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AbstractThis article explores the entanglements of bodies, affects and infrastructures that give shape to the experiences, practices and sense-making of everyday mobilities among metro passengers in contemporary China. Building on the affective turn and infrastructural turn, this paper argues that passengering is an affectively charged and infrastructurally mediated process of forming and negotiating mobile subjectivities. Drawing on in-depth interviews and ethnographic observations, this paper demonstrates how ‘squeezing in’ is a core space-making practice among Chinese passengers that involves not only acquiring bodily skills, habits, and tactics but also engaging in affective capacities to negotiate modes of feeling and affective relations on the move. Moreover, situating the analysis in the specific context of infrastructural development and citizenship cultivation in contemporary China, this paper reveals how the norms, regulations and practices of ‘good ridership’ is closely entangled with the narrative of ‘quality citizenship’ in post-reform China. This paper thus enriches existing literature on passenger mobilities through providing new empirical insights and conceptual contemplation on what it means to be a passenger. [ABSTRACT FROM AUTHOR]

(1) Background: Public transport has a vital role to play in creating sustainable, accessible societies. Accessible and inclusive, door-to-door public transport systems with low barriers to use benefit everyone, increasing the mobility of citizens and improving independence. As the industry strives towards multi-modal and Mobility as a Service (MaaS) concepts, there is a need to delve deep into the needs and perceptions of transport user's door-to-door journeys to find ways to improve. Accordingly, in order to increase the sustainability of MaaS, improving accessibility and understanding service user perceptions are of utmost importance. However, there is a scarcity of research within national transport services to determine unmet user needs to increase the accessibility and autonomy of door-to-door journeys. This research aims to investigate if it is possible to improve the door-to-door journey experience for public transport travellers, increasing the accessibility and the perception of autonomy via technology, and by doing so, providing a more sustainable alternative to road transport. It focuses on understanding service users of Ireland's National Rail service, Irish Rail, to create key improvements in interactive systems. (2) Methods: The study applies a user-centred mixed-methods methodology using surveys (N = 316) and co-design workshops (four workshops N = 15). The research collected deep insights into the mindsets and needs of service users, showing the potential to improve this door-to-the-door customer journey. Key improvements for interactive systems were outlined. Experience maps were designed, leading to a Conceptual Design for a travel assistant to aid the service user throughout the door-to-door journey. (3) Results: Travellers' autonomy and the sense of freedom they experience can be improved, mainly if their needs across the complete door-to-door customer journey are supported. Highlighted areas for action include information, accessibility, personal security, ticketing, comfort, facilities, and anxiety. (4) Conclusions: This research reiterates the need for national transport and MaaS providers to prioritise service users' perspectives when developing sustainable services. Co-designing is recommended as a means of achieving this. [ABSTRACT FROM AUTHOR]

Nature-inspired algorithms allow us to solve many problems related to the search for optimal solutions. One such issue is the problem of searching for optimal routes. In this paper, ant colony optimization is used to search for optimal tram routes. Ant colony optimization is a method inspired by the behavior of ants in nature, which as a group are able to successfully find optimal routes from the nest to food. The aim of this paper is to present a practical application of the algorithm as a tool for public transport network planning. In urban public transport, travel time is crucial. It is a major factor in passengers' choice of transport mode. Therefore, in this paper, the objective function determining the operation of the algorithm is driving time. Scheduled time, real time and theoretical time are analyzed and compared. The routes are then compared with each other in order to select the optimal solution. A case study involving one of the largest tramway networks in Poland demonstrates the effectiveness of the nature-inspired algorithm. The obtained results allow route optimization by selecting the route with the shortest travel time. Thus, the development of the entire network is also possible. In addition, due to its versatility, the method can be applied to various modes of transport. [ABSTRACT FROM AUTHOR]

Accurate prediction of bus arrival times can greatly benefit public transport users, allowing them to better plan their journeys in cities. The usual Expected Time of Arrival (ETA) estimators provided to citizens use all the information available to the bus service provider (vehicle position, traffic, etc.); in this paper we propose a procedure to improve these estimators that relies solely on historical ETA records provided by public transport councils through application programming interfaces (APIs). This improvement is achieved by means of a machine learning scheme that predicts and corrects the systematic errors of the available ETA estimators. Significant improvements in terms of error mean and standard deviation are achieved for the Madrid and Paris bus fleets. These robust results and the fact that the proposed scheme uses only historical and online information provided by APIs, without requiring the cooperation of the service provider, support the suitability of the proposed method for general public benefit applications toward the sustainability of cities. [ABSTRACT FROM AUTHOR]

This paper complements the existing literature on Bike Share Schemes (BSS) by investigating their use from a spatiotemporal perspective to assess their relationship with public transport (PT). We address these questions through the case of Brussels and its long-standing docked BSS 'Villo!'. Our study analyses comprehensive (consecutive 12 months) and disaggregated (station level) data on rentals and returns and finds that Villo! is used mostly in dense (although not all) districts also well served by PT. However, temporal structures suggest Villo! overtakes PT at night in vibrant districts and possibly in selected districts with lower PT services over weekends. In addition, Villo! stations at key PT hubs usually do not show specific temporal patterns, which suggests intermodality may work at all times during PT operations. There could be an evening peak effect combined with the Brussels' topography, but this needs to be confirmed by on-site surveys. [ABSTRACT FROM AUTHOR]

This study focuses on solving the problem of metro first/last mile, studying the method for designing microcirculation bus routes and coordinating schedules considering the impact of shared bicycles. First, we propose a bilevel mixed-integer programming model for designing microcirculation bus routes and coordinating schedules considering the impact of shared bicycles. The upper-level model minimizes the weighted sum of the travel time cost of passengers and the operating cost of public transport enterprises, and the lower-level model maximizes the number of passengers served by microcirculation bus routes. Then, an improved genetic algorithm is developed to solve the model, called the Monte Carlo adaptive genetic algorithm (M-GAI). Finally, the proposed model and algorithm are evaluated using the case study in the area near the Fubao metro station of Shenzhen Metro Line 3. Results show that if the impact of shared bicycles is not considered, the passenger demand will be greater than the actual value, and the operating cost of public transport enterprises will be increased by 36%. Compared with GAI, the average number of iterations of M-GAI is reduced by 31%, and the objective function value is decreased by 4%. In addition, when the number of routes increases, the average waiting time of passengers is shortened, the average attendance rate of microcirculation buses increases, and the average empty distance of each vehicle is shortened. However, the operating cost of public transport enterprises will increase with the number of routes. Finally, when weight factors α and β are 0.6 and 0.4, respectively, and the sum of the travel time cost of passengers and the operating cost of public transport enterprises reach optimal. [ABSTRACT FROM AUTHOR]

Individual mobility is driven by activities and thus restricted geographically, especially for trip destination prediction in public transport. Existing statistical learning based models focus on extracting mobility regularity in predicting an individual's mobility. However, they are limited in modeling varied spatial mobility patterns driven by the same activity (e.g. an individual may travel to different locations for shopping). The paper proposes a deep learning model with activity, geographic and sequential (DeepAGS) information in predicting an individual's next trip destination in public transport. DeepAGS models the semantic features of activity and geography by using word embedding and graph convolutional network. An adaptive neural fusion gate mechanism is proposed to dynamically fuse the mobility activity and geographical information given the current trip information. Besides, DeepAGS uses the gated recurrent unit to capture the temporal mobility regularity. The approach is validated by using a real‐world smartcard dataset in urban railway systems and comparing with state‐of‐the‐art models. The results show that the proposed model outperforms its peers in terms of accuracy and robustness by effectively integrating the activity and geographical information relevant to a trip context. Also, we illustrate and verify the working mechanism of the DeepAGS model using the synthetic data constructed using real‐world data. The DeepAGS model captures both the activity and geographic information of hidden mobility activities and thus could be potentially applicable to other mobility prediction tasks, such as bus trip destinations and individual GPS locations. [ABSTRACT FROM AUTHOR]

Metro systems play an important role in reducing urban traffic congestion and promoting the sustainable development of urban transport in megacities. With the expansion of a metro network, transfer stations are necessary for increasing the service connectivity of a metro network. An accurate estimation of transfer passenger flow can help improve the operations management of a metro system. This study proposes a data‐driven methodology for estimating the transfer passenger flow volume of each transfer station in a metro network by mining smart card data. The estimated transfer passenger flow data are visualized to show the spatial‐temporal distribution characteristics of metro transfer passenger flow. The case study results of the Shenzhen Metro network demonstrate that the proposed data‐driven methodological framework is very effective in estimating different types of transfer passenger flows, such as total transfer passenger flow, hourly transfer passenger flow, and inbound and outbound transfer flows at each transfer station. The spatial‐temporal distribution characteristics of transfer passenger flow can be very useful for designing effective and efficient passenger flow management measures to ensure the safe and efficient operation of a metro system. [ABSTRACT FROM AUTHOR]

The environmental commitment of public transport authorities plays a role in addressing the challenges ahead. After the COVID-19 pandemic, we can analyze the strength of green commitments during that turbulent time. Green public procurement (GPP) is a government tool dedicated to mitigating the environmental impact of public acquisitions. These actions can be monitored as an indicator that captures efforts for green actions by organizations. GPP adoption rates among public transport suppliers are comparable across countries because they operate in the same sector and share characteristics that facilitate comparison. In this study, the largest public transport suppliers in 38 European cities are compared from 2010 to 2023. A subsample of 13,280 contract notices was employed for the public transport sector from the Tender Electronic Database and GPP adoption was found to be higher on bus vehicle acquisitions than on tramway/metro vehicle acquisitions. During the COVID-19 pandemic, there was a marked GPP fall. These findings also indicate that while GPP adoption rates are higher among the 38 large public transport suppliers compared with medium and lower ones, the largest ones are not the front-runners in terms of GPP adoption. Our results suggest that environmental priorities are not as significant as one might expect. [ABSTRACT FROM AUTHOR]

With poor transportation infrastructure and increased reliance on motorization, fast-growing cities in the Global South that are experiencing rapid urbanization have received less attention in terms of sustainable transportation research. In this regard, it is imperative to support active mobility and public transit that help to reduce vehicle emissions, traffic congestion, road fatalities, and energy depletion while supporting public health, robust economies, and social equity. However, in the emerging cities context, the adoption of sustainable transportation options are constrained by various factors. This study aims to explore the key factors hindering the adoption of sustainable transportation options in Addis Ababa, Ethiopia. To do so, travel survey data were gathered from 720 households using stratified sampling and analyzed using factor analysis. The results from factor analysis indicated five groups of factors hindering residents' intention to adopt sustainable transportation options, including (1) infrastructure condition, (2) modal characteristics, (3) land use pattern, (4) policy framework, and (5) technology-related factors. The confirmatory factor analysis also depicts the five latent factors and the contributions of observed variables that are statistically significant (p < 0.01). More specifically, observed variables such as (i) inadequate pedestrian facilities, (ii) lack of bike facilities, (iii) poor public transit facilities, (iv) limited availability of reliable public transport, (v) long wait times, (vi) high public transport fare, (vii) discomfort, (viii) safety and security issues are the most significant factors. Another set of factors includes (ix) walking distance, (x) dispersed land use pattern, (xi) poor land use mix, (xii) inadequate policy support, and (xiii) lack of real-time information. Furthermore, the intention to adopt sustainable modes of transportation is influenced by socio-demographic characteristics such as gender, age, educational status, income, family size, and car ownership. The result contributes to the existing literature by providing insight into adopting sustainable transportation modes in emerging cities like Addis Ababa, which are characterized by several urban transportation challenges. [ABSTRACT FROM AUTHOR]

This article discusses the link between public transport and literary practices by analyzing Imraan Coovadia's 2012 novel, The Institute for Taxi Poetry. In this novel, Coovadia comments on South Africa's palimpsestic history from the precolonial to the postcolonial. One way in which Coovadia does this is through the motif of the taxi. The taxi refers to a mini-bus taxi which in South Africa is a form of public transport primarily used by people from working-class backgrounds. Another way concerns the proposal of a fictional genre that plays a prominent role in this novel: taxi poetry. The article explores the ways in which the novel uses the taxi and submarine vessels to open up the geography of the sea as a transport surface whose impact on the histories of the dispossessed is visible from both below and above the waterline. Through engagement with the humanities turn in mobility studies and with scholarship in the oceanic humanities from the Global South, the article argues that the national and terrestrial readings of public transport in African literature(s) undervalue the sea, a prominent transport arena in Coovadia's novel, as both a space of transit as well as a public space with shared transnational histories. The article engages the novel's imagined literary sub-genre to evaluate how the text's subterranean extensions of the South African taxi industry, and public transport generally, unearth the layered narrative of South Africa as nation. [ABSTRACT FROM AUTHOR]

This article analyzes representations of mobility and public transport in the following Mozambican novels: Terra Sonâmbula [Sleepwalking Land] (1992), O Outro Pé da Sereia [The Mermaid's Other Foot] (2006) by Mia Couto, O Comboio de Sal e Açúcar [The Train of Salt and Sugar] (1999) by Licínio Azevedo, and Museu da Revolução [Museum of the Revolution] (2022) by João Paulo Borges Coelho. Despite the importance of mobility and public transport in these works, existing scholarship has not considered these themes but has opted for more traditional categories such as 'travel', 'diaspora', and 'migration'. Focusing on the literary portrayals of public transport and infrastructure of mobility – i.e. buses, ships, and railway stations (Couto), a slow-moving train (Azevedo), and a Toyota Hiace car (Borges Coelho) – this article aims to demonstrate the central role that the mobility/immobility binomial plays in the representation of post-independent Mozambique. The main argument of this article is that the images of the railway, the road, automobility, and maritime travel are the literal driving force of the narratives and contribute to the (un)building of the national space. I use literary perspectives on mobility studies and world-system approaches developed within the framework of world-literature (Warwick Research Collective) to demonstrate that the tropes of mobility and the representations of public transport in the four novels register and encode the social, political, and economic transitions in Mozambique's colonial and post-colonial history and its incorporation into the capitalist world-system. [ABSTRACT FROM AUTHOR]

A close reading of literary representations of Johannesburg's public transport in the early decades of the 20th century gives insight into the intricate way in which freedom, mobility, and narratives of progressive modernity interlink with urban mobility regimes of public transportation. The literary representations mark public transport simultaneously as progressive and oppressive, depending on access. Where access is denied, public vehicles become part of an oppressive racist mobility regime and exclude individuals from formative experiences of collective belonging. The present analysis engages with selected concepts from the field of mobility studies, namely Cresswell's thoughts on the relationship of mobility and modern citizenship, Bissell's observations regarding 'mobile collectives', and the idea of 'throwntogetherness' by the social geographer Massey. These will be used to analyze the gatekeeping function of public transport in representations of early Johannesburg, where black, male, urban subjecthood is negotiated against white urban modernity. [ABSTRACT FROM AUTHOR]

Validation of travel demand models, although recognised as important, is seldom undertaken. This study adds to the scarce literature in this field by undertaking an external validation of a multi-modal transit route choice model. The model was estimated using smart card data for the urban transit network of Amsterdam before the introduction of a new metro line and is used to predict changes in travel behaviour after the network change. To validate, the model was checked for changes in estimated parameters between the two time periods, and predictive ability was evaluated at different aggregation levels. Although most model parameters were found to be unstable between the two contexts, the predictive performance at all levels was similar to the locally estimated model. Moreover, individual choices and transit mode-share predictions were found to be close to the observed ones. The errors were relatively larger for the link and route-level predictions, some of which could be attributed to the assumptions made regarding consideration choice set given as input to the model. On comparing alternative model specifications, using generic instead of mode-specific travel attributes lead to a strong degradation in predictive performance. Conversely, a model incorporating overlap between routes, with a better model fit in the base period, did not offer a clear improvement in prediction performance. The study highlights the need to validate transit route choice models before using them for deriving policy recommendations, especially in this data-rich age in which it can often be undertaken at a relatively low additional cost. [ABSTRACT FROM AUTHOR]

In the article, under field conditions (on the lane of a city road for public transport), using modeling and traffic flow analysis methods, the formation of ruts on an asphalt concrete pavement is studied. The maximum total rut depth on the road section under consideration reaches 110 mm. 715 buses and 25 trucks pass along a separate lane of the road per day, the relative rutting impact of which is from 5.68 to 16.41 compared to the design vehicle. The design of the road pavement on the experimental section with a total thickness of 48 cm is too weak for the actual traffic flow, which was the main reason for the premature failure of the road due to unacceptable rut sizes on the asphalt concrete pavement. [ABSTRACT FROM AUTHOR]

This article examines a distinctive and debated social group called the "Baboos" in late colonial India, particularly in Bengal. The Baboos represented the Western-educated, aspiring middle class who were integral to the British administration. They were often viewed skeptically for adopting the English language and Western lifestyle. This study delves into the quotidian lives of the Baboos, particularly their interactions with the colonial rulers in public transport, which became a crucial contact zone. Despite facing racial conflicts and discrimination in these shared spaces, the Baboos were not passive victims. They used diverse strategies to combat injustices and voice their grievances publicly. Within this larger narrative of discriminating treatment, another power narrative was played out by the Baboos among their own population. Conscious of their distinct functional status, the Baboos sought to distance themselves from those Indians who did not match their ideas of "respect". Everyday experiences formed the basis of the public outrage reflected continually in regional newspapers and, subsequently, in the larger narratives of resistance and nationalism. How the Baboos negotiated their position in the public spaces sheds light on their claims of civil rights and their ways of using the colonizer's tropes of equality, justice, and fairness back at them. [ABSTRACT FROM AUTHOR]

Public transport disruptions are conducive to disorientation narratives in which the temporal aspects of the experience are central, but it is difficult to collect psychometric data at the moment of disruption to quantify the occurring underlying feelings. We propose a new real-time survey distribution method based on travellers' interaction with disruption announcements on social media. We analyse 456 responses in the Paris area and find that travellers experience time slowing down and their destination feeling temporally farther away when undergoing traffic disruptions. Time dilation is more pronounced for people filling out the survey while still presently experiencing the disruption, suggesting that over time people remember a compressed version of their disorientation. Conflicted time feelings about the disruption, e.g., both faster and slower feelings of the passage of time, appear the longer the recollection delay. Travellers in a stopped train seem to change their itinerary not because the alternative journey feels shorter (it does not), but because it makes time pass faster. Time distortions are phenomenological hallmarks of public transport disruptions, but these distortions are poor predictors of confusion per se. Public transport operators can alleviate the time dilation experienced by their travellers by clearly stating whether they should reorient or wait for recovery when incidents occur. Our real-time survey distribution method can be used for the psychological study of crises, where a timely and targeted distribution is of paramount importance. [ABSTRACT FROM AUTHOR]

In view of success stories of unicorn startups from the sharing and gig economy such as Airbnb, DiDi, or Uber, it is not surprising that postal service providers try to transfer the sharing idea toward their last-mile delivery services: owners of under-used assets (here private crowdshippers traveling anyway) are connected with users willing to pay for the use of these assets (here postal service providers having to deliver parcels). In this paper, we consider a special form of crowdshipping where public transport users, steered by a smartphone app, pick up parcels from parcel lockers, take these shipments with them on their subway rides, and deposit these parcels into other lockers. Finally, the actual recipients can pick up their shipments from their most convenient parcel lockers, e.g., on their own way back home from work. We formulate the optimization problem that matches crowdshipping demand and supply and determines the routes along lockers and crowdshippers each parcel takes. Specifically, we allow that each parcel is moved by multiple cooperating crowdshippers and solve this problem with different objective functions capturing the individual aims of the main stakeholders: shippers, crowdshippers, recipients, and the platform provider. We evaluate the relationship of these objectives and quantify the efficiency loss of a more restricted matching policy, where only a single crowdshipper can be assigned to each parcel's complete path between origin and destination. Finally, we also explore the impact of delays and investigate whether specific objectives protect against unforeseen events. [ABSTRACT FROM AUTHOR]

While extensive research has been conducted to explore factors influencing mode choices and first- or last-mile connectivity, few studies have delved into the underlying hierarchy of decision making processes. An understanding of this hierarchy, which illustrates causal relationships, is crucial for modeling travel decisions, as trip structure depends on choice behavior and vice versa. Traditional mode choice models often neglect these underlying causal relationships, necessitating the development of new models. By incorporating mediating effects of trip chaining and mode choice, alongside traditional factors, a more holistic understanding of mode choice behavior is achieved. In this study, hierarchical relationships are identified between trip chaining and mode choice in Hyderabad, India, using a structural equation modeling (SEM) method, owing to its inherent strength in handling latent causal relationships. SEM analysis provides the total effects of sociodemographic variables on mode choices and trip chain types through these causal relationships. Findings reveal that, for nonwork trips, the decision making process is simultaneous, regardless of the mode chosen. In contrast, for work trips, the decision making process is simultaneous for active and public modes, but the choice of mode precedes trip chaining for private modes. Furthermore, in this study, we learn from those who own private vehicles but use active or public transport by choice and extract the factors that had indeed motivated their choice. Confirmatory factor analysis is employed to validate the identified factors. The identified factors, coupled with the understanding of decision making hierarchy, offer valuable insights for shaping policies that can maximize the potential of active and public transport modes. [ABSTRACT FROM AUTHOR]

When transport systems are accessible and inclusive, people with disability experience dignity. Alternatively, when personal mobility is constrained by physical, social and/or communication, barriers, people with disability experience exclusion and an increasing vulnerability to indignity. This study sought to qualitatively explore the role of trains and buses in an Australian city in supporting access, inclusion and dignified mobility experiences for people with disability. Twenty-six semi-structured interviews were conducted with participants with diverse visible and invisible disabilities and were analysed thematically using Framework Analysis. The findings highlight the complexities involved with navigating public transport systems while maintaining dignity for people with disability. Accessible and inclusive information, infrastructure, and interactions with staff ensured dignified mobility experiences. If any part of a journey was inaccessible, participants were vulnerable to indignity. Dignified mobility experiences represent a complex and dynamic interaction between personal experiences and preferences, impairment-specific requirements, transport infrastructure, interpersonal experiences, and information inclusivity. Points of interest: Public transport systems can play an important role in enabling, facilitating and sustaining dignity for people with disability. People with disability experience theoretical and practical gaps when using trains and buses. Gaps result from infrastructure, environment, information, and attitudinal barriers. Universal Design, access to accessible and inclusive information, and empathic attitudes help create dignified mobility experiences for people with disability when using buses and trains. [ABSTRACT FROM AUTHOR]

In this paper, we develop the concept of a "Sustainable Mobility Guarantee". We first review existing "Mobility Guarantees", which are rather motivated by socioeconomic interests than environmental sustainability and classify them. Based on this assessment, we define a Sustainable Mobility Guarantee, which extends existing approaches with environmental interests. It is an emerging concept in policymaking to ensure a certain level of mobility without the need for private cars - particularly in rural areas - but it is still in its infancy and lacks clear definitions. The concept embraces the idea of Classical Mobility Guarantees while seeking to enable and promote the use of non-automobile modes for everyday travels for everyone, not only for specific trip purposes like commuting, nor for specific target groups like the elderly. We then discuss the practical implementation and financial feasibility. Implementation is possible through programmatic or regulatory approaches, which may serve as a potential transitional basis for legal regulation. At least in developed countries, implementing mobility services realizing a Sustainable Mobility Guarantee is deemed financeable, given that financial instruments now subsidizing automobile use are shifted towards implementation of the guarantee, without being detrimental to the economy. • Policy, laws and regulations to guarantee human mobility are reviewed and classified from several perspectives. • A Classical Mobility Guarantee aims to provide fallback for people without car or ability to drive. • A Sustainable Mobility Guarantee aims to motivate people to shift away from cars both in cities and rural areas. • The concept for a Sustainable Mobility Guarantee is developed and transition is discussed. • An analysis of implementation cost is estimated and discussed using Austria as a case study. [ABSTRACT FROM AUTHOR]

The functioning of modern urban environments relies heavily on the public transport system. Given spatial, economic, and sustainability criteria, public transport in larger urban areas is unrivaled. The system's role depends on the quality of service it offers. Achieving the desired service quality requires a design that meets transport demands. This paper uses a data-driven approach to address headway deviations in public transport lines and explores ways to improve regularity during the design phase. Headway is a critical dynamic element for transport organization and passenger quality. Deviations between planned and actual headways represent disturbances. On lines with headways under 15 min, passengers typically do not consult schedules, making punctuality less crucial. Reduced headway regularity affects the average travel time, travel time uncertainty, and passenger comfort. Ideally, the public transport system operates with regular headways. However, disturbances can spread and affect subsequent departures, leading to vehicle bunching. While previous research focused on single primary disturbances, this study, with the help of AI (reinforcement learning), examines multiple primary disturbances in the cities of Belgrade, Novi Sad, and Niš. The goal is to model the cumulative impact of these disturbances on vehicle movement. By ranking parameter influences and using the automatic optimization of static line elements, this research aims to improve headway regularity and increase system resilience to disturbances. The results of this research could also be useful in developing adaptive public transport management systems that leverage AI and IoT technologies to continuously optimize headway regularity in response to real-time data, ultimately enhancing service quality and passenger satisfaction. [ABSTRACT FROM AUTHOR]

This paper analyses the commuting frequencies and modal choices of travellers in Melbourne, using a dataset reflecting travel behaviour before and after COVID-19. A factor analysis of 63 latent variables identified seven key factors, which were used in cluster analysis to examine the relationships between latent constructs, land use, and socio-demographic variables, as well as commuting behaviours. The analysis categorised white-collar employees into four groups based on their remote work engagement, with socio-demographics and industry type as key factors. The analysis shows that female clerical and administrative workers who worked from home during the pandemic are now returning to the office, raising gender equality concerns within society. Meanwhile, the education and training sector mandates office attendance despite the feasibility of remote work, as universities prioritise in-person attendance to attract more international students, impacting societal norms around telecommuting. The analysis revealed that saving on commute costs, reducing travel time, and spending more time with family are the among the primary factors influencing travel behaviour among white-collar employee's post-pandemic. The study found that the decrease in public transport trips is associated with increased telecommuting rather than service dissatisfaction, especially among Central Business District (CBD) employees who still rely on public transport. This trend suggests that the CBD sector's growing acceptance of remote work is reducing daily commutes, which puts additional pressure on public transport providers to sustain and improve their services. A decline in service quality could further reduce ridership, highlighting the need for consistent, high-quality public transport. Furthermore, the study found that increased telecommuting is likely to reduce car trips in the future, especially among healthcare and social workers who prefer driving due to public transport's unreliability for their demanding schedules. By examining variables like the advantages and disadvantages of working from home, convenience, accessibility, and the efficiency of public transport, this study enhances the understanding of transport behaviour and underscores the need to improve public transport reliability to support sustainable cities as remote work grows. [ABSTRACT FROM AUTHOR]

Transfer behavior is a critical factor influencing the travel efficiency of public transportation passengers. To address the potential group heterogeneity, the present work developed an integrated Classification and Regression Tree-Multiple-Cox Proportional Hazards (CART-Multi-Cox) model for transfer behavior analysis using smart card data in Shenzhen, China. Specifically, passengers are first grouped into different types based on transfer behavior features, and the influence of various independent variables on the transfer duration of different passenger groups is then examined. The results reveal that the proposed CART-Multi-Cox model is able to account for the heterogeneity effect and provides a deeper understanding about passengers’ transfer behavior and its underlying influencing mechanism. The findings offer valuable references for refined transfer behavior management and help enhancing the competitiveness of public transportation. [ABSTRACT FROM AUTHOR]

AbstractPublic transport inherently involves encounters with other people. For women, negotiating everyday overcrowded, unsafe, and unreliable conditions is a major barrier to accessing public transport mobility that triggers emotions. Using qualitative research methods – in-depth interviews and visual surveys – this study delves beyond understanding the barriers and looks at the affective realm to comprehend how affects and emotions shape accessibility, acceptability, and affordability of public transport for women in Kolkata. The disruptive affects of overcrowded, unsafe, and unreliable conditions produce emotional ordeals, increase travel time and costs, and restrict mobility. The sense of despair that emerges compels women to adjust, accept, and even opt out of overcrowded, unsafe, and unreliable public transport more often than not. This paper argues that affects, emotions, reactions, and consequences are entangled and impact the accessibility, acceptability, and affordability of public transport. The contribution of this paper lies in bringing to the fore the need for feminist inquiries into gendered mobility inequalities and the role of affects and emotions therein. [ABSTRACT FROM AUTHOR]

In most urban areas, mobility is predominantly reliant on automobiles, leading to significant negative environmental impacts, such as noise pollution, air pollution, and greenhouse gas emissions. To meet the objectives of the Paris Agreement, urgent action is required to decarbonize the mobility sector. This necessitates the development of assessment and planning tools to create effective decarbonization scenarios. Urban mobility must evolve to reduce dependency on fossil fuels by increasing public transport options and promoting active modes of transportation. This research presents a methodology to estimate the modal share required to shift car users to active modes and public transport, thereby achieving future CO2 emission reduction targets in the road transport sector. A case study in Braga, Portugal, demonstrates that to meet the 2040 target of 59,150 tons of CO2, 63% of trips must be made using active modes (e.g., walking and cycling) and 32% by public transport. [ABSTRACT FROM AUTHOR]

The establishment of an evaluation model for bus operation efficiency is crucial in determining the bus routes along the rail transit line that require optimization, laying the theoretical foundation for the integration of the two networks. Firstly, a qualitative and quantitative method was used to select bus routes that have a high correlation with the rail transit system and are of research significance. Secondly, an evaluation system was constructed based on the rationality of the bus network itself and the synergy between the two networks. Finally, the Pareto optimal cross-efficiency model was employed to determine the operation efficiency of the bus routes along the rail transit line. Taking the example of Line 1 in Nanchang, 25 bus routes along the line were identified and empirically analyzed. The results indicate that the Pareto optimal cross-efficiency models score is more readily accepted by all DMUs (decision-making units). The data analysis reveales that the bus network in Nanchang exhibites good self-rationality. However, in terms of synergy between the two networks, there is room for improvement by optimizing route directions and adjusting route duplication coefficients to enhance their collaborative nature. Finally, this paper is based on the Pareto cross-efficiency mean values of both factors, the 25 bus routes were categorized into four cases, providing practical and valuable insights for the managers and decision-makers of the public transportation system. [ABSTRACT FROM AUTHOR]

This article investigates the factors behind the likelihood of experiencing a specific type of mobility situation. The case of commuting by public transport in Greater Mexico City is analysed. A one-way ANOVA with post-hoc procedures and three multinomial logistic regression models are used to assess the extent to which transport-, land use- or socio-economic-related variables influence the likelihood of experiencing a specific mobility situation. The results show that the mobility situations of workers are primarily influenced by the socio-economic characteristics of commuters, followed by land-use patterns and the availability of transport systems, respectively. This means that in addition to transport-related policies, reducing commuting disparities in urban regions will require policies able to reduce socio-economic inequalities and influence the urban structure. [ABSTRACT FROM AUTHOR]

COVID‐19 brought public health challenges to the public transport system throughout the world. As a result, a range of response measures were implemented to ensure the safety of passengers while maintaining a functioning system. This paper explores the responses of public transport agencies in New Zealand's metropolitan cities (Auckland, Christchurch and Wellington) to the COVID‐19 pandemic by examining their physical and communication measures. We analysed public transport agencies' websites to understand the response measures implemented, including the accessibility of COVID‐19‐related information, and the communication of information via websites and social media platforms. The results show that 13 service responses were implemented across the three public transport agencies, with Auckland implementing the most measures. Seven infrastructural responses were implemented, with Christchurch implementing all seven. Wellington was found to be the public transport agency that used social media the most during the pandemic. The website accessibility findings suggest that the more accessible a public transport agency's website was, the less information was present. The research concludes that all three public transport agencies in New Zealand performed reasonably well and were able to maintain a safe and responsive public transport system. [ABSTRACT FROM AUTHOR]

A current topic that has surfaced among Public Transport Companies (PTCs) is the selection of alternative fuels for their bus fleets. Both European and Italian regulations are pushing toward abandoning diesel fuel and the consolidation of alternative traction power sources, such as battery-electric vehicles, fuel-cell electric vehicles, and hydrogen-electric vehicles. The literature has provided some approaches toward assessing this selection such as multicriteria-decision-methods in some countries in the world. However, not enough specific attention has been paid to cost criteria, experts involved, and the type of service required. This paper intends to address these gaps by applying an integrated method, which includes: (i) the Analytical Hierarchy Process (AHP) to define the weights of criteria; (ii) the ELimination Et Choix Traduisant la REalitè I (ELECTRE I) to find a good compromise solution among the fuel alternatives and (iii) a simple Weighted Sum Model (WSM) to refine ranking. This integrated method was applied in Italy involving a panel of experts from whom the data was collected. Different fuel alternatives for both urban and interurban services and with and without funding are discussed. The results provide a useful tool supporting PTC policies, which aims to rationalise and prioritise bus fuel alternatives when deciding on fleet renewal. • Bus fuel selection studies lack cost criteria, experts involved, and service type. • The multicriteria-decision-methods (MCDM) considers the previous issues. • An integrated MCDM method selects fuel alternatives for urban/interurban bus services. • Results prioritise the economically advantageous fuels for with and without funding. [ABSTRACT FROM AUTHOR]

Accessibility is commonly defined and operationalised through objective measurements, such as travel time and physical distance to destinations; however, there is a lack of empirical studies capturing perceived accessibility from individual perspectives. With the aim of sustainable transport for inclusive communities, it is crucial to investigate the impact of socio-economy and travel mode on perceived accessibility and key driving factors of perceived safety and service quality. Through the collection of primary data from one of the fastest-growing suburbs in Melbourne, this study examined variation of perceptions towards accessibility, safety, and service quality among diverse social groups and travellers using different modes of transport. The findings of this study would assist transport planners in making informed decisions in creating inclusive transport networks that can improve community health and well-being. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of quantitatively assessing ride comfort in tram travel in Growing Urban Environments, where multiple influencing factors complicate developing a unified evaluation index system. A comprehensive evaluation framework based on cloud theory is proposed to overcome this challenge. The approach involves defining five‐level comfort evaluation grades to capture passengers' experiences and perceptions accurately. The Criteria Importance through Inter‐Criteria Correlation (CRITIC) method is employed to ensure objectivity to establish objective weights for evaluation indices. Subsequently, a cloud model algorithm is utilized to generate evaluation benchmark and actual result clouds, providing intuitive representations of the evaluation outcomes. The efficacy and rationality of the methodology is illustrated through a case study focusing on Suzhou Tram Line 2. This research contributes valuable insights for enhancing public transportation experiences in new urban settings by offering a systematic and objective approach to assessing tram ride comfort. [ABSTRACT FROM AUTHOR]

This study investigated key physical and social barriers to accessing public transport in Dhaka, Bangladesh, and how the unequal accessibility of transport leads to the social exclusion of older adults. Employing a transport disadvantage perspective and drawing on visual surveys and in-depth interviews, the study explores the context and lived experiences of older adults using public transport in their everyday lives. Difficulty in accessing buses due to overcrowding and congestion, struggling to get on rickshaws due to height, avoiding CNG (an autorickshaw) and cabs due to high fares, disliking Laguna (a small four-wheeler human haulier for carrying passengers) for compact seating arrangements, undesirable behavior, and social attitudes discourage older adults from participating in social activities and produce a feeling of social isolation and exclusion. Hence, more inclusive transport policies are essential in low- and middle-income countries to reduce transport-related social exclusion and improve the well-being of older adults. [ABSTRACT FROM AUTHOR]

Abstract Individual mobility is driven by activities and thus restricted geographically, especially for trip destination prediction in public transport. Existing statistical learning based models focus on extracting mobility regularity in predicting an individual's mobility. However, they are limited in modeling varied spatial mobility patterns driven by the same activity (e.g. an individual may travel to different locations for shopping). The paper proposes a deep learning model with activity, geographic and sequential (DeepAGS) information in predicting an individual's next trip destination in public transport. DeepAGS models the semantic features of activity and geography by using word embedding and graph convolutional network. An adaptive neural fusion gate mechanism is proposed to dynamically fuse the mobility activity and geographical information given the current trip information. Besides, DeepAGS uses the gated recurrent unit to capture the temporal mobility regularity. The approach is validated by using a real‐world smartcard dataset in urban railway systems and comparing with state‐of‐the‐art models. The results show that the proposed model outperforms its peers in terms of accuracy and robustness by effectively integrating the activity and geographical information relevant to a trip context. Also, we illustrate and verify the working mechanism of the DeepAGS model using the synthetic data constructed using real‐world data. The DeepAGS model captures both the activity and geographic information of hidden mobility activities and thus could be potentially applicable to other mobility prediction tasks, such as bus trip destinations and individual GPS locations.

Abstract Metro systems play an important role in reducing urban traffic congestion and promoting the sustainable development of urban transport in megacities. With the expansion of a metro network, transfer stations are necessary for increasing the service connectivity of a metro network. An accurate estimation of transfer passenger flow can help improve the operations management of a metro system. This study proposes a data‐driven methodology for estimating the transfer passenger flow volume of each transfer station in a metro network by mining smart card data. The estimated transfer passenger flow data are visualized to show the spatial‐temporal distribution characteristics of metro transfer passenger flow. The case study results of the Shenzhen Metro network demonstrate that the proposed data‐driven methodological framework is very effective in estimating different types of transfer passenger flows, such as total transfer passenger flow, hourly transfer passenger flow, and inbound and outbound transfer flows at each transfer station. The spatial‐temporal distribution characteristics of transfer passenger flow can be very useful for designing effective and efficient passenger flow management measures to ensure the safe and efficient operation of a metro system.

Abstract Improving travel time by public transport is a major task for city planners and policy makers to increase its competitiveness relative to cars which can be facilitated by implementing public transport preferential infrastructure treatments such as signal priority. We study the impact of one such preferential treatment, signal priority, on accessibility to jobs between 2015 and 2022 in Warsaw, Poland, which implemented signal priority on 187 intersections during this time period. We develop a method to extract inter-stop travel times from the General Transit Feed Service. We find that signal priority implementation lead to (1) a travel time decrease over the network by 6.7%, (2) an increase in accessibility by 5–8.5%, (3) a full signal priority setting drives the accessibility change over time, and (4) the location of SP and travel time segments at the entry point to high-density jobs drives accessibility change. Our analysis provides a method to help decision makers evaluate the impact of signal priority on accessibility to jobs. Our results indicate significant effectiveness of signal priority implementation.

Abstract The environmental commitment of public transport authorities plays a role in addressing the challenges ahead. After the COVID-19 pandemic, we can analyze the strength of green commitments during that turbulent time. Green public procurement (GPP) is a government tool dedicated to mitigating the environmental impact of public acquisitions. These actions can be monitored as an indicator that captures efforts for green actions by organizations. GPP adoption rates among public transport suppliers are comparable across countries because they operate in the same sector and share characteristics that facilitate comparison. In this study, the largest public transport suppliers in 38 European cities are compared from 2010 to 2023. A subsample of 13,280 contract notices was employed for the public transport sector from the Tender Electronic Database and GPP adoption was found to be higher on bus vehicle acquisitions than on tramway/metro vehicle acquisitions. During the COVID-19 pandemic, there was a marked GPP fall. These findings also indicate that while GPP adoption rates are higher among the 38 large public transport suppliers compared with medium and lower ones, the largest ones are not the front-runners in terms of GPP adoption. Our results suggest that environmental priorities are not as significant as one might expect.

In our three-year project, the team set the final goal as a proposal for future cities and public transportation linkages in the context of cultural and creative activities in cities. As the project leader, the author first introduces a basic discussion of cities and urban public transport modes, followed by an analysis of subjective accessibility related to well-being. Second, the author introduces field surveys in New York, London, and Wien as advanced cities with excellent cultural and creative activities, as well as Toyama City in Japan, where the importance of public space redesign related to quality public transport in conjunction with cultural and creative activities is identified. Finally, the author summarizes the conclusion of the research project, including the proposal as “Yoin City” (city or district where aftertaste of any cultural and creative activities is highly respected mainly with excellent design of urban public spaces and public transport services) with “new local” concept primarily for middle-sized cities in Japan.

Public transport focuses on meeting the transport needs of people both within the city and in the suburban area. Passenger transport is a key element of sustainable development and improving the quality of life in agglomerations because it provides mobility for residents and tourists. In recent years, residents have become increasingly willing to use public transport. However, this trend was disrupted as a result of global changes taking place in the years 2019 - 2022. The aim of this publication was to analyse and assess the impact of crisis situations on the implementation of transport processes using the example of public transport in Warsaw. It has been shown that events such as the COVID-19 pandemic or the war in Ukraine also had a significant impact on the functioning of transport processes in Warsaw public transport. The study made it possible to identify recommendations aimed at securing the operation of public transport in the event of similar threats in the future.

Many researchers have explored public transport assignment methodologies employing transport modelling software. Nevertheless, there remains a gap in evaluating real-world public transit networks utilizing diverse assignment procedures within Visum software. This paper introduces a thorough comparison of algorithms involved in public transport assignment processes, using the transport model of the city of Kryvyi Rih in Ukraine. The three scenarios of the model were developed depending on the public transport assignment procedure: headway-based, transport system-based utilized to all links, turns, and major turns in the network graph, and transport system-based applied only to the links, turns, and major turns traversed by the active public transport lines. The model of the network comprises 13 transport systems, 7 transport modes, 27598 links, 10097 nodes, 83270 turns, 238 zones, 1748 connections for private transport, 3013 connections for public transport, 534 stops, 1165 stop areas, 1190 stop points, 130 lines and 218 line routes. The transport demand model encompassed 14 demand segments. Compared to the outputs of the model calculation using the headway-based procedure, in the scenarios with transport system-based assignment, passenger flows on rail tram lines significantly decreased. Also, the results of scenarios with transport system-based assignment showed that the passengers extremely use parallel streets for travel from an origin to a destination. The modelling outputs for an actual urban network illustrate that the choice of the shortest route in the transport system-based assignment is closely linked to the main urban roads. This circumstance could potentially result in a rise in the number of transfers needed to sustain accessibility to districts residing far from the central highway.

The COVD-19 pandemic has changed the mobility patterns of city dwellers worldwide. These changes apply to the number of trips made, their durations and directions as well as transport modes chosen for travelling purposes. In general, although the number of trips decreased, the use of cars increased and that of public transport declined. These mobility changes were induced by the fear of travelling in crowded vehicles and the extent of restrictions introduced by the governments. The effects of such changes are hard to assess and their evaluation is a complex issue. Based on data available about the transportation system in Warsaw and analysis of Big Data (comprising SIM card movements, acquired from mobile phone network operators), a research project has been carried out under the “IDUB against COVID-19” programme. Transportation models had been built which enabled estimation of the number of trips made at each stage of the pandemic in the spring 2020 and identification of differences through comparison with the models developed for the pre-pandemic conditions (year 2019). The calculations enabled assessment of the social costs of the pandemic associated with the urban transportation system, brought about mostly by changes in using private and public transport modes. The cost efficiency of public transport decreased as a result of limits on the number of passengers per vehicle introduced by transport authorities.

Purpose – The purpose of this paper is to analyse museums and theme parks as a tourist package and how the proximity of airports to the city and public transport influence the development of this tourist package to stimulate tourism demand in cities. Design/methodology/approach – Qualitative and quantitative indicators have been applied in our methodology to measure the most visited European theme parks and museums from 2012 to 2022. Moreover, the localisation of airports has allowed us to address the importance of theme parks and museums in cities and their regional economies. Findings – The results suggest that the location of the city, entertainment complementary activity, airport proximity, intermodal passenger transport, air and train accessibility, tourism demand and supply, and a high concentration of population in cities have a high influence on the development of a tourist package that includes museums and theme parks to stimulate the tourism demand in European urban cities. London and Paris are two of the most visited cities in the world, and these are the most attractive European cities for tourists in terms of efficiency because tourists can optimize much better their space and time to visit the city’s tourist attractions during their holidays. Another important finding is that the public transport service plays an important role in museums and theme parks’ visits and the optimization of space-time for tourists when they are visiting a city and its tourist attractions on holidays, especially subways, trains and buses. Although time-space measures of accessibility in public transport in cities must be improved to optimize the time of the native population and tourists. Originality/value – This research shows the complementary role of museums and theme parks as an attractive tourist package and an entertainment, cultural and educational activity to improve the quality of tourism supply and redistribute tourist flows in European countries. Moreover, there are limited studies that tackle the theme of parks and museums in a tourism context.

Abstract This study addresses the challenge of quantitatively assessing ride comfort in tram travel in Growing Urban Environments, where multiple influencing factors complicate developing a unified evaluation index system. A comprehensive evaluation framework based on cloud theory is proposed to overcome this challenge. The approach involves defining five‐level comfort evaluation grades to capture passengers' experiences and perceptions accurately. The Criteria Importance through Inter‐Criteria Correlation (CRITIC) method is employed to ensure objectivity to establish objective weights for evaluation indices. Subsequently, a cloud model algorithm is utilized to generate evaluation benchmark and actual result clouds, providing intuitive representations of the evaluation outcomes. The efficacy and rationality of the methodology is illustrated through a case study focusing on Suzhou Tram Line 2. This research contributes valuable insights for enhancing public transportation experiences in new urban settings by offering a systematic and objective approach to assessing tram ride comfort.