Passengers’ satisfaction with railway services is mostly discussed in the context of service quality in the literature. However, limited studies have considered other attributes that may influence passengers’ satisfaction, such as their travel experience and issues encountered. This study aims to systematically model passengers’ satisfaction and its relationship with travel experience attributes. This paper makes a theoretical contribution by proposing a conceptual model that evaluates the overall satisfaction of passengers through four attribute groups, including traveller attributes, trip attributes, service attributes, and other attributes. The model is tested with the 429 valid responses collected from a passenger survey targeting Metro train users in Melbourne, Australia. Result shows that the best-fitted model is produced only when all attribute groups are considered together, for which 60% of the variation in overall satisfaction is accountable. It is found that all attribute groups have at least one variable included in the final model, and the service attribute group has the greatest influence. The best model has nine significant variables, with eight having positive associations to the overall satisfaction and one variable (GroupTravel) having a negative association. This finding suggests that consideration of other attributes is also important besides the service attributes, and hence advances our scientific understanding of train passengers’ satisfaction with train services. The public transport sector and the operators can use this knowledge to improve service and increase passenger satisfaction.

Railways Passengers Comfort Evaluation through Motion Parameters: A Systematic Review

Railways are one of the most widely used mass transportation systems. Its superior transportation capacity, low environmental impact, high safety, and comfort have been leading to a continuous increase in passengers. To keep this trend going, it is crucial to improve the railways’ attractiveness and comfort levels. A rail journey’s comfort performance is rather complex, involving the analysis of multiple factors. Those raised by the vehicle motion and seat performance are the focus of vehicle designers’ concerns. Therefore, only a combination of static and dynamic comfort methodologies can accurately characterize passengers’ comfort. This work aimed to perform a systematic review concerning the comfort evaluation of train passengers. The bibliographic search yielded 62 studies on static and dynamic comfort evaluation methods. Results show a lack of experiments conducted on real rail environments, leading to weak conclusions regarding the real in-service conditions that train users face. Moreover, an investigation gap concerning the simultaneous application of both static and dynamic methodologies was observed. Therefore, more investigations are needed to evaluate and increase passengers’ comfort and promote rail usage as a daily transportation system.

Improving multimodal passenger transportation technology under the wartime conditions in Ukraine

Abstract. Problem. Ukraine has a rather complex transport network, so the mismatch between the work of carriers when transferring from one mode of transport to another can create a large number of inconveniences for passengers. Issuance of various travel documents, the complexity of processing luggage and its movement between vehicles, a more thorough check of documents and luggage by employees of law enforcement agencies at border crossings and transfer points lead to an increase in travel time. On the other hand, ensuring the demand for some main directions of transportation can only be through the use of several modes of transport, so there is a need to improve the existing logistics technology for multimodal passenger transportation.
 Goal. The goal of this publication is to improve the technology of multimodal passenger transportation under martial law Methodology. Analytical research methods were used to form the relationship between the train delay at the border station and the number of passengers in it. Mathematical modulation methods were used in the formation of a new agreed schedule for the arrival of international passenger trains at the Kyiv-Passenger transport hub. Results. The research has shown that even under the current wartime conditions, it is possible to improve the operation of various types of passenger transport and the consistency of their traffic schedules to better meet the needs and quality of passenger transportation. The authors of the article analyzed the state and causes of delays in passenger trains at the Mostyska-2 border crossing, through which the largest railway passenger flows between Ukraine and the EU countries currently follow. Based on the analysis, the dependence of the train delay time at the border station on the number of passengers in the train was revealed, and in order to reduce the duration of these delays, it was proposed to improve the existing technology for calculating the travel time of a passenger train by introducing and using value F, corresponding to the train delay time at the border station per passenger. Originality. It is suggested to improve the model for organizing the interaction of different types of transport in the transport interchange Kyiv-passenger hub, by introducing a new value φ based on the dependence of the train delay time at the border station on the number of passengers transported in it, taking into account the specifics of the introduction of martial law in Ukraine. Practical value. The introduction and integration of the proposed technology into the existing mathematical models for the formation of a rationally coordinated schedule of multimodal passenger transportation will significantly reduce the waiting time for passengers at transfer points, rationalize the capacity and population of the rolling stock and increase the financial profit for carriers, it can also be used for the development of the system, information technologies and the use of a "single ticket".

Пути оптимизации дальних, местных и пригородных пассажирских перевозок в современных условиях

In this article, the authors consider the issue of optimizing passenger transportation by rail in terms of competition with other modes of transport that carry passengers both on the territory of Kazakhstan (local and suburban passenger transportation) and in the international direction. The analysis of the current state of passenger transportation in the Republic of Kazakhstan is carried out, divided by types of transport. The trends of changes in passenger traffic by the main modes of transport of the Republic of Kazakhstan are studied. The main priority directions of the development of railway passenger transport are highlighted, which can increase the demand for passenger transportation. The foreign experience of implementation and features of implementation of projects of high-speed and high-speed movement of passenger trains of developed countries are considered. Recommendations of the most cost-effective approach to increasing the speeds of passenger trains on the railway transport network are presented.

Alternative Policy Management Framework in Determination of Long-Distance Travel Permit Based on Covid-19-like Symptoms Using Data Mining

Even though the obligation to carry out a Covid-19 booster vaccination still applies to long trips using public transportation in Indonesia. One clause regarding checking policy for symptoms of Covid-19 is still often ignored by train passengers because the symptoms of Covid19 are still similar to those of influenza. Somehow, the travel policy is not fair for comorbid person which cannot have Covid-19 vaccination. This research goal is to propose an alternative policy, which is a part of policy management framework, to prevent the transmission of covid19 by long-distance train travel in new era when the enforcement of Covid-19 regulation has been repealed. As alternative of Covid-19 vaccination requirement, the use of data mining algorithm will be proposed ning algorithm to determine whether or not it is permissible to travel long distances by using the dominant covid-19 like symptoms. The results of this study are in the form of a reasoning knowledge regarding the symptoms that passengers need to pay close attention to avoid the risk of transmission of Covid-19. Even though the accuracy of the decision is still 66.67% using C4.5 algorithm, it is the first step to be implemented in a new era, namely the era of prevention of Covid-19, no longer an era of mitigation. The publication of this result is put on bulletin board design

Performance analysis of protective functions of forest plantations of the Lviv railway line (Ukraine)

To reduce the harmful impact of railway transport on the environment and ensure environmental safety, railway enterprises develop and implement a wide range of environmentally effective measures annually. First, it concerns the protection of the territories adjacent to the railroad tracks from various types of pollution. These forest plantations are created for the protection of the railroad track from adverse climatic factors, as well as for the reduction of the railway's impact on the surrounding territories - to reduce the various types of pollution, and to protect from adverse aerodynamic effects. In order to investigate the protective properties of forest plantations, we presented their detailed characteristics on the section of the Lviv-Sambir railway line. This is the busiest railway line in terms of the number of trains, which connects the eastern industrial regions of Ukraine with the western part of the European Union. It transports the largest volumes of cargo, including hazardous ones. The effect of afforestation on reducing the heavy metals content in the soil of the impact area of the railway was determined experimentally. In all samples, the concentrations of heavy metals in the soil do not exceed the maximum permissible concentration standards: Cu-100, Zn-100, Pb-30, Cd-3.0 mg/kg3. However, there is a decrease in the heavy metals' content with the distance from the track. Differences in ingredient pollution depending on the placement of plantations were established. Thus, the concentration of heavy metals is higher on average from 2.6% to 29.9% in the areas on the windward side compared to the areas on the opposite leeward side. Therefore, forest vegetation intensively retains heavy metals and performs the function of a filter for the natural environment. Research has established a reduction in the parametric impact of railway transport. The level of protective plantings' effect on noise reduction along railway lines was determined. The highest noise levels of electric trains were determined at 95-94 dBA near the track, at a distance of 50-100 m the noise level remained high at 90-82 dBA, and at a distance of 150-200 m the noise ranged from 86 to 65 dBA; the highest noise levels of passenger trains were determined near the track of 92-91 dBA; freight trains ‒ near the track 93-92 dBA. The dependence of the noise level on the structure and condition of the plantations was determined. Thus, it can be stated that the existing forest plantations perform their phytomelioration functions and reduce the negative ingredient and parametric impact of railway transport. In order to protect the territories adjacent to the railway from pollution successfully, it is necessary to monitor transport sections constantly to ensure the sustainable development of the railway industry.

Создание автоматизированной программы по расчету значений целевых показателей для выполнения графика движения

Purpose: Achievement of the autonomy of calculations of target indicators for the implementation of passenger and suburb train schedule, decision-making and operational management, based on obtained calculations. Writing the program "Calculation of Target Indicator Values for Traffic Schedule Implementation" is due to the need to improve process implementation quality and to obtain maximal efficiency of planning and management system in a whole. Methods: Pascal programming language was used to automate the calculation of target indicators. Results: Creation and writing of independent software product with the preservation of organizational and mathematical methods of the work with information for to make managerial decisions. Practical significance: Automated calculation of target indicators for passenger and suburb train traffic schedule implementation will allow passenger complex all participants to consider the automation of the group of the processes related to information collection and processing on the process implementation "Train Traffic Schedule Implementation" through a single window. The proposed software product can be recommended for practical usage in the passenger complex of JSC "Russian Railways".

Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow

The development of some central cities tends to be saturated, so some mega cities try to adopt the express and local mode of the metro. Suburban lines with imbalanced passenger flow between stations will lead to extremely crowded passenger flow in some stations, while scarce passenger flow in other stations. To balance the train’s carrying capacity with the imbalanced passenger flow, this study explores the collaborative optimization of train operation under the new mode of express and local. First, a time-stamped data cropping strategy based on fine-grained time zones as the grid index is developed, which is used to deeply explore the OD spatiotemporal representation of passenger flow correlation mapping mechanism based on multisource data; then, the calculation model of the proportion of trains matching with the OD temporal and spatial characteristics of suburban passenger flow are constructed, and an efficient solution algorithm is developed to solve the problem of interest. Finally, a set of numerical experiments with operation data from Shanghai Metro Line 16 are conducted to verify the performance and effectiveness of the proposed model and algorithm. The experimental results show that the proposed approach can effectively realize the collaborative optimization of passenger OD prediction, train proportion, stop scheme, and travel time, so as to provide decision-making support and method guidance for the optimization of metro organizations in megacities.

The impact of coal trains on PM2.5 in the San Francisco Bay area

Exposure to fine particulate matter (PM2.5) is associated with adverse health effects, including mortality, even at low concentrations. Rail conveyance of coal, accounting for one-third of American rail freight tonnage, is a source of PM2.5. However, there are limited studies of its contribution to PM2.5, especially in urban settings where residents experience higher exposure and vulnerability to air pollution. We developed a novel artificial intelligence-driven monitoring system to quantify average and maximum PM2.5 concentrations of full and empty (unloaded) coal trains compared to freight and passenger trains. The monitor was close to the train tracks in Richmond, California, a city with a racially diverse population of 115,000 and high rates of asthma and heart disease. We used multiple linear regression models controlling for diurnal patterns and meteorology. The results indicate coal trains add on average 8.32 µg/m3 (95% CI = 6.37, 10.28; p < 0.01) to ambient PM2.5, while sensitivity analysis produced midpoints ranging from 5 to 12 µg/m3. Coal trains contributed 2 to 3 µg/m3 more of PM2.5 than freight trains, and 7 µg/m3 more under calm wind conditions, suggesting our study underestimates emissions and subsequent concentrations of coal train dust. Empty coal cars tended to add 2 µg/m3. Regarding peak concentrations of PM2.5, our models suggest an increase of 17.4 µg/m3 (95% CI = 6.2, 28.5; p < 0.01) from coal trains, about 3 µg/m3 more than freight trains. Given rail shipment of coal occurs globally, including in populous areas, it is likely to have adverse effects on health and environmental justice.