JournalTOCs

Public Transport
Journal Prestige (SJR): 0.529

Citation Impact (citeScore): 1
Number of Followers: 18

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1613-7159 - ISSN (Online) 1866-749X
Published by Springer-Verlag

[2469 journals]

Resolution of coupling order and station level constraints in train unit
scheduling
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  Abstract: Train unit scheduling assigns vehicles to cover all trips of a fixed timetable satisfying constraints such as seat demands. With a two-phase approach, this problem is first solved in Phase I as an integer multi-commodity flow problem. Train stations are simplified as single points and coupling orders of train units are left undetermined. In this paper, platforms and their layouts at the stations are restored to complete a fully operable schedule, defined as Phase II. An adaptive approach expanding Phase I to Phase II is proposed. The logistics of (de-)coupling operations, coupling orders and re-platforming are determined in detail to prevent unit blockage where possible, particularly focusing on developing a schedule with conflict-free coupling orders. If unresolvable station level conflicts still exist, the process loops back to Phase I with addressed Phase II constraints to avoid identified conflicts. Thus, the schedule is iteratively improved until it is fully operable.
  PubDate: 2022-05-11
Is the relationship between bus and light rail transit a competition
substitution or a congestion substitution' An empirical study in
Seattle
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  Abstract: Abstract Public transit in Seattle has achieved success, with increases in transit ridership during these years, while most U.S. cities face a decline in transit ridership. It is worth learning the experience from Seattle's transit success, but the causes remain unclear. This study hypothetically attributes this success to a good cooperation between public transit modes and uses quantile regressions to prove this hypothesis. Based on a bus stop ridership of 2988 in 2017, results indicate that the differences between bus stops within light rail transit catchments and outside catchments are significant and prove the relationship as the substitution of light rail transit for bus services. We further identify the situations when substitution happens and find it only happens in areas with high bus ridership, as congestion substitution. Besides, bus rapid ride lines and land-use factors are significantly associated with bus ridership. Conclusively, our study proves that the good cooperation between light-rail transit and bus service and transferring facilities could be a success story in the Seattle public transit service. This study can contribute to policymakers allocating public transit budgets wisely and suggest that a good cooperation between public transit modes can be a potent way to promote public transit ridership.
  PubDate: 2022-04-20
An optimization model for planning limited-stop transit operations
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  Abstract: Abstract Surface transit lines in North America commonly feature a basic service pattern consisting of a single branch of all-stop service, with stops usually tightly spaced. Such a configuration is inefficient for the operator and unattractive for the users, particularly if the prevailing passenger demand is unevenly distributed along the line. In such cases, it is more effective to tailor the scheduled services to passenger demand, both spatially and temporally. Public Transit agencies have increasingly adopted various stop and service pattern strategies in order to provide high-quality services while reducing operating costs. This study is focused on one such strategy, namely limited-stop operation. It proposes a new mathematical programming model to find the best candidate route stops for this strategy to minimize the total passenger travel time. The adopted approach consists of three steps: optimization, post-optimization, and simulation. An agent-based simulation platform, called Nexus, is used to represent real-life operating conditions, generate input data for the optimization model, enable post-optimization pattern recognition for grouping trips, and finally help assess the optimization results and present a best possible strategy. The developed approach is tested in a case study of a transit system in Hamilton, Ontario, Canada. Multiple analysis and algorithm test cases are demonstrated.
  PubDate: 2022-04-08
Understanding the temporal and spatial interactions between transit
ridership and urban land-use patterns: an exploratory study
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  Abstract: Abstract The land-use characteristics of urban areas continually change, and thus the activity patterns of the significant trip generators evolve. Efficient public transit planning needs to perform frequent estimates of the spatio-temporal distribution and dynamics of different activities in urban areas and measure the likely consequences of changes. Automated data collection systems usually collect transit ridership data (e.g., automated passenger count (APC)). Many transit agencies also generate General Transit Feed Specification (GTFS) data and make them publicly available. This study explores the use of APC, GTFS, and land-use data to examine various land-use and transit ridership interactions at the stop, route, and zonal levels using visualization, data mining, and statistical analysis techniques. Results show that transit ridership at the bus stop level gives a better understanding of each bus stop's unique land use. Zonal-level transit ridership patterns reveal the different trip generations and attraction roles of the neighboring land usage. This study could provide additional insights on the interaction between the temporal changes in population from the perspective of transit use and the associated land uses.
  PubDate: 2022-04-08
Segmenting fare-evaders by tandem clustering and logistic regression
models
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  Abstract: Abstract In this study, a tandem clustering is applied on data collected by an Italian public transport company. Three clusters of evader passengers are discovered. Next, for each cluster, the influence of significant determinants in evaluating the chance of being a frequent fare evader is shown by logistic regression models. Members of Cluster 1 are a small segment of choice-workers, who seldom evade fares significantly. Members of Cluster 2 represent a big segment of captive students, who often evade the fare. Members of Cluster 3 are a medium segment of captive unemployed, who always evade the fare. The logistic regression models show that attributes related to the situational factors are significant, and honesty is the common variable that significantly affects the chance of being a frequent fare evader among segments. These outcomes are relevant and useful for both research and practice. Indeed, this paper contributes to the empirical understanding of the determinants of being a frequent fare evader for segments a posteriori selected. Moreover, it helps PTCs to better understand how some segments differ from each other.
  PubDate: 2022-04-08
Analyzing public transport in the city of Buenos Aires with MobilityDB
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  Abstract: Abstract The General Transit Feed Specification (GTFS) is a data format widely used to share data about public transportation schedules and associated geographic information. GTFS comes in two versions: GTFS Static describing the planned itineraries and GTFS Realtime describing the actual ones. MobilityDB is a novel and free open-source moving object database, developed as a PostgreSQL and PostGIS extension, that adds spatial and temporal data types along with a large number of functions, that facilitate the analysis of mobility data. Loading GTFS data into MobilityDB is a quite complex task that, nevertheless, must be done in an ad-hoc fashion. This work describes how MobilityDB is used to analyze public transport mobility in the city of Buenos Aires, using both, static and real-time GTFS data for the Buenos Aires public transportation system. Visualizations are also produced to enhance the analysis. To the authors’ knowledge, this is the first attempt to analyze GTFS data with a moving object database.
  PubDate: 2022-03-01
  DOI: 10.1007/s12469-022-00290-8
Measurement and classification of transit delays using GTFS-RT data
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  Abstract: Abstract This paper presents a method for extracting transit performance metrics from a General Transit Feed Specification’s Real-Time (GTFS-RT) component and aggregating them to roadway segments. A framework is then used to analyze this data in terms of consistent, predictable delays (systematic delays) and random variation on a segment-by-segment basis (stochastic delays). All methods and datasets used are generalizable to transit systems which report vehicle locations in terms of GTFS-RT parameters. This provides a network-wide screening tool that can be used to determine locations where reactive treatments (e.g., schedule padding) or proactive infrastructural changes (e.g., bus-only lanes, transit signal priority) may be effective at improving efficiency and reliability. To demonstrate this framework, a case study is performed regarding one year of GTFS-RT data retrieved from the King County Metro bus network in Seattle, Washington. Stochastic and systematic delays were calculated and assigned to segments in the network, providing insight to spatial trends in reliability and efficiency. Findings for the study network suggest that high-pace segments create an opportunity for large, stochastic speedups, while the network as a whole may carry excessive schedule padding. In addition to the static analysis discussed in this paper, an online interactive visualization tool was developed to display ongoing performance measures in the case study region. All code is open-source to encourage additional generalizable work on the GTFS-RT standard.
  PubDate: 2022-02-23
  DOI: 10.1007/s12469-022-00291-7
Revisiting the richness of integrated vehicle and crew scheduling
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  Abstract: Abstract The last decades have seen a considerable move forward regarding integrated vehicle and crew scheduling in various realms (airline industry, public transport). With the continuous improvement of information and communication technology as well as general solvers it has become possible to formulate more and more rich versions of these problems. In public transport, issues like rostering, delay propagation or days-off patterns have become part of these integrated problems. In this paper we aim to revisit an earlier formulation incorporating days-off patterns and investigate whether solvability with standard solvers has now become possible and to which extent the incorporation of other aspects can make the problem setting more rich and still keep the possible solvability in mind. This includes especially issues like delay propagation where in public transport delay propagation usually refers to secondary delays following a (primary) disturbance. Moreover, we investigate a robust version to support the claim that added richness is possible. Numerical results are provided to underline the envisaged advances.
  PubDate: 2022-02-23
  DOI: 10.1007/s12469-022-00292-6
Decoding customer experiences in rail transport service: application of
hybrid sentiment analysis
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  Abstract: Abstract The paper aims to enhance customers’ satisfaction levels by identifying improvements in the service quality of the rail transport industry in developing countries such as India. A multi-algorithmic combination of a LEXICON analysis and a Naïve Bayes machine learning hybrid approach to sentiment analysis is performed for identifying passengers’ opinions on the services provided by Indian Railways. Inputs were gathered from the Twitter microblogging platform. Data analysis reveals that the ticket reservation and refund process, delay in operational activities, and abhorrent behavior of staff were crucial areas in which Indian Railway service needs improvement. The study imparts a conceptual methodology/process for implementing a hybrid multi-algorithmic LEXICON and machine learning techniques in sentiment analysis. The model proves to take less time to process, train, and test data than stand-alone LEXICON or machine learning-based approaches. Managers, practitioners, and researchers may use this approach to understand customer experience especially in rail transportation but also across hospitality sectors such as hotels, restaurants, education, and hospitals.
  PubDate: 2022-02-22
  DOI: 10.1007/s12469-021-00289-7
Crime and safety in transit environments: a systematic review of the
English and the French literature, 1970–2020
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  Abstract: Abstract This article reviews five decades of English and French literature on transit safety in several major databases, with the focus on Scopus and ScienceDirect. The review explores the nature and frequency of transit crime and passengers’ safety perceptions in transport nodes and along the trip using bibliometric analysis and a systematic review of the literature. The number of retrieved documents was 3137, and 245 were selected for in-depth analysis. Transit safety as a research area took off after the mid-1990s and peaked after the 2010s. The body of research is dominated by the English-language literature (mostly large cities), with a focus on the safety of rail-bound environments and examples of interventions to improve actual and perceived safety for public transportation (PT) users. Highlighting the importance of transit environments along the whole trip, the article also helps advocate for more inclusion of passengers’ safety needs and the involvement of multiple stakeholders in implementing PT policies.
  PubDate: 2022-01-31
  DOI: 10.1007/s12469-021-00265-1
Optimizing train stopping patterns for congestion management
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  Abstract: Abstract In this paper, we optimize train stopping patterns during the morning rush hour in Japan. Since trains are extremely crowded, we need to determine stopping patterns based not only on travel time but also on congestion rates of trains. We exploit a Wardrop equilibrium model to compute passenger flows subject to congestion phenomena and present an efficient local search algorithm to optimize stopping patterns which iteratively computes a Wardrop equilibrium. The framework of the proposed algorithm is extended to solve the problem of optimizing the number of services for each train type. We apply our algorithms to railway lines in Tokyo including the Keio Line with six types of trains and demonstrate that we succeed in relaxing congestion.
  PubDate: 2021-11-10
  DOI: 10.1007/s12469-021-00286-w
Mode boundaries of automated metro and semi-rapid rail in urban transit
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  Abstract: Abstract Our research question is to what extent, and under what circumstances, full automation in metro lines defines transit mode boundaries with respect to semi-rapid transit. The modeling approach is based on micro-economic appraisal. Automation, beside changing the investment and operation and maintenance cost profiles of metro lines, can improve some aspects of the user experience. The low marginal cost of frequency possible with automated metro may unlock both users’ benefits via reduced waiting times and crowding, and operator’s savings via shorter trains and smaller platforms and stations. We show how the user’s travel time components are structurally different under several configurations. In particular, we highlight the critical role that different demand and alignment patterns play in the mode comparison.
  PubDate: 2021-11-08
  DOI: 10.1007/s12469-021-00287-9
A survey on the transit network design and frequency setting problem
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  Abstract: Abstract Appropriate public transport systems are crucial in modern cities. Given the high costs that they represent and the impact they have on people’s lives, effective tools are required to support their design. With this in mind, the Transit Network Design problem (TNDP) and the Transit Network Design and Frequency Setting problem (TNDFSP) have been extensively studied in the domain of Operations Research. However, due to the complexity of these problems, multiple simplifications are typically made when modelling and designing solution algorithms. Therefore, still no optimization techniques are available to address these problems in practice. Moreover, different studies address different versions of the problem, with varying assumptions and constraints, complicating the comparison of results or solution approaches. This paper presents an extensive survey of studies addressing the TNDP and the TNDFSP. It discusses the different assumptions, constraints, objectives, solution approaches and testing instances that have been considered in the literature. Furthermore, a detailed analysis is done regarding the case studies considered for the TNDFSP. Moreover, the variants of the passenger assignment subproblem that have been applied within the TNDP and the TNDFSP are discussed. The analysis shows that extensive research has been done regarding these problems. However, it also identified the significant gap that still exists between theory and practice, even in the studies addressing case studies.
  PubDate: 2021-10-18
  DOI: 10.1007/s12469-021-00284-y
The influence of vicinity to stations, station characteristics and
perceived safety on public transport mode choice: a case study from
Copenhagen
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  Abstract: Abstract The perception of safety within the public transport system is of high importance for passengers according to multiple passenger satisfaction surveys. However, among the many studies of public transport mode choice, little focus has been on the influence of safety perceptions. This study contributes to existing literature by specifically investigating the influence of perceived safety on public transport mode choice using a large-scale multimodal travel survey with 17,355 respondents and 42,438 trips from the Greater Copenhagen area. This made it possible to analyse safety at stations while still taking into account other main determinants of public transport usage. The study also includes walking distances to various public transport stops, e.g. metro, suburban and regional train stations, and bus stops, hence taking into account possible differences in attitudes towards different public transport modes. The results of a logistic regression confirm the hypothesis of lower perceived safety at stations being negatively correlated with public transport mode choice, but still to a smaller extent than that of service characteristics in terms of service frequency. The study also revealed that travellers perceive metro and suburban rail services as more attractive, as compared to local rail and bus services. Hence, vicinity to such stations was associated with a higher likelihood of choosing public transport, thus highlighting the importance of close vicinity to high-class services being of the highest importance for attracting passengers to public transport while perceived safety being of minor, yet significant, importance.
  PubDate: 2021-10-06
  DOI: 10.1007/s12469-021-00285-x
Effects of system configurations of automated fare collection on transit
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  Abstract: Abstract Automated fare collection (AFC) systems such as smart cards are becoming increasingly popular among transit agencies worldwide. Two main configurations of AFC systems can be found, characterized by whether users are required to scan their cards at the beginning of their trips (i.e., entry-only system) or both at the beginning and end of their trips (i.e., entry–exit system). Recently, there has been growing interest in implementing the latter configuration in order to provide more equitable fare structures that charge users based on distance, while arguably providing more accurate data for an origin-destination analysis of users. Therefore, this study explores the spatial and temporal differences in transit users’ origin-destination estimations that are based on the two AFC system configurations. To achieve this goal, it uses AFC system data collected from GO Transit, the operator of the regional commuter rail and bus systems in the Greater Toronto and Hamilton Area (GTHA). A comprehensive model was developed which suggests that the entry–exit AFC system configuration helps in estimating about 14% more trips than an entry-only AFC system configuration; the latter uses a set of common assumptions that are normally employed by researchers in estimating users’ destinations. Spatial, temporal and mode related differences between the two system estimations were also found. This paper offers policy makers and planners a better understanding of the possible benefits/impacts of implementing entry–exit systems vs. entry-only systems on transit users’ origin-destination estimations.
  PubDate: 2021-10-06
  DOI: 10.1007/s12469-021-00283-z
Advanced systems in public transport, with a touch of data
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  PubDate: 2021-10-01
  DOI: 10.1007/s12469-021-00288-8
Unsupervised approach towards analysing the public transport bunching
swings formation phenomenon
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  Abstract: Abstract We perform an analysis of public transport data from The Hague, the Netherlands, combined from three sources: static network information, automatic vehicles location and automated fare collection data. We highlight the effect of bunching swings, and show that this phenomenon can be extracted using unsupervised machine learning techniques, namely clustering. We also show the correlation between bunching rate and passenger load, and bunching probability patterns for working days and weekends. We present the approach for extracting isolated bunching swings formations (BSF) and show different cases of BSFs, some of which can persist for a considerable time. We applied our approach to the tram line 1 of The Hague, and computed and presented four different patterns of BSFs, which we name “high passenger load”, “whole route”, “evening, end of route”, “long duration”. We analyse each bunching swings formation type in detail.
  PubDate: 2021-10-01
  DOI: 10.1007/s12469-020-00251-z
A hybrid stochastic approach for offline train trajectory reconstruction
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  Abstract: Abstract The next generation of railway systems will require more and more accurate information for the planning of rail operation. These are essential for the introduction of automatic processes of an optimized traffic planning, the optimal use of infrastructure capacity and energy, and, overall, the introduction of data-driven approaches into rail operation. Train trajectories collection constitutes a primary source of information for offline procedures such as timetable generation, driving behaviour analysis and models’ calibration. Unfortunately, current train trajectory data are often affected by measurement errors, missing data and, in many cases, incongruence between dependent variables. To overcome this problem, a trajectory reconstruction problem must be solved, before using trajectories for any further purpose. In the present paper, a new hybrid stochastic trajectory reconstruction is proposed. On-board monitoring data on train position and velocity (kinematics) are combined with data on power used for traction and feasible acceleration values (dynamics). A fusion of those two types of information is performed by considering the stochastic characteristics of the data, via smoothing techniques. A promising potential use is seen especially in those cases where information on continuous train positions is not available or unreliable (e.g. tunnels, canyons, etc.).
  PubDate: 2021-10-01
  DOI: 10.1007/s12469-020-00230-4
Evaluation of bus bridging scenarios for railway service disruption
management: a users’ delay modelling tool
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  Abstract: Abstract Unexpected transit service disruptions degrade the quality of service provided to the public. Bus bridging is considered a key response strategy used to handle metro service interruptions, where buses are retracted from scheduled services and deployed to offer shuttle services along disrupted segments. Most transit agencies rely on ad-hoc approaches (based on experience) to determine which buses should be dispatched from the scheduled services, with little (or no) consideration of the impacts on users’ delays. This paper presents a practical tool to estimate the total users’ delay associated with a user-specified bus bridging plan. The tool is based on deterministic queueing theory. The total delay is composed of two components; direct delays of affected metro passengers along the disrupted segment and indirect delays of bus riders on the routes from which shuttle buses are dispatched. The tool utilizes several input data, including travel times, train load information, boarding and alighting passenger counts, bus frequencies, and routes’ cycle times. It provides transit practitioners and operational managers with a valuable instrument for evaluating different bus bridging scenarios. A case study of the transit network in Toronto is used to illustrate the tool’s functionality.
  PubDate: 2021-10-01
  DOI: 10.1007/s12469-020-00238-w
Insights into factors affecting the combined bicycle-transit mode
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  Abstract: Abstract This paper considers an increasingly popular, sustainable multimodality: the combination of bicycle and transit. The flexibility of the bicycle combined with the speed and comfort of good transit can be a highly competitive alternative to the car. This study shows that many factors influence the uptake and attractiveness of the bicycle-transit combination. An in-depth literature review resulted in over thirty unique factors: six transit-related factors, twenty-first-last mile factors and fifteen context-related factors. All these factors might influence the demand for this ‘new’ mode positively or negatively. An exploratory choice modelling study showed the weights of some factors that Dutch bicycle-train users consider when choosing to cycle to a railway station. The weights showed that people are especially willing to cycle to a station with longer bicycle time (or bicycle parking time) when by doing so they can avoid a transfer in their train trip thereafter. The willingness to pay found were €0.11 for 1 min less bicycle time, €0.08 for a minute less train time, €0.11 for a minute of less time to park and €0.60 per avoided transfer. These kinds of insights give the bicycle and transit sector valuable information to be used in modelling multimodality and cost–benefit analyses, thereby supporting improved decision making and integrated design of bicycle and transit networks.
  PubDate: 2021-10-01
  DOI: 10.1007/s12469-020-00240-2