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The West Virginia University (WVU) Personal Rapid Transit (PRT) system was built between 1971 and 1975 in Morgantown, West Virginia to be a prototype transportation system of the future. Envisioned as a hybrid of public and automotive transportation, the fully automated cars deliver passengers directly to their destinations without stopping at intervening stations. The PRT concept may be familiar to STS scholars through Latour's study of Aramis, a PRT in Paris that was never completed. This article recounts a history with the opposite ending: the successful realization of a PRT in West Virginia. Our account supplements existing ones, which explain the construction of the WVUPRT primarily as the product of geography and politics. While not denying these factors, we carve out an explanatory role for another influence: a public narrative about the dangers of hitchhiking and crimes that might ensue from that practice. In weaving together that narrative with the history of the WVUPRT, we show how public narratives of crime authorize technological infrastructure.

Accurate prediction of bus arrival time is essential to achieve efficient bus dispatch and improve bus trip sharing rate. This article proposes using the improved whale optimization algorithm–long short‐term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. Initially, the bus arrival process and its associated influencing factors are analyzed, with certain factors being quantified to serve as input features for the prediction model. After processing the GPS data of the No. 220 bus in Nanchang, Jiangxi, China, the proposed prediction model is analyzed and validated using an example and compared with other prediction models. The results show that the IWOA–LSTM prediction model has the best‐fitting effect between the predicted values and actual values in all time periods. Its MAPE, RMSE, and MAE have been reduced by at least 9.47%, 12.77%, and 8.93%, respectively, and the overall R2 has been improved by at least 10.65%. These results indicate that the model has the best predictive performance. [ABSTRACT FROM AUTHOR]

In addition to addressing the labor shortage due to an aging population, the transition to autonomous vehicle (AV)-based mobility services offers enhanced efficiency and operational flexibility for public transportation. However, much of the existing focus has been on improving AV safety without fully considering road conditions and real-world service demand. This study contributes to the literature by proposing a comprehensive framework for efficiently integrating AV-based mobility services at the network level, addressing these gaps. The framework analyzes and optimizes service networks by incorporating actual demand patterns, quantifying road segment difficulty from an AV perspective, and developing an optimization model based on these factors. The framework begins by quantifying the operational difficulty of road segments through an evaluation of Operational Design Domains (ODDs), providing a precise measure of AV suitability under varying road conditions. It then introduces a quantitative metric to assess operational feasibility, considering factors such as the service margin, costs, and safety risks. Using these metrics alongside Genetic Algorithms (GAs), the framework identifies an optimal service network that balances safety, efficiency, and profitability. By analyzing real-world data from different mobility services, such as taxis, Demand-Responsive Transport (DRT), and Special Transportation Services (STSs), this study highlights the need for service-specific strategies to optimize AV deployment. The findings show that optimal networks vary with demand patterns and road difficulty, demonstrating the importance of tailored network designs. This research provides a scalable, data-driven approach for integrating AV services into public transportation systems and lays the foundation for further improvements by incorporating dynamic factors and broader urban contexts. [ABSTRACT FROM AUTHOR]

The transportation industry has been recognized as one of the industries that can benefit from investment in blockchain-based systems and services that enable distributed data management and improve the effectiveness and efficiency of the transportation sector. However, the literature needs a guiding framework for integrating blockchain in issuing and preserving public transportation transactions in a technical environment that is secure, efficient, and transparent. This study proposes a blockchain-based transportation wallet (BTW) framework that facilitates the main digital transactions across diverse public transportation services. BTW embodies leveraging blockchain technology, which provides a decentralized and immutable ledger that records and verifies transactions, ensuring trust and reducing the risk of fraud. The framework has been validated by developing a blockchain-based public transportation smart wallet named "RideChain". This serves as a single decentralized point for making public transportation transactions and payments, as well as identity authorizations and management. RideChain enhances passengers' and service providers' experience through a secure and authentic platform for offering several reliable public transportation transactions efficiently. In this study, we implemented a smart contract to establish a protocol between passengers and journey services. The testing methodologies used in this study comprise unit testing, integration testing, performance testing, and user acceptance testing. The findings suggest that BTW has been successfully verified to demonstrate its capability for secure transactions, authenticity of monetary transactions, automated smart contracts, decentralized identity authentication, and effortless payments. [ABSTRACT FROM AUTHOR]

The integration of shared bikes and flexible transit services offers significant potential and benefits for urban transit systems. This paper presents a novel robust optimization framework for designing demand responsive connectors (DRC) that are fed by shared bikes. A two-stage model is formulated, with the first stage focusing on prereserved requests and the second stage addressing en-route random requests. The findings demonstrate that incorporating shared bikes can enhance the efficiency of serving en route late requests and reduce the required DRC vehicle fleet size. Additionally, it is observed that e-bikes are particularly suitable for this joint service due to their adaptability. [ABSTRACT FROM AUTHOR]

The objective of this research is to identify the main characteristics and geographical distribution of bus stops, associated with collective public transport systems, through data analysis techniques that can identify clustering patterns based on various characteristics of the stops, such as geographical location, passenger flow, service demand, land use, etc. number of routes available, slope of the road, signage, among other relevant factors. The main result of this study is that the current layout of the stops is distributed according to the main characteristics of their environment, allowing us to conclude that the grouping of transport stops facilitates the interpretation of the location and operability of the stops, thus allowi ng to improve decision-making in the implementation of stops, guaranteeing an adequate operation of the service without compromising coverage and travel time of users. [ABSTRACT FROM AUTHOR]

Transportation uses substantial energy and is a significant household expense in the United States; public transportation and working from home present opportunities to reduce energy use and increase household affordability. However, during COVID-19, transportation systems reduced service, and nationwide, public transportation use has been declining. Focusing on six small-to-medium-sized "Gateway Cities" in Massachusetts—more affordable cities with lower-than-state-average median income and lower-than-state-average education—that have regional transit systems and are within Boston's commuter rail area, we analyzed the changes in public transit ridership and work from home. We estimated linear and hierarchical linear regression models to understand the association between demographics and built environment and lower emission modes to work between 2011 and 2021. We used GIS to visualize the distribution of public transit ridership and work from home over time and space. We found that the block groups in our sample retained public transit users over the study period and saw increases in working from home. Across all cities, transit ridership was more likely to increase in block groups with higher accessibility to jobs and more frequent transportation to those jobs; work-from-home was more likely to increase in block groups with a lower percentage of Hispanic residents and lower rent burden. We found that most block groups either saw an increase in ridership or working from home, suggesting that work from home and public transit users are spatially segmented groups. [ABSTRACT FROM AUTHOR]

In the context of rapidly urbanizing cities, integrating sustainable technologies into public transportation systems is important. This study examines the policies and legislative frameworks of NEOM and articulates their impact on the adoption and expansion of sustainable technologies within the public transport domain. The objective is to determine whether these regulatory mechanisms facilitate or impede NEOM's sustainability ambitions. The main finding is that NEOM's current legislative and policy framework presents notable challenges. The commitment to advancing sustainable technologies is clear, tension exists between the rigidity of traditional legislative approaches and the rapidly evolving nature of technological innovation. Our analysis suggests NEOM has considerable potential to reform its policies and measures. Recalibration would ensure compatibility with sustainable practices and drive the city's vision for a sustainable and technologically advanced public transportation system. The study recommendations highlight the need for flexible, innovation‐centric legal frameworks. A more adaptable legislative approach could inform NEOM to leverage sustainable technologies more effectively, ensuring an environmentally responsible public transportation system that serves its expanding user community. Furthermore, this research offers broader implications for other emerging smart cities, underscoring the essential relationship between policy, technology, and sustainability in shaping future‐ready urban transport systems. [ABSTRACT FROM AUTHOR]

This article analyzes public transportation as a trope for networked narrative forms in two novels by Chinua Achebe: No Longer at Ease and Anthills of the Savannah. Combining insights from mobility studies with criticism on tragedy, the present article suggests that intersections of tragedy and transportation remain understudied aspects of Achebe's fiction. While agon implies the struggle or dispute that drives literary plots in general, I argue that Achebe settles elements of the deliberative agon from classical Greek theatre within transport networks to structure agonistic exchanges amongst characters and social groups, to juxtapose forms of thinking, and to expand the idioms within his novels. As much as Achebe's novels pivot on the experiences of singular and seemingly heroic protagonists, he is deeply invested in the relations between individuals and collectives and the representation of both in novels concerned with the problems of postcolonial nations and nation-states. As such, Achebe's transportation systems facilitate fleeting modes of assembly for the exchange of ideas. Studying No Longer at Ease and Anthills of the Savannah together crystallizes the orchestrated and often ironic interplay between individual and collective insights. Achebe's representations of conviviality and agonism in public transportation thus present models of thinking and feeling collectively in the novel. Moments of transportations in Achebe's fictional worlds impart the modes of thinking animating the imagination of the nation and the machinery of the state. [ABSTRACT FROM AUTHOR]

The COVID-19 has forced people to rethink the interrelationships between public health, urban environment and transportation. Past studies have attempted to investigate the impact of the COVID-19 on individuals' mobility. Nevertheless, relevant strategies for the urban adaptation and resilience strategies to cope up with the post pandemic situation have not been explored yet in Gulf Cooperation Council (GCC) countries, especially in the United Arab Emirates (UAE). Therefore, this study examines the changes in the urban mobility—trip frequencies by mode and purpose during the different severity periods of COVID-19 in the UAE. To draw strategies for the post pandemic transport management, the study tries to quantify the effects of participants' personal and perceived features on the change in mobility behavior as the severity of the COVID-19 changes. To achieve this objective, data are gathered through a comprehensive web-based questionnaire, yielding 1,964 responses. The data are analyzed via descriptive analyses and random parameter bivariate probit model. The results indicate a shift in the individuals' mobility behavior during the three COVID-19 periods (before the peak, during the peak, and after the peak). More importantly, the individuals' mobility reduced substantially during the during the peak period and recovered back to normal after the during the peak. Moreover, there exists a significant relationship between the respondents' personal and perceived features and the change in mobility as the COVID-19 severity changes from before the peak to during the peak and from during the peak to after the peak. This study underscores the crucial role of integrating public health insights with urban and transportation planning to enhance the resilience and adaptability of cities in the face of future pandemic. [ABSTRACT FROM AUTHOR]

Electric bus transport, a popular mode of public transportation, offers punctual, safe, and comfortable services to passengers through the efficient and effective use of designated road space. The performance of electric bus transport systems depends largely on the design of proper locations of bus stops, with the consideration of passenger demands, waiting time, and traveling time. Optimal electric bus route planning can attract an increasing number of passengers and increase public transit services. Aiming to provide guidance for the electric bus route planning of developing cities, this study proposed an intelligent route planning method to minimize the waiting time and traveling time of passengers, in order to achieve the best comfortable level. In addition, a self‐learning anomaly detection method based on reinforcement learning (RL) was proposed to eliminate abnormal data caused by traffic accidents or emergencies. With a large spatiotemporal dataset collected over 3 years from a real electric bus project in Yantai, China, we developed a prototype system and conducted extensive experiments to evaluate the proposed intelligent route planning method. The results showed that the proposed method can reduce the passengers' waiting time and attract more passengers traveling by electric bus. In addition, the proposed method has achieved optimal route planning recommendation (RPR) subject to 1,872,391 passenger demands on electric bus services; more than 86% of them were accurately predicted, and more than 97% were satisfied with recommendation results. [ABSTRACT FROM AUTHOR]

This study investigates magnetic flux density (B) and radiofrequency electromagnetic field (RF-EMF) measurements on electric buses operating in Samsun, Turkey, focusing on two bus routes (called E1 and E4) during the morning and evening hours. Measurements were taken under diverse operational conditions, including acceleration, cruising, and braking, at locations of peak passenger density. Along the E1 route, the magnetic field intensity varied significantly based on the bus position, road slope, and passenger load, with notable increases during braking. In contrast, the E4 route showed a lower magnetic field intensity and RF-EMF values due to its straighter trajectory and reduced operational stops. The highest RF-EMF measurement recorded was 6.01 V/m, which is below the maximum levels established by the ICNIRP guidelines. In 11 out of the 12 different band-selective RF-EMF measurements, the highest contribution came from the downlink band of the base stations, while in only one measurement, the highest contribution originated from the uplink bands of the base stations. All data were subject to the Anderson–Darling test, confirming the generalized extreme value distribution as the best fit for both B and RF-EMF measurements. Additionally, the study assessed B levels inside and outside the bus during charging, revealing heightened readings near the pantograph. These findings significantly contribute to our understanding of electromagnetic field exposure in electric bus environments, highlighting potential health implications and informing the development of targeted mitigation strategies. [ABSTRACT FROM AUTHOR]

Airborne infections pose significant challenges to public transportation systems which can result in significant decline in ridership levels and financial stress for operators. This systematic review presents a comprehensive overview of measures and strategies employed by ground public transportation agencies to protect passengers and staff while ensuring the uninterrupted operation. This study also conducted a bibliometric analysis to provide insights into key topics, publication patterns, and major contributors in the field of airborne transmission research in public transportation. We have included studies published from January 2003 to June 2024, which reported measures and recommendations for managing public transportation to reduce virus transmission. Of the 2848 initially identified studies, 69 met our eligibility criteria. Our review identified four key strategies to prevent virus transmission in public transportation, including air quality improvement, cleaning, mask-wearing, and social distancing in vehicles and stations. While social distancing poses a significant challenge to public transportation, the integration of crowd management techniques and technology-driven information dissemination can provide effective strategies for managing capacity. The adoption of technology-driven solutions, such as efficient filtration systems, automated mask detection mechanisms, ultraviolet disinfection devices, and real-time passenger information, is required to implement these strategies effectively. Transportation agencies can utilize an airborne infection risk calculator during pandemics and beyond to assess and mitigate the risk of airborne transmission in various modes of transportation. Lessons from the Covid-19 pandemic underscored the need for developing advanced technologies to enhance passenger and staff safety in public transportation vehicles and stations. • Systematically reviewed countermeasures for airborne infection in public transport. • Highlighted the need for integrating advanced technologies to minimize infection transmission. • Key strategies included air quality improvement, sensitization, mask wearing, social distancing, and crowd management. • Future research on cost-benefit analysis and technological feasibility is necessary. [ABSTRACT FROM AUTHOR]

Implementing the concept of sustainability in tourism needs a significant reduction of vacationists' ecological footprint at destination level. A key aspect there is tourists' travel mode choice on‐site. Based on an online‐panel based survey in Italy and Germany and applying ordinal regression, this study analyzes for the destination South Tyrol, the impact of five blocks of potential factors on public transportation (PT) usage during a vacation: sociodemographics, everyday mobility at residence, attitudes toward climate change and environment, preferences for cars, and PT services at the destination, including the availability of a guest card for free PT use. The results of an ordinal regression analysis show that the availability of a guest card and the level of daily use of PT at home significantly increase PT usage. This is countered by daily use of the car at home and a positive affinity toward cars, having a negative effect on PT use. [ABSTRACT FROM AUTHOR]

In this paper, a Multi-Criteria Decision Analysis methodological framework is developed to rank alternative fuel buses. It is applied to the case-study of the public transportation system of the island of Gotland in Sweden. Seven alternative fuel buses are identified: bioethanol, biodiesel, biogas, plug-in hybrid electric biodiesel, plug-in hybrid electric biogas, battery electric and hybrid electric hydrogen fuel cell buses. These alternatives are evaluated under 11 criteria that are categorized under four dimensions and measured under a Life Cycle Sustainability Analysis approach where possible. The ranking is accomplished by means of the weighted summation method; weights are determined through the Analytic Hierarchy Process. Explicit weights on these criteria provided by local experts and stakeholders are used to evaluate the alternatives under various island-specific scenarios. Results show that biogas and plug-in hybrid electric biogas buses are the preferred alternatives as long as biogas is produced from waste residuals; otherwise, the import of biodiesel could be the preferred short-term alternative. Bioethanol appears to be the least suitable fuel. The developed methodological framework proved helpful to the local authorities of Gotland when they sought to identify the best compromise fuel bus solution and has shown that it can be applied in similar case-studies. [ABSTRACT FROM AUTHOR]

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Tunnel boring machines (TBMs) are preferred for constructing tunnels, particularly for underground mass transit railways, because of their speed, minimal environmental impact, and increased safety. However, TBM tunneling involves unavoidable risks, necessitating careful assessment and management for successful project completion. This study presents a novel hybrid risk-analysis method for tunnel construction using TBMs. The proposed method integrates fault tree analysis (FTA) and the fuzzy analytic hierarchy process (fuzzy AHP). FTA was employed to calculate the probabilities of risk occurrences, while fuzzy AHP was utilized to determine the consequences of the risks. These probability and consequence values were used to calculate continuous risk levels for more accurate risk analysis. The proposed method was applied to a real case of metro line construction. The results demonstrated that the proposed method effectively analyzes the risks, accurately reflecting decision support data. The risks were categorized based on the continuous risk levels in descending order. The most significant risk was the deterioration of the TBM. The benefits of this study provide project managers and stakeholders involved in underground construction with a new risk-analysis method that enhances work safety and facilitates the timely execution of urban tunnel construction projects. [ABSTRACT FROM AUTHOR]

With the growing demand and projected shortage of rare earth elements in the near future, the urgent task of developing energy-efficient electrical equipment with less dependence on rare earth magnets has become paramount. The use of permanent magnet-assisted synchronous reluctance motors (PMaSynRMs), which reduce the consumption of rare earth magnets, can help solve this problem. This article presents a theoretical analysis of the characteristics of PMaSynRM in a subway train drive. Options with rare earth and ferrite magnets are considered. Optimization of the motor designs considering the train movement cycle is carried out using the Nelder-Mead method. Characteristics of the motors, such as losses, torque ripple, and inverter power rating, as well as the mass and cost of active materials, are compared. [ABSTRACT FROM AUTHOR]

Empirical data from several cities worldwide show that low consideration rates of bus transit constitute an important reason for declining transit mode share. This trend raises a critical question: why do not more commuters consider buses for travel? The aim of this paper is to investigate the key deterrents to bus transit consideration among commuters. Consideration refers to the decision of an individual to include a given mode in his/her choice set. Along this line, this study focuses on two important directions. The first is to gain an understanding of how the key factors and their influence on consideration propensity differ across market segments based on personal vehicle availability and accessibility. The second is to quantify the spatial heterogeneity in the influence of those key factors across geographical locations. A new geographically weighted segmented logistic regression (GWSLR) model is proposed to address these research issues. The model is developed using household survey data from a sample of work-commuters from Chennai city, India. The findings reveal that neglecting either segmentation or spatial heterogeneity cannot only result in inaccurate model predictions and inferences, but also lead to sub-optimal policy interventions. Results show that factors influencing consideration differ significantly across segments based on captivity and accessibility. Choice users within walking distance to bus stops can benefit from direct bus service, whereas those beyond walking distance prioritise first-mile connectivity. Results also highlight significant variations in the influence of different factors across locations. Improved walkability in central business districts (CBD) could increase consideration, while non-CBD areas should focus on first-mile connectivity. Finally, this study illustrates that customised policy interventions for specific segments and locations can be more effective in enhancing bus consideration than segment-agnostic or geographically uniform policies. [ABSTRACT FROM AUTHOR]

In response to the phenomenon of global warming, the transportation sector aims to mitigate carbon emissions by promoting the use of public transportation. This study employs social network analysis to propose effective improvements to the public transportation system, focusing on bus stop locations and route networks in Hwaseong City, South Korea. Two networks were constructed based on existing public transportation routes and usage data at each bus stop. The findings and implications are as follows: Analyzing the public transportation network from a network perspective can effectively contribute to improving the public transportation network route system. By evaluating centrality and brokerage for the existing routes, it is possible to identify inefficient routes and develop efficient route modification plans. Based on actual usage patterns, excessive bus supply and unnecessary bus stop locations can be identified, allowing for the establishment of appropriate operational plans. This can lead to improved operational efficiency and cost savings. Rational route design and operational planning can enhance public transportation services and promote increased use of public transportation. Ultimately, this contributes to sustainable development through carbon reduction in the transportation sector. [ABSTRACT FROM AUTHOR]

Airport shuttle buses, as a specialized form of bus service, serve as an economical, efficient, and sustainable transportation option for air travelers. In contrast to conventional bus services, airport shuttle bus operations exhibit more pronounced market-oriented characteristics, striving to balance extensive public transport coverage with the optimization of corporate profitability. Although these services outperform regular bus transit in terms of efficiency, they incur higher operational costs. However, existing studies on enhancing profitability and optimizing resource allocation for airport shuttle buses are inadequate. This study proposes a differential pricing strategy based on historical ticketing data. Initially, we analyze the characteristics of orders, users, and reservations within the context of customized bus operations. Leveraging the differences among various groups, we employ clustering techniques to classify seat grades and segment users. Based on the clustering outcomes, we determine distinct price elasticity values for each segment. As the strategies are developed based on seat grades, booking time, and user travel patterns, the numerical experiments indicate that the proposed differentiated pricing strategy can increase the revenue of customized public transport services by at least 41%. This strategy not only enhances the efficiency of resource allocation and service accessibility but also makes the service more financially sustainable. [ABSTRACT FROM AUTHOR]

Background: In the context of socially sustainable urban development, comfortable, safe, and accessible public transport is crucial to motivating people to travel more sustainably. Using the framework given by Masoumi and Fastenmeier (2016) to examine the concepts of safety and security, we explore how perceptions of safety about different transport modes shaped the mobility of older adults in Bengaluru, India. Methods: In-depth telephonic interviews were conducted with 60 adults, aged 50 years and over, residing in urban Bengaluru, using a semi-structured in-depth interview guide to explore the perceptions of safety in different transport modes. Observations were conducted prior to the COVID-19 pandemic. Applying thematic analysis, we present how the perceptions of safety during their everyday travel shaped their mobility. Results: According to our research, older adults' perception of safety during their everyday travel is shaped by past negative experiences with accidents, pickpocketing, theft of mobile phones, and chain snatching. In addition, the Covid-19 pandemic exacerbated the already existing inequalities, further limiting older adults' mobility to carry out regular activities such as buying groceries, socialising, making a hospital visit, or going to work due to the fear of getting infected. Conclusion: Our findings indicate that the use of public transport needs to be encouraged among older adults by enhancing necessary safety features following the age-friendly cities framework. Furthermore, it can help policymakers develop transport polices, which suit the mobility needs of older adults. [ABSTRACT FROM AUTHOR]

This study will focus on public transportation problems in terms of energy consumption, excessive travel time, and fares. The study seeks the best solutions for such concerns in the Izmir case. It aims to optimize these subjects for the tramway and bus systems, which are comparable in terms of origin and destination points. This study, also, draws attention to the integration issue of the transportation modes. The methods employed in this study are linear programming and sensitivity analysis. For this study, nine routes, which have both tramway and bus lines, were determined. The routes sharing the same transfer points were taken to investigate which transportation type would be the most convenient or useful, what their drawbacks and positive outcomes would be, and which one would be environmentally friendly, with especially the lowest cost. For linear programming, the Solver tool of Microsoft Excel® software was utilized. Initially, the objective functions were identified as minimization of energy consumption, minimization of route length and minimization of passenger costs. The data about energy consumptions, speeds, and passenger volumes were collected are constraints of optimizations. Finally, sensitivity analysis was conducted to assess the findings. The best solutions with bus and tram options were found for both passengers and operators. Optimal routes are Fahrettin Altay-Alsancak, Fahrettin Altay-Halkapınar, Mavişehir-Bostanlı and Egekent-Bostanlı. The study contributes to the literature using the time matrix besides to the transport cost matrix. Thus, this research serves not only for monetary aims but also for environmental and social aims. [ABSTRACT FROM AUTHOR]

Background and Aims: The role of fomites in the transmission of infectious diseases is becoming more important because of the possibility that contaminated surfaces act as reservoirs of diseases. The aim of this study was to ascertain the level of bacterial contamination and the prevalence of antibiotic-resistant genes on the most touched surfaces on public transport. Methods: One hundred samples were collected from door handles and armrests of buses and tricycles, respectively at Isale-Oko motor garage, Sagamu. Bacteria were isolated from the samples and identified following standard microbiological techniques. Antibiotic susceptibility testing was done with the Kirby-Bauer disc diffusion method. The presence of antibiotic-resistant genesvanA, drfA, dfrG genes, and extended-spectrum betta-lactamase (ESBL) genes in Gram-negatives were screened by polymerase chain reaction (PCR) method. Results: Out of the samples tested, 91% were positive for bacterial contamination. Among the 91 positive samples, 126 bacteria were identified, comprising 98 Gram-positive and 28 Gram-negative bacterial isolates. Staphylococcus aureus had the highest overall frequency of occurrence with 62 (49.2%) isolates. Among the Gram-positives, azithromycin resistance was present in 35(56.5%) S. aureus and 19(52.8%) Staphylococcus epidermidis. Salmonella species was the most resistant to ciprofloxacin (100%). dfrG was the most detected among trimethoprim-resistant genes occurring in 11(55%) of multidrug-resistant S. aureus and 6(54.6%) of S. epidermidis. vanA gene was present in S. aureus (20%). dfrA was present in only Klebsiella pneumoniae and Esherichia coli. E. coli and Shigella species carried blaTEM while blaSHV was found in Pseudomonas aeruginosa. Conclusion: The most-touched surfaces of public transportation can serve as a substantial source of spread for potentially harmful bacteria. [ABSTRACT FROM AUTHOR]

Many cities and countries have embraced transit-oriented development as an international growth management approach, shifting trips from car-oriented to transit. But in this race to become more sustainable, who is being left out? Using mobility justice as a theoretical framework, this paper presents a qualitative comparison between Malmö, Sweden, and Kitchener, Canada, two mid-sized cities where new rail-based infrastructure was completed in 2019. Using over 40 interviews with local residents, business owners and staff, planners, and private sector developers in each city, we found that transportation improvements have created unequal transport mobilities. In both cities, new transportation infrastructure did not improve travel times or access to transit for existing users; in Kitchener, local changes to make way for the new LRT had negative effects on the neighborhood, and bus transit times increased, while in Malmö bus services remained the same as the new train was barely used. This detachment of transportation needs from infrastructure is necessary for local and state politicians to promote new infrastructure as a branding approach. We call this transit boosterism. [ABSTRACT FROM AUTHOR]

As large open spaces, such as national and regional parks, have become popular as recreational destinations, car dependency to access those open spaces has created capacity challenges. Due to these issues, transit-to-parks (T2P) initiatives—public transportation services connecting populated areas to large parks—have gained global traction. Limited research has examined these sustainability initiatives, and more knowledge is needed about how these initiatives are created and function. To address these gaps, this study explores motivations, facilitators, and challenges related to T2P initiatives in the U.S. and Canada. We conducted semi-structured interviews with 28 practitioners involved in the planning or operation of T2P initiatives in the two countries. Motivations for T2P included parking and congestion issues, environmental concerns, equity, and economic development. Facilitators of T2P initiatives included robust partnerships, community engagement, and advocacy efforts, emphasizing the importance of tailored narratives and coalition-building. The primary challenges mentioned were limited funding and labor, inadequate infrastructure, and siloed agencies and politics. This study reveals the complex dynamics of T2P initiatives and provides practical implications for transit agencies, public lands agencies, and community advocates seeking to enhance more sustainable and equitable access to nature. • We examine emerging transit-to-parks (T2P) initiatives in the U.S. and Canada. • T2P initiatives are driven by traffic, environmental, social, and economic motivations. • Policy advocacy, partnerships, and community engagement emerge as critical facilitators. • Challenges include limited funding and labour, inadequate infrastructure, and siloed agencies and politics. [ABSTRACT FROM AUTHOR]

Suroboyo Bus Operational Risk Management System Using Fmea Method (Failure Mode Effect Analysis). Suroboyo Bus currently has several operational risks so efficient risk management planning is needed. The risk management planning mechanism used is Failure Mode and Effect Analysis (FMEA) with the hope of identifying the risks inherent in the operational business process of Suroboyo Bus. It can be seen from the survey results that 35% of the public want to add routes and 25% of the public want to add fleets. From the results of risk identification, 18 causes of the highest operational risks were obtained, including Driver absence, Minor damage or disruption to tyres, Major damage or disruption to facilities inside, Minor damage or disruption to facilities inside the bus, Traffic congestion around the bus stop, No plastic bottle checks, Damage or incomplete bus spare parts that were missed from the checking process, No helper at the passenger gathering point, Accidents on the way to the bus stop, Bus accidents, Major damage or disruption to the engine, Major damage or disruption to tyres, Unprinted receipts (out of stock), Unvalidated receipts, Lost receipts, Gears not in P position when parking at the Pool, No bus spare part checking process, accidents by cleaning staff, so SOPs, regulations, and budget policies are needed. [ABSTRACT FROM AUTHOR]

This paper investigates the choices to engage in various activities while commuting. Using data collected through a survey of 2149 Northern California commuters, we develop binary logistic regression models of the decision to engage in each of eight types of activities on the commute: rest/sleep, use a laptop, use a smartphone, listen to audio, read printed materials, edit papers/ printed materials, read electronic documents, and edit electronic documents. Explanatory variables include socio-demographic characteristics and attitudinal and time use factors. We model the engagement in each type of activity while traveling by each of five different modes (bicycle, commuter rail, transit, shared ride, and drive alone) – 33 models in all (excluding impractical combinations). The results illuminate the individual-specific traits affecting commuters’ propensities to engage in activities while traveling. Those propensities exhibit large differences across modes. Longer commutes result in higher propensities to engage in almost all modeled activities for commuter rail and ridesharing. Age, gender, income, trip distance, education level, attitudes and preferences towards the adoption of technology, familial obligations, expectations about time use, and attitudes towards multitasking all affect the propensity to engage in activities while commuting.

The purpose of this study was to improve commuter safety in South Africa’s minibus taxi industry. It is a vital component of the nation’s transportation network that is plagued by road safety concerns due to driver behaviour. A quantitative research approach involving 150 respondents selected through probability sampling was utilised. Data were collected via self-administered questionnaires at Bosman Taxi Rank in Pretoria, Gauteng province, and analysed using the Statistical Package for the Social Sciences (SPSS). The study’s findings revealed severe safety issues faced by public transport passengers, including fatalities and injuries resulting from unsafe practices by minibus taxi drivers. It also highlighted systemic shortcomings in traffic law enforcement, particularly during weekends, which are exacerbated by drivers operating under the influence of alcohol. Recommendations include professionalising the minibus taxi sector, enhancing collaboration between traffic law enforcement agencies and the taxi industry, revising remuneration structures for National Traffic Police officers, establishing passenger-centric organisations, centralising traffic law enforcement mechanisms, improving driver employment conditions, and conducting public road safety awareness workshops. This study contributes to scholarship by providing empirical evidence on the safety challenges within the minibus taxi industry and proposing comprehensive measures to address these issues, ultimately striving for a safer transportation environment for all commuters in South Africa.

Public transportation usage in Delhi has declined, with the Delhi Metro having a significant share. However, due to fare hikes and COVID-19 restrictions, the DM's share has been decreasing further. To improve ridership, a study is being conducted to evaluate the DM's performance and identify areas for improvement in passenger convenience and comfort. The Magenta line is investigated through an on-board survey to collect primary data. The survey covers commuter perceptions of safety & security, financial & economic factors, infrastructure & comfort and functional & operational features. The Relative Importance Index approach is used to analyse the data and evaluate DM performance. An ANN model is also presented to determine the factors influencing the choice to travel on the DM, with the “metro fare per trip” factor being a key consideration. Based on the analysis results, recommendations are made to improve the DM's performance. The study found that safety and security had the highest RII, followed by efficiency and viability, functional and operational features, infrastructure and comfort, and financial and economic factors. The subway fare had the lowest RII. The ANN model is adapted to understand the reasons behind low metro ridership.

This paper proposes a novel decision-support system (DSS) to assist decision-makers in the ULTIMO project with integrating Autonomous Vehicles (AVs) in Geneva, Switzerland. Specifically, it aids in selecting the best scenario for incorporating AVs into Geneva’s public transportation system. The proposed DSS is architected on a combined integrated framework that includes a machine learning (ML) algorithm, random forest (RF) algorithm, and three novel multi-criteria decision-making (MCDM) algorithms: (1) Modified E-ARWEN (ME-ARWEN) for selecting the best scenario with high sensitivity; (2) Compromiser—Positive, Neutral, Negative (Compromiser-PNN) for extracting weights from stakeholders, considering their preferences and potential conflicts; and (3) Collective Weight Processor (CWP) for deriving weights from expert opinions. Besides the main objective, this article also aims to: (1) Address the gap in practical DSS software within AV-related studies by providing Python codes of the DSS; (2) Develop a highly sensitive and comprehensive MCDM framework to address the project’s needs; and (3) Employ Artificial Intelligence within the DSS to optimize outputs. By the application of the proposed DSS, four scenarios were evaluated: (1) Full integration of AVs; (2) Partial integration; (3) Pilot project in limited areas; and (4) Delayed integration. The analysis identified partial integration as the best scenario for integrating AVs. Furthermore, comprehensive analyses conducted to validate the DSS outputs demonstrated the reliability of the results. [ABSTRACT FROM AUTHOR]

Abstract Background In the context of socially sustainable urban development, comfortable, safe, and accessible public transport is crucial to motivating people to travel more sustainably. Using the framework given by Masoumi and Fastenmeier (2016) to examine the concepts of safety and security, we explore how perceptions of safety about different transport modes shaped the mobility of older adults in Bengaluru, India. Methods In-depth telephonic interviews were conducted with 60 adults, aged 50 years and over, residing in urban Bengaluru, using a semi-structured in-depth interview guide to explore the perceptions of safety in different transport modes. Observations were conducted prior to the COVID-19 pandemic. Applying thematic analysis, we present how the perceptions of safety during their everyday travel shaped their mobility. Results According to our research, older adults’ perception of safety during their everyday travel is shaped by past negative experiences with accidents, pickpocketing, theft of mobile phones, and chain snatching. In addition, the Covid-19 pandemic exacerbated the already existing inequalities, further limiting older adults’ mobility to carry out regular activities such as buying groceries, socialising, making a hospital visit, or going to work due to the fear of getting infected. Conclusion Our findings indicate that the use of public transport needs to be encouraged among older adults by enhancing necessary safety features following the age-friendly cities framework. Furthermore, it can help policymakers develop transport polices, which suit the mobility needs of older adults.

The main objective of the research is to determine the efficiency in population and area coverage of the set of bus stops to existing land uses in the city, allowing the identification of possible shortcomings, which leads to the formulation of restructuring proposals in terms of the location of the stops. The research methodology to be applied includes the use of geostatistical models of accessibility based on GIS-type digital tools, supported by the collection of field information and road inventories. As a main result, it is obtained that the stop-system coverage allows the access of more than 80% of the population in a trip time by walking less than 5 minutes. Likewise, it is possible to identify a robust redundancy concerning the system of stops. Thus, it is concluded that the research process facilitates the evaluation and identification of possible interventions, guaranteeing a better coverage of the stops set regarding the city's existing activities.

Accurately understanding the travel demand of urban rail transit (URT) systems is crucial for effective operational management. Despite the recognition that the diversity in human activity patterns results in different travel demands, few studies have thoroughly investigated the heterogeneity among passengers and its impact on URT ridership. This study utilizes smart card data collected from the Beijing Subway to categorize passengers into four groups: tourist passengers, flexible commuters, regular commuters, and life-oriented passengers, based on their spatiotemporal travel patterns. Furthermore, a Multiscale Geographically Weighted Regression (MGWR) model is employed to examine the relationship between station-level ridership of URT and its determinants, including the built environment and station properties, for each passenger group. The results indicate that the influence of these determinants on station-level ridership varies across passenger groups and spatial scales. For instance, regular commuters exhibit lower sensitivity to accessibility on workdays, whereas those unfamiliar with the URT network are more concerned about the bus accessibility in pedestrian- or bicycle-unfriendly areas. Notably, for tourist and life-oriented passengers, the stations significantly affected by population density are concentrated in areas with a higher proportion of elderly individuals. Conversely, for flexible and regular commuters, these stations are predominantly situated in areas associated with internet technology and scientific research. These findings are valuable for policymakers in designing strategies tailored to different passenger groups to balance trip demand and capacity, thereby improving URT services and promoting a sustainable urban environment., Author(s): Qian Qian [1]; Yang Liu [2]; Min He [2]; Mingwei He [2]; Huimin Qian [3]; Zhuangbin Shi (corresponding author) [2] 1. Introduction Unbridled urban expansion and excessive reliance on [...]

Transport for London, which manages public transport for the British capital, continues to experience technical disruptions from a cyberattack on September 1. It reported the cyberattack at the beginning of [...]

Introduction: Drivers' role is essential in road accidents. In other words, they deal with public safety and health. The current research investigated the mental health of intercity public transportation drivers. Materials and Methods: This descriptive-analytical research was conducted on 70 intercity public transportation drivers in Gorgan City, Iran. After coordinating with the Intercity Bus Organization of Gorgan, the drivers were randomly selected. They completed the demographic information and the General Health Questionnaire (GHQ-28). The data were analyzed using SPSS 23, descriptive statistics, and independent t-test. Results: Sixty-nine (98.6%) drivers were married, with a mean age of 39.05 ± 5.82 years. The ethnicity of most drivers (81.4%) was Fars. The mean duration of driving was 10.15 ± 4.45 years. The highest general health score was related to the anxiety and insomnia subscale, equal to 15.17 ± 3.98 (P= 0.813), and the lowest score was related to depression, equal to 10.55 ± 4.05 (P= 0.229). The level of depression was higher in Fars drivers than in those with other ethnicities (P= 0.008). Conclusion: The intercity public transportation drivers have mental health problems, mostly encompassing anxiety and insomnia. Given the role of drivers in society, it is recommended that municipal officials pay more attention to their mental health. [ABSTRACT FROM AUTHOR]

The present research investigates the advancement of sustainable transportation by promoting electric vehicles, expanding public transit, and implementing tax increases on fossil fuels and automobiles, via crucial strategies. The present study has examined a market with a fossil fuel vehicle (FFV) manufacturer, an electric vehicle manufacturer, and the government. The manufacturers' pricing strategies are geared towards optimizing profits, whereas the government's objectives for transportation are centered on attaining sustainability across economic, environmental, and social dimensions. The government has considered two strategies, one taxation-based and the other non-taxation-based, to achieve its objectives. In the taxation-based strategy, fixed taxes on fossil-fuel vehicles and fossil fuels are considered, while in the non-taxation-based strategy, subsidies for purchasing electric vehicles and the number of buses purchased for public transportation are predefined. Based on this, eight scenarios with different values for the predefined factors of each strategy have been defined to attain their respective objectives. Game theory has been utilized to determine an optimal solution based on Norwegian data, owing to the interconnected decision-making among stakeholders. By analyzing the findings, managers can enhance their decision-making capabilities. The results suggest that appropriately adjusting subsidies, taxes, and bus numbers within specific thresholds is crucial for mitigating air pollution and achieving other objectives. The assertion that electric cars are a definitive solution may not be accurate, as it depends on the source of the generated electricity. While excessive subsidies in non-renewable energy countries can lead to increased pollution, even in Norway, where most electricity is renewable, rising demand for electric vehicles contributes to air pollution due to increased production. In countries where electricity generation is not primarily from renewable resources, the growth of electric vehicles further exacerbates pollution. Simultaneous increases in fuel taxes and tariffs on fossil fuel vehicles negatively impact the demand for fossil fuel vehicles and government revenues. Therefore, it is recommended that an increase in fuel taxes be implemented to optimize both government revenues and social welfare. This approach safeguards public revenues, promotes societal well-being, and mitigates air pollution. • Examining the impact of promoting Evs and public transportation on sustainable transportation development. • Pricing of electric and fossil fuel vehicles using game theory and based on a case of Norway. • Studying the impact of tax, subsidies, and public transportation expansion on sustainable transportation goals. • Investigating vehicle selection based on government policies (allowing EV access to dedicated bus lanes). • Examining the Rebound effect of excessive promotion of electric vehicles or buses. [ABSTRACT FROM AUTHOR]

Background and Objectives Gentrification is a prevalent neighborhood development process in urban areas across the United States. Prior studies have identified the influence of gentrification on late-life health and quality of life, yet little is known about its relationship with food insecurity, an important public health issue for older adult populations. Using New York City as a case study, this study investigated associations between living in a gentrifying neighborhood and food insecurity, as well as the mediating roles of neighborhood environment factors—social cohesion, public transportation, and food environment. Research Design and Methods This study adopted 2 waves of annual data from the Poverty Tracker Study (2015–2016; N  = 703) merged with American Community Survey and spatial data sets to measure gentrification and neighborhood factors. Adjusted logistic regressions were used to examine the associations between gentrification and food insecurity. Further mediation analyses were conducted to test the mechanisms of such associations. Results Older adults in gentrifying neighborhoods were more likely to have food insecurity than those in moderate- to high-income neighborhoods. Compared to low-income neighborhoods, older adults in gentrifying neighborhoods had a lower likelihood of reporting food insecurity. Two significant mediators were found when comparing gentrification with moderate- to high-income neighborhoods: social cohesion and healthy food outlets. Discussion and Implications This study highlights the importance of gentrification in determining late-life food insecurity and identifies possible mechanisms with policy and social service implications to reduce the risk of food insecurity in urban areas. [ABSTRACT FROM AUTHOR]

Introduction: Infrastructure regularly supports male pursuits more than women's. Recent transportation scholarship focuses on this inequity by quantifying the daily travel of women and men for everyday care provision, often termed "the mobility of care." Care trips include dropping off and picking up family members, accompanying young children and old adults to medical appointments, and acquiring household goods. This study analyzes gendered travel behavior in the National Capital Region of the United States, including Washington, D.C. Methods: The basis of this study's analysis is data from the 2017/2018 Regional Travel Survey conducted by the National Capital Region Transportation Planning Board. The survey included records from approximately 16,000 households, 2,000 in Washington, D.C. Our study sample contained 19,274 unique people who made 49,215 trips. Many of these trips were made using the local bus and subway systems. Following an established methodology, the researchers recoded trip purpose data into five broad categories: care, work, shopping, leisure, school, and all other purposes. We then ran descriptive and statistical analyses of travelers aged 18 through 65 to measure the frequencies of household demographic characteristics and person-level trips for all purposes made by five travel modes: walk, bike, car, bus, and subway. Results: Based on our analysis, trips for work represent the majority of trips (34.7%), followed by shopping (28.2%), care (22.3%), leisure (8.5%), other (4.1%), and school trips (2.3%). Our findings indicate that women make more carerelated trips during the day than men (25.1% vs. 18.8%). They also make fewer work-related trips than men (30.3% vs. 40.2%). Regression analyses revealed correlations between care-related travel by all modes and public transportation by age, race, location of residence, and income. Discussion: The mobility of care, done mostly by women, is one of the primary reasons that people travel in and around Washington, D.C., and its suburbs. However, D.C.'s bus and subway systems are primarily designed to support the mobility of work done mostly by men. As a result, our study identifies the need for improvements in gender-responsive infrastructure, including public transportation policies and programs that explicitly address the mobility of care, improve access to care, and reduce the environmental impact of cars. [ABSTRACT FROM AUTHOR]

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Valuing urban public transport plays a vital role in the growth and development of a city. In addition, an exemplary system connection allows the formation of functional relationships between the different users and the surrounding environment. That is why, in this research, it is proposed as an objective to carry out a comparative analysis of the levels of coverage offered by Public Transport Systems in cities of the Colombian coffee region to visualize the current state of operation of each city. The research methodology uses geographic accessibility as a visualization tool complemented with the analysis of sociodemographic coverage. The main result is that the assessment of accessibility and coverage shows that the population has easy access in a travel time of less than 35 minutes. It can also be concluded that the evaluation process provides a broad view of the levels of transport supply in each city. [ABSTRACT FROM AUTHOR]

Public transportation usage in Delhi has declined, with the Delhi Metro having a significant share. However, due to fare hikes and COVID-19 restrictions, the DM's share has been decreasing further. To improve ridership, a study is being conducted to evaluate the DM's performance and identify areas for improvement in passenger convenience and comfort. The Magenta line is investigated through an on-board survey to collect primary data. The survey covers commuter perceptions of safety & security, financial & economic factors, infrastructure & comfort and functional & operational features. The Relative Importance Index approach is used to analyse the data and evaluate DM performance. An ANN model is also presented to determine the factors influencing the choice to travel on the DM, with the "metro fare per trip" factor being a key consideration. Based on the analysis results, recommendations are made to improve the DM's performance. The study found that safety and security had the highest RII, followed by efficiency and viability, functional and operational features, infrastructure and comfort, and financial and economic factors. The subway fare had the lowest RII. The ANN model is adapted to understand the reasons behind low metro ridership. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT)-based public transportation systems face distinct challenges within the broader realm of IoT. Developers of such systems encounter a notably intricate development environment compared to general IoT systems, which are inherently characterized by elevated levels of complexity and heterogeneity. As successfully applied in other domains, domain-specific modeling languages (DSMLs) can also be employed to facilitate the development of IoT-based public transportation systems and address the challenges mentioned. Hence, in this study, a novel model-driven engineering (MDE) methodology is presented, comprising the steps of using a DSML, called DSML4PT, for the development of a wide-range of IoT-based public transportation applications. Moreover, the usability evaluation of DSML4PT within this MDE methodology during the real applications of IoT-based public transportation systems is also provided, which is missing in similar studies. For this purpose, we investigated the usability of DSML4PT within a systematic evaluation approach in which the features of DSML4PT are assessed both quantitatively and qualitatively in eight different real public transportation applications with the participation of experienced developers. Comparative analysis revealed that approximately 80% of IoT-based public transportation systems could be automatically generated through modeling exclusively employing DSML4PT. In contrast to the conventional software development methodologies, the novel DSML4PT approach also decreased the time required for the development of public transportation applications by almost 50%. In addition, according to a questionnaire-based assessment, the general evaluation rating of the language was measured as 4.44 over 5-point Likert scale. Feedback from the developers corroborated the practicality of this language and its widespread adoption across diverse perspectives. [ABSTRACT FROM AUTHOR]

Urban logistics face growing complexity as cities seek sustainable development pathways; one solution is integrating freight transportation with public transit. The purpose of this study is to evaluate current practices, identify gaps, and highlight opportunities for advancement in this field. Through a comprehensive literature review guided by four research questions, this study evaluates methodologies, vehicle choices, the application of intermodal containers, and the shared use of public transportation infrastructure for freight delivery. A meticulous search methodology was employed to select references, which were then analyzed and classified into two main tables. Findings reveal a progression from initial pilot projects and cost analyses to sophisticated planning and optimization challenges, with a focus on metro networks and buses. This study uncovers a predilection for certain research types, the utilization of varied transportation modes, underexplored intermodal container use, and an emerging emphasis on transshipment operations. The integration of freight and public transportation within urban settings is identified as a dynamic and diversifying field, with significant potential for contributing to sustainable urban development. We outline nine areas for future research, including the incorporation of external costs and congestion effects into optimization models, and the exploration of unmanned vehicles, thereby laying the groundwork for more inclusive and efficient urban logistics solutions. [ABSTRACT FROM AUTHOR]

Mobility as a service, and its associated variants, has been proposed as a method to improve the sustainability of transport systems; however, most of the approaches that have been proposed so far have been unsuccessful or have worsened the situation. The work presented in this paper investigates an intermodal system that combines a ride-pooling service with a public transport network. The system is composed of a dedicated simulator that evaluates the transport scenario and an intermodal dispatcher that optimises the service according to requests, accounting for their time windows. This intermodal approach considers trips with multiple legs, for which either ride-pooling or public transport are used. This study investigates how the batch size and the early dispatching of the last leg, supported by a vehicle reservation strategy, impact diverse demand profiles that range from single-passenger to multiple-passenger requests, while also addressing the critical aspect of fleet size. The experimental setting used in this work is the metropolitan area of Barcelona; the experimentation results yield valuable insights into the functionality of the proposed intermodal system. [ABSTRACT FROM AUTHOR]

Public transportation vehicles are frequently preferred for daily transportation. Buses are one of the most common types of these vehicles in road transport. As buses have a much higher passenger capacity than cars, the drivers of these vehicles take on much more responsibility. It is the responsibility of the bus driver to ensure that each passenger is transported comfortably, punctually and safely during the journey. This extra responsibility can have a psychological impact on bus drivers. Due to the tiring nature of their work, they can sometimes exhibit aggressive behaviour. Any argument between the driver and the passenger during the journey can cause various problems. The behaviour of drivers and passengers can be monitored with a large number of cameras installed in the buses. In Erzurum, one of the cities where this practice is used, the Metropolitan Municipality reports the inspections of public transport buses. When these reports were analysed, it was found that there were a total of 1068 arguments between bus drivers and passengers in the last 3 years. These arguments were divided into 13 categories according to their content, and the data in the training set created was analysed using machine learning methods. The results of the analysis showed that the naive Bayes algorithm was the most successful. When all the data was distributed with this algorithm, the problems caused by drivers and passengers, which have the highest proportion of discussions, were revealed. When interpreting the results, some recommendations are made in order to make public transport more efficient and to reduce driver-passenger arguments. [ABSTRACT FROM AUTHOR]