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Reliability is a key factor in public transportation systems, significantly influencing passenger satisfaction and their perceptions of service quality. Therefore, measures of Travel Time Reliability (TTR), which help quantify unexpected delays, are essential for effectively planning and managing travel times. This research aims to provide a prediction model for standard deviation of travel time, as an indicator of TTR, on an urban bus route using Automatic Vehicle Location data as well as evaluating and comparing the results of ARIMA and LSTM models. Our research contributes to the existing body Ofliterature by considering the effect of a wide range of predictor variables which were categorized by route characteristics, weather condition, congestion, and temporal feature, on bus TTR, which received less attention in previous studies. The results show that LSTM is an efficient and accurate TTR predictive model than ARIMA, with an accuracy of about 87%. In addition, the LSTM model exhibits lower mean absolute percentage error (40%), mean square error (52.08%), and root mean square error (39.70%) compared to the corresponding values in the ARIMA model. Also, the congestion, weather condition, and holidays are the key variables in increasing the accuracy of LSTM model, respectively. Our findings provide insights to facilitate the decision-making of managers and planners in public transportation planning sector to improve transit reliability and passengers' satisfaction level. [ABSTRACT FROM AUTHOR]

As the air–rail integration continues to emerge around the globe, the successful and maintainable implementation of such schemes can be influenced by many factors within administrative, social, infrastructural, and economic aspects. With the existing airport rail link system that shifted from air–rail integration at beginning to air–rail cooperation at present, this work aims to assess the success factors of air–rail integration development in Thailand and evaluate the partnership level required to achieve a long-term and indefinite horizon of relationship based on an ongoing airport rail link project in the country. The factor assessment results from using fuzzy analytical hierarchy process (AHP) revealed different perspectives from regulators and operators, while directing the high influence of administrative, economic, and infrastructural factors. The partnership evaluation suggested the highest level of partnership; although, the operators still express doubt whether the competitive advantages incurred from the partnership and the partnership itself would be sustainable. [ABSTRACT FROM AUTHOR]

Employment center locations, the jobs-housing relationship, and commuting patterns are inextricably connected in a megacity that heavily relies on the urban transit system to shuttle commuters. Using a transit smartcard dataset, a machine learning method is employed as a preliminary filter to sift through commuter flows and isolate key data, then kernel density and topological analysis methods are implemented to delve into the primary research questions, providing a detailed look at how these patterns unfold. The results show that transit commuting behavior in Shanghai is a dispersal activity based on multi-level employment centers characterized as hierarchical, boundary-clear, and functionally oriented. Further analysis illustrates that the intensity of commuting linkages correlates with the employment center level, shaping a hybrid pattern that couples a core-periphery pattern with a spoke-hub pattern. The commuting network connections present corridor, neighborhood, capture, and replacement features, highlighting the importance of employment centers in shaping commuting patterns. From a daily flow perspective, these findings echo the central place theory and verify that the employment center distribution in Shanghai is also multi-layered and well-nested, forming the basis for commuting links. Policy implications are provided for polycentric megacities with progressively sophisticated urban transit systems. [ABSTRACT FROM AUTHOR]

To alleviate peak-hour congestion in urban rail transit, this study proposes a new off-peak fare discount strategy to incentivize passengers to shift their departure time from peak to off-peak hours. Firstly, a questionnaire survey of Shanghai metro passengers is conducted to analyze their willingness to change departure time under different fare strategies. Secondly, based on the survey results, a time-differentiated fare discount model is constructed, considering both the company's revenue and passengers' travel benefits, and with the optimization objective of achieving balanced peak-hour and off-peak-hour train loads throughout the day. Subsequently, a genetic algorithm with nested fmincon functions is designed and combined with the actual data of Shanghai rail transit line 9 for arithmetic analysis. Finally, the effectiveness of the model is validated using the survey data. The research results show that the off-peak fare discount strategy can incentivize 6.88% of passengers traveling in the morning peak and 6.66% of passengers traveling in the evening peak to shift to off-peak travel. This research provides theoretical support and decision-making guidance for implementing time-differentiated pricing in urban rail transit systems. [ABSTRACT FROM AUTHOR]

Abstract To alleviate peak-hour congestion in urban rail transit, this study proposes a new off-peak fare discount strategy to incentivize passengers to shift their departure time from peak to off-peak hours. Firstly, a questionnaire survey of Shanghai metro passengers is conducted to analyze their willingness to change departure time under different fare strategies. Secondly, based on the survey results, a time-differentiated fare discount model is constructed, considering both the company’s revenue and passengers’ travel benefits, and with the optimization objective of achieving balanced peak-hour and off-peak-hour train loads throughout the day. Subsequently, a genetic algorithm with nested fmincon functions is designed and combined with the actual data of Shanghai rail transit line 9 for arithmetic analysis. Finally, the effectiveness of the model is validated using the survey data. The research results show that the off-peak fare discount strategy can incentivize 6.88% of passengers traveling in the morning peak and 6.66% of passengers traveling in the evening peak to shift to off-peak travel. This research provides theoretical support and decision-making guidance for implementing time-differentiated pricing in urban rail transit systems.

As the air–rail integration continues to emerge around the globe, the successful and maintainable implementation of such schemes can be influenced by many factors within administrative, social, infrastructural, and economic aspects. With the existing airport rail link system that shifted from air–rail integration at beginning to air–rail cooperation at present, this work aims to assess the success factors of air–rail integration development in Thailand and evaluate the partnership level required to achieve a long-term and indefinite horizon of relationship based on an ongoing airport rail link project in the country. The factor assessment results from using fuzzy analytical hierarchy process (AHP) revealed different perspectives from regulators and operators, while directing the high influence of administrative, economic, and infrastructural factors. The partnership evaluation suggested the highest level of partnership; although, the operators still express doubt whether the competitive advantages incurred from the partnership and the partnership itself would be sustainable.

The object of the research is the urban transport quality. The problem to be solved in the course of the study to optimize current planning systems while reducing human impact on managing daily disruptions that affect urban transport quality and citizen well-being. This will allow all buses to run on time and all users to travel in good conditions. This study aims to address the most critical problems of the growing demand for public transportation, the inability to meet these demands, and the approved ineffectiveness of existing planning. In the course of the research, it is proposed to apply a model for managing daily disturbances that used a developed algorithm based on four major aspects. These aspects include admitting all actors into the system, collecting real-time data, processing data to manage their exploitation and destruction as quickly as possible, and even achieving an ideal operational strategy to handle potential disruptions to the system. Authors’ proposal for achieving this goal involves two types of hardware and software architectures, taking into consideration the use of modern technological innovations and their potential application. While ensuring a good flow of information, which contributes greatly to the proper functioning of the network and even to the proper management of disturbances in real-time. To validate this work, it is possible to simulate an application of this model on an existing situation of a transport line in the city of Constantine (Algeria), already studied in a previous study to see the evolution of the situation in terms of quality reflected by the journey time. As a result of the research, it is shown that positive feedback and improvement were observed after the first simulation of the application. This result only encourages the application of this proposed approach, which could ensure a better quality of service offered to the users. In the future, the application of this proposed approach could be the revolution of the field of urban transport in Algeria, which is the pillar of the viability, productivity, and efficiency of a city and the well-being of the citizens. [ABSTRACT FROM AUTHOR]

This study employs the fundamental concept of the American Customer Satisfaction Index (ACSI) model to explore the factors influencing passengers' satisfaction with monorail service in Kuala Lumpur, Malaysia and their reuse intention. The study tests the hypotheses on 417 monorail passengers using a hybrid structural equation modelling based on parameter estimation of partial least squares (PLS-SEM) and an artificial neural network (ANN) method to estimate the proposed model. The results showed that the proposed model explains 70.4% and 59.5% of the variance in passenger satisfaction with the monorail service and reuse intention. The PLS-SEM results for Stage 1 showed that perceived quality and perceived value have a statistically significant influence on passenger satisfaction. Furthermore, all critical factors in the output from Stage 1 were used as the input in the ANN model to overcome the simplistic nature of the SEM model. The results for the ANN model (Stage 2) showed that perceived quality is the most crucial predictor of passenger satisfaction with the monorail service, followed by perceived quality. The outcomes of this study can help service providers, policymakers, and planners develop effective strategies for enhancing user satisfaction and improving monorail ridership. [ABSTRACT FROM AUTHOR]

The flourishing of transit art globally reflects a widespread belief in the power of aesthetic practices to promote infrastructural and civic revitalisation. This article analyses how transit art engages spaces and practices of publicness and how art explores ideas of mobility in Toronto. It argues that while arts are frequently deployed to reproduce status quo relations of power and to bolster elite and exclusionary forms of urbanisation, they can also work to challenge these. Through the notion of infrastructural citizenship, I show how arts can unsettle grounds of public space and public life and illuminate the contentious relations that cohere in public transit space. Overall, I claim that transit networks are a key platform through which the politics of public art are staged and that despite existing constraints, there are many affordances for transit art to critically intervene into neoliberal urban processes. [ABSTRACT FROM AUTHOR]

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Introduction. Current methods for determining passenger ridership, due to their complexity and limited efficiency, do not allow monitoring transport demand at the proper level (in terms of comprehensiveness and continuity). Nowadays, technologies based on the collection, integration and analysis of big data (Urban computing, Big data, Internet of things) are used to create effective solutions in many aspects of our lives (including for urban transit).Materials and methods. Within the framework of this approach, a methodology for determining the correspondence of transit passengers from the operations of validating any kind of electronic travel tickets: smart cards, transport cards, magnetic cards has been developed. Each operations details are recorded in the Automated Fare Collection (AFC) system during the validation.This methodology based on the definition and evaluation the set of acceptable options of passenger trips sequences, which form the passenger correspondence, taking into account many factors that effect on the route choice by a passenger. For example, in contrast to previous studies, the practice of paying for trip at any point on the route, not necessarily immediately after boarding the vehicle, was taken into account.Results. It was proved that passenger correspondence calculated using the developed methodology statistically corresponds to the general set of transit passenger ridership within acceptable errors. The chaacteristics of transit demand is provided in the results.Discussion and conclusion. The application of the developed methodology makes it possible to organize continuous monitoring of passenger flows, technical and operational indicators of the functioning of transit system and thus implement the concept of sustainable development of public transport by designing public transit supply that meets demand.

High-profile architecture and design, alongside integrated arts and cultural programming are now ubiquitous features of public transit networks. This article considers how and why transit-based arts and cultural programmes are proliferating globally as well as the impact of these programmes on transit and urban dynamics. Through critically analysing the discourses surrounding different transit art initiatives and the institutional structures which support them, this article shows how transit art is used today for varied – and often contradictory – ends. Based on this, it argues that we should not uncritically celebrate the rise of transit art as an unmitigated civic good. Rather, we must situate the rise of transit art within a political and aesthetic economy in which art has become 'expedient', and contend with the way transit art is implicated in elite, exclusionary and unsustainable processes of urbanisation. [ABSTRACT FROM AUTHOR]

This study employs the fundamental concept of the American Customer Satisfaction Index (ACSI) model to explore the factors influencing passengers’ satisfaction with monorail service in Kuala Lumpur, Malaysia and their reuse intention. The study tests the hypotheses on 417 monorail passengers using a hybrid structural equation modelling based on parameter estimation of partial least squares (PLS-SEM) and an artificial neural network (ANN) method to estimate the proposed model. The results showed that the proposed model explains 70.4% and 59.5% of the variance in passenger satisfaction with the monorail service and reuse intention. The PLS-SEM results for Stage 1 showed that perceived quality and perceived value have a statistically significant influence on passenger satisfaction. Furthermore, all critical factors in the output from Stage 1 were used as the input in the ANN model to overcome the simplistic nature of the SEM model. The results for the ANN model (Stage 2) showed that perceived quality is the most crucial predictor of passenger satisfaction with the monorail service, followed by perceived quality. The outcomes of this study can help service providers, policymakers, and planners develop effective strategies for enhancing user satisfaction and improving monorail ridership.

Mass transit systems, including subways and buses, are useful environments for studying the urban microbiome, as the vast majority of populations in urban areas use public transportation. Microbial communities in urban environments include both human- and environment-associated bacteria that play roles in health and pathogen transmission. In this study, we used shotgun metagenomic sequencing to profile microbial communities sampled from various surfaces found in subway stations and bus stops within the Seoul mass transit system. The metagenomic approach and network analysis were used to investigate broad-spectrum antibiotic resistance genes (ARGs) and their co-occurrence patterns. We uncovered 598 bacterial species in 76 samples collected from various surfaces within the Seoul mass transit system. All samples were dominated by the potential human pathogen Salmonella enterica (40 %) and the human skin bacterium Cutibacterium acnes (19 %). Significantly abundant biomarkers detected in subway station samples were associated with bacteria typically found in the human oral cavity and respiratory tract, whereas biomarkers detected in bus stop samples were associated with bacteria commonly found in soil, water, and plants. Temperature and location had significant effects on microbial community structure and diversity. In total, 41 unique ARG subtypes were identified, associated with single-drug or multidrug resistance to clinically important and extensively used antibiotics, including aminoglycosides, carbapenem, glycopeptide, and sulfonamides. We revealed that Seoul subway stations and bus stops possess unique microbiomes containing potential human pathogens and ARGs. These findings provide insights for refining location-specific responses to reduce exposure to potentially causative agents of infectious diseases, improving public health.

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modeling Crew Assignments for Urban Transport Services Using Differentiated Flows Public transit agencies need to judiciously deploy their limited crew members to operate numerous daily scheduled services, while meeting duty and working time regulations for each crew member. Since crew costs account for a large portion of the organizations' operating expenses, minimizing the total crew and transfer costs is very important. But, with hundreds of daily trips and millions of possible crew itineraries, optimizing trip-to-crew assignment decisions is challenging. In "Crew Assignment with Duty Time Limits for Transport Services: Tight Multicommodity Models," Balakrishnan, Mirchandani, and Lin propose a novel integer optimization model that represents itineraries as multicommodity flows, differentiated by first trip and depot, to capture the duty time limits and incorporate additional requirements such as selecting equitable schedules. The authors show that this compact model can be tighter than previous formulations, further strengthen the model, and propose a restricted optimization approach combined with an optimality test to generate near-optimal solutions quickly. Extensive computational tests using well-known and real-life problem instances show that the proposed model and solution approach can be very effective in practice. Crew costs account for a significant portion of the operating expenses for transportation service providers, and so utilizing crews effectively is an important priority for these organizations. This paper addresses the core problem of assigning crews to urban transit and other scheduled transportation services at minimum total cost for crew usage, assignment, and transfers, taking into account crew work rules that limit their duty and working times. We propose a new multicommodity flow model with polynomial number of variables and constraints that is well suited to capture these work rules. This model can also readily incorporate additional desired features of crew assignments, such as balancing task assignments across crew members. It is more compact than previous flow-based and set partitioning models that have exponential constraints or variables. When work rules impose only duty time restrictions, our model is at least as tight as these previous models and can be strictly tighter than single-commodity models. We develop several classes of valid inequalities to further strengthen our model and discuss how to exploit any limits on working time to reduce model size and tighten the constraints. The model is easy to implement and apply, without requiring specialized decomposition procedures. To accelerate computational performance for large problems, we propose an effective optimization-based approach that entails first solving a restricted problem and then applying an optimality test to eliminate variables. We demonstrate the effectiveness of our modeling approach by applying it to several large-scale problem instances from the literature, solving most problems within a few minutes using a standard solver. [ABSTRACT FROM AUTHOR]

The Taipei Mass Rapid Transit (MRT) System is instrumental to both the reconstruction of a collective identity and the development of a renewed political subjectivity, with which the Taiwanese establish themselves as autonomous, law-abiding citizens vis-á-vis a historically repressive state on the one hand, and enlightened, worthy members in the league of the world's urban civilizations on the other. The rescaling of the world economy from the scale of nations to one with an increasingly glocalized configuration has enabled the possibility of scale jumping that allows Taipei the city to stand in for Taiwan the nation, thus helping Taiwan break through its isolation and increase its international visibility. Under this circumstance, the civility displayed on the Taipei MRT takes on the significance of an act of performativity. It has come to signify the Taiwanese people's belonging, in the dual sense of both 'be-ing' in a social complex with fellow citizens and 'longing' for an identification of oneself in a particular historical present. However, the continuing controversies regarding MRT guidelines also indicate that the rights and responsibilities are not always understood to be equal among individual citizens. The process of civic subject formation is contentious and ongoing. [ABSTRACT FROM AUTHOR]

San Francisco’s public transportation system is the slowest major urban transit system in the United States and has one of the worst on-time performance rates. This paper examines how these problems with time—slowness and lateness—are constructed in public discourse and mobilized in labor disputes with the drivers who operate the transit system. Demands for faster moving and more timely transit lead to the implementation and enforcement of impossible-to-meet schedules, and political economic logics configure fault for the time problems in the work practices and work ethics of the transit drivers. Disputes about the transit system’s slow speeds and lateness intensify political opposition between public workers and the publics they serve, and reveal shifting conceptions of the public good. I argue that morally infused understandings of time and timeliness enable a neoliberal remaking of the transit system, its workers, and its publics.

Gelişmekte olan ülkelerde kentiçi toplu taşıma sistemleri arasında en yaygın tür olan otobüs taşımacılığının verimliliğini arttırmaya yönelik çalışmalar son yıllarda artmaktadır. Otobüs sitemlerinin performansının ele alındığı birçok çalışmada, kullanıcı ve işletmeci faydalarını eniyileyen yaklaşımlar üzerinde durulmaktadır. Bu çalışmada, kentiçi otobüs ağlarındaki sefer sıklıklarını eniyileyen iki-seviyeli bir simülasyon/optimizasyon modeli geliştirilmektedir. Üst seviyede, işletmeci ve kullanıcı maliyetlerini temsil eden bir amaç fonksiyonunun çözümü için sezgisel Armoni Araştırması (AA) optimizasyon tekniği tabanlı bir model önerilmektedir. Alt seviyede ise talebin toplu taşıma ağına dağılımını temsil eden toplu taşıma ataması problemi çözülmektedir. Önerilen modelde, aktarma bekleme sürelerinin kesin hesabı için zaman çizelgesi tabanlı toplu taşıma ataması yaklaşımı kullanılmakta ve toplu taşıma ataması problemi logit tabanlı bir modele dayalı olarak VISUM yazılımı ile çözülmektedir. Geliştirilen model, toplu taşıma ağ tasarımı çalışmalarında yaygın olarak kullanılan bir test ağına uygulanmıştır. Sonuçlar, AA tabanlı modelin sefer sıklığı optimizasyonu probleminin çözümünde etkin olarak kullanılabileceğini ortaya koymuştur.

Gelişmekte olan ülkelerde kentiçi toplu taşıma sistemleri arasında en yaygın tür olan otobüs taşımacılığının verimliliğini arttırmaya yönelik çalışmalar son yıllarda artmaktadır. Otobüs sitemlerinin performansının ele alındığı birçok çalışmada, kullanıcı ve işletmeci faydalarını eniyileyen yaklaşımlar üzerinde durulmaktadır. Bu çalışmada, kentiçi otobüs ağlarındaki sefer sıklıklarını eniyileyen iki-seviyeli bir simülasyon/optimizasyon modeli geliştirilmektedir. Üst seviyede, işletmeci ve kullanıcı maliyetlerini temsil eden bir amaç fonksiyonunun çözümü için sezgisel Armoni Araştırması (AA) optimizasyon tekniği tabanlı bir model önerilmektedir. Alt seviyede ise talebin toplu taşıma ağına dağılımını temsil eden toplu taşıma ataması problemi çözülmektedir. Önerilen modelde, aktarma bekleme sürelerinin kesin hesabı için zaman çizelgesi tabanlı toplu taşıma ataması yaklaşımı kullanılmakta ve toplu taşıma ataması problemi logit tabanlı bir modele dayalı olarak VISUM yazılımı ile çözülmektedir. Geliştirilen model, toplu taşıma ağ tasarımı çalışmalarında yaygın olarak kullanılan bir test ağına uygulanmıştır. Sonuçlar, AA tabanlı modelin sefer sıklığı optimizasyonu probleminin çözümünde etkin olarak kullanılabileceğini ortaya koymuştur.

Reasonable bus timetable can reduce the operating costs of bus company and improve the quality of bus services. A data-driven method is proposed to optimize bus timetable in this study. Firstly, a bi-objective optimization model is constructed considering minimize the total waiting time of passengers and the departure times of bus company. Then, Global Positioning System (GPS) trajectories of buses and passenger information collected from Smart Card are fused and applied to calculate the key parameters or variables in optimization model, including time-dependent travel time, bus dwell time and passenger volume. Finally, by adopting a specific coding scheme, an improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is designed to quickly search Pareto optimal solutions. Furthermore, an experiment is conducted in Beijing city from one bus line to validate the effectiveness of the proposed method. Comparing with empirical scheduling method and traditional single-objective optimization base on GA, the results show that the proposed model could quickly provide high-quality and reasonable timetable schemes for the administrator in urban transit system. [ABSTRACT FROM AUTHOR]

This research seeks to explain patterns of capital investment and operating expenses for urban transit systems in the United States. We isolate supply factors including urban scales, urban spatial form and financial capacity. Individual and group transit demands are accounted for by social and demographic characteristics including education level, immigrant populations, poverty levels, senior population and race. The results demonstrate that transit investments are super-linear to population, directly contradicting predictions of Bettencourt's popular urban scale theory. Transit expenses are explained primarily by urban scales, urban spatial form and financial capacity, but demand forces such as poverty, car usage and political ideology have strong effects as well. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Arquitectura (1657-0308) is the property of Universidad Catolica de Columbia, Facultad de Arquitectura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Transit Network Design and Frequency Setting Problem (TNDFSP) can be defined as the creation of effective routes in a public transport network and the determination of relevant frequencies. Generally, the TNDFSP problem is in the same category as the Traveling Salesman Problem (TSP), which is known to be a non-deterministic polynomial-period (NP-hard) difficult problem. This study consists of two stages: first, the design of a public transport network with an evolutionary optimization technique – the Intelligent Water Drops (IWD) algorithm – based on the TSP and the determination of relevant frequencies; and second, the assignment of passengers to designated routes. All decisions related to public transport network design may be evaluated by considering environmental costs in relation to passengers, operators and the environment. This study presents an acceptable, constructive and original algorithm. [ABSTRACT FROM AUTHOR]

What's a fair way to pay for urban transportation? Local option sales taxes (LOSTs) for transportation are an increasingly common mechanism for locally financing transportation in the context of declining federal and state funding. LOSTs are typically regressive, raising equity concerns. But their fairness also depends on who benefits from them, based on which projects are funded, where projects are located, and when investments occur. We examine how perceptions of these four dimensions of equity (income, geographic, temporal, and modal) are represented and debated in the ballot arguments for 38 LOST elections in California. We find that measure supporters use subtle language to imply that proposed expenditure plans achieve equity on all dimensions, promising "something for everyone." Measure opponents, by contrast, typically attack specific perceived inequities in proposed expenditure plans. We find that tradeoffs among types of equity debated in ballot arguments frame winners and losers across multiple equity dimensions. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract In this article, the results of the research in a field of which uses active global navigation satellite system (GNSS) geodetic networks for the inventory of geodetic geometric tram tracks are presented. The applied measurement technique has been adapted for the designing of the geometric layout of tram tracks. Several configurations of receivers and settings of an active GNSS networks with the objective to increase the accuracy of positioning and the availability of accurate localization are investigated. The measurement methods are optimized in order to increase the accuracy of determining positions from 3 mm up to 6 mm. Thus, the study of deformations in geometric layouts—according to the authors—is already possible. The implementation techniques of the mobile satellite measurements in a field of tram track inventory process are presented in this article. The course of the measurements and the results of the inventory of the tram system in Gdansk, Poland have been discussed. The results have turned out to be extremely useful for the geometric track layout evaluation. It has been proved that the applied method allows a comprehensive tram network inventory to be performed based on satellite measurements. The presented method is fast and cost-efficient.

This report documents the development of a preliminary specification for a transit bus frontal collision warning system, based on a system engineering approach. The research efforts included: 1) a literature review, 2) detailed analyses of the five-year safety records of a group of California transit properties to identify the causes of their safety problems, 3) an in-depth data collection and analysis from instrumented buses serving San Mateo County, CA, and 4) development and testing of three generations of transit bus frontal collision warning systems, incorporating enhancements to meet the needs identified by the bus drivers using the prototype systems. The analyses of the safety records and the combination of video and engineering data from the instrumented buses provide a uniquely rich pool of data for diagnosing transit bus safety challenges. The prototype warning systems incorporated innovations in signal processing to ensure that warnings are issued with high reliability and low rates of false alerts. Finally, the results of this work led to the definition of a preliminary specification for a frontal collision warning system for subsequent field testing.

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Designing reasonable departure schedule is the key step to realize the urban transit priority. It can not only reduce the operating cost of bus company, but also guarantee convenience for passengers. This paper estimates the travel time between bus stations based on the historical trajectory data of the bus, and then combines the number of passengers get on and off at each station to optimize the departure timetable. In addition, several constraints including actual travel time, limited capacity and arrival time distribution type are considered in the optimization models to effectively and comprehensively estimate the passenger waiting time. Finally, a hybrid algorithm combining Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA) is proposed to search optimal solution in scheduling model. A case study is applied to testify the effectiveness of proposed models. In the experiments, we compare optimization results of proposed method to traditional genetic algorithms, and the results show the superiority and feasibility of the hybrid optimization approach. Highlights • We apply Poisson distribution to determine the passengers waiting time. • An optimization model considering actual travel time, limited capacity and arrival time is proposed. • We propose a hybrid algorithm to generate departure timetable. • The results prove the superiority and feasibility of the proposed optimization method. • We discuss the impact of vehicle resource constraints on the scheduling scheme. [ABSTRACT FROM AUTHOR]

Consider the urban transit "problem." In the 1960s the problem was declining transit patronage. Finances received little discussion because the industry was essentially self-supporting; operating costs were so low that passenger revenues covered costs. In the 1990s "problem" has a whole new meaning: financial deficits. Today, most transit revenue comes from governments, not passengers, and the result is continual fiscal crisis - the search for money to continue the subsidies. The new transit problem grew from our efforts to solve the old one.

Energy conservation is attracting more attention to achieve a reduced lifecycle system cost level while enabling environmentally friendly characteristics. Conventional research mainly concentrates on energy-saving speed profiles, where the energy level evaluation of the timetable is usually considered separately. This paper integrates the train driving control optimization and the timetable characteristics by analyzing the achievable tractive energy conservation performance and the corresponding boundaries. A calculation method for energy efficient driving control solution is proposed based on the Bacterial Foraging Optimization (BFO) strategy, which is utilized to carry out batch processing with timetable. A boundary identification solution is proposed to detect the range of energy conservation capability by considering the relationships with average interstation speed and the passenger volume condition. A case study is presented using practical data of Beijing Metro Batong Line and two timetable schemes. The results illustrate that the proposed optimized energy efficient driving control approach is capable of saving tractive energy in comparison with the conventional traction calculation-based train operation solution. With the proposed boundary identification method, the capability space of the energy conservation profiles with respect to the energy reduction and energy saving rate is revealed. Moreover, analyses and discussions on effects from different passenger load conditions are given to both the weekday and weekend timetables. Results of this paper may assist the decision making of rail operators and engineers by enhancing the cost effectiveness and energy efficiency.

In developing countries, efforts to increase the efficiency of bus transportation, which is the most common type of urban public transport systems, have been increasing in recent years. Many studies addressing the performance of bus systems focus on approaches to optimizing user and operator benefits. In this study, a bi-level simulation/optimization model is developed to optimize service frequencies in urban bus networks. At the upper level, a meta-heuristic Harmony Search (HS) optimization technique based model is proposed for solving an objective function that represents operator and user costs. At the lower level, the transit assignment problem, which represents the distribution of demand over the transit network, is solved. In the proposed model, a time-table based transit assignment approach is used for the exact calculation of transfer wait times, and the transit assignment problem is solved using VISUM software based on a logitbased choice model. The developed model has been applied to a test network that is widely used in transit network design studies. The results show that the HS based model can be used effectively to solve the service frequency optimization problem. [ABSTRACT FROM AUTHOR]

Understanding urban mobility patterns and their connections with different area characteristics is a traditional topic in urban studies, considering its importance for the planning and management of urban facilities, transportation systems, and services. Data recordings about trips using different means of transportation, such as a subway, bus, and taxi have been collected because of the development of IT technologies; such development has motivated various research related to uncovering detailed urban mobility patterns and factors that affect mobility. However, many works usually focus only on a specific means of transportation and fail to present different aspects of ridership patterns for other means of transportation. In this study, subway and taxi data were analyzed simultaneously to uncover factors on human mobility depending on the means of transportation in Seoul. The present research focused on regions nearby subway stations. Data mining techniques, such as clustering and classification, were employed. Different distinct ridership patterns of subway and taxi were detected using clustering; moreover, the difference between ridership patterns and spatial distributions of clusters were examined. A two-step classification analysis was then performed to determine factors that influence ridership patterns. [ABSTRACT FROM AUTHOR]

In this article, the results of the research in a field of which uses active global navigation satellite system (GNSS) geodetic networks for the inventory of geodetic geometric tram tracks are presented. The applied measurement technique has been adapted for the designing of the geometric layout of tram tracks. Several configurations of receivers and settings of an active GNSS networks with the objective to increase the accuracy of positioning and the availability of accurate localization are investigated. The measurement methods are optimized in order to increase the accuracy of determining positions from 3 mm up to 6 mm. Thus, the study of deformations in geometric layouts-according to the authors-is already possible. The implementation techniques of the mobile satellite measurements in a field of tram track inventory process are presented in this article. The course of the measurements and the results of the inventory of the tram system in Gdansk, Poland have been discussed. The results have turned out to be extremely useful for the geometric track layout evaluation. It has been proved that the applied method allows a comprehensive tram network inventory to be performed based on satellite measurements. The presented method is fast and cost-efficient. [ABSTRACT FROM AUTHOR]