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Background: Excessive car use hampers progress toward tackling global health challenges, including climate and sustainability issues, and is linked to lower physical activity. Local communities have been developing solutions through bike buses. This paper, one of the first on bike buses, explores how a bike bus is perceived by other road and place users. Methods: An interdisciplinary survey instrument with dialogic-style questions was distributed on flyers to road and place users on 1 bike bus route including when the bike bus was passing. Responses were thematically analyzed using analytic framing to identify themes and subthemes. This paper focuses on 2 domains related to physical activity's link to the global health challenges of climate change and sustainability issues of excess car traffic: climate actions and community-level activism. Results: Overall, 172 responses were received from 542 distributed flyers (31.8%). The climate actions domain identified a bike bus as a solution that creates a transport mode shift, reduces emissions, and improves air quality. Themes associated with community-level activism domain include perception that a bike bus is a form of activism or a protest and that it is a disruption to the status quo on the roads. Conclusions: Our findings indicate that this active mobility practice goes beyond the utility of getting children to school and being a way to promote physical activity. A bike bus is seen as local community action that could create a transport mode shift, draw attention to road space allocation, and help tackle global health challenges. [ABSTRACT FROM AUTHOR]

School buses are a prevalent mode of school travel that may negatively affect students' academic performance due to numerous factors, including longer commutes. These extended travel times can introduce or exacerbate mental and physical stressors, including air pollution exposure and bullying, while reducing opportunities for health‐promoting activities like physical activity and sleep. While a few researchers have explored the effects of school bus transportation on academic achievement, the research is limited. In this study, we used data from two major Canadian cities, Toronto and Ottawa, to investigate the relationship between the proportion of students commuting by bus to and from school and the percentage meeting standards on standardized tests. We employed beta regression models to analyze performance in reading, writing, math, and literacy across Grades 3, 6, 9, and 10 while controlling for family and income variables that may influence school travel mode and student achievement. Our findings indicate a significant inverse correlation between school bus transportation and academic achievement for Grade 10 literacy. Longer commutes appear to impair academic performance, given that Grade 10 students presumably spend more time on the bus than younger students. Notably, the negative effects on literacy outcomes are greater than on math. Key messages: Our study identified a significant negative correlation between school bus travel and Grade 10 literacy performance in two major cities.Longer commutes likely hinder academic achievement, given that Grade 10 students presumably spend more time on the bus than younger students.The adverse impacts on literacy outcomes are more pronounced than on math performance. [ABSTRACT FROM AUTHOR]

The Léman Express (LEx) is Europe's largest cross-border rail network. As the backbone of public transportation that connects Geneva with its French suburbs, the LEx should contribute to increasing sustainable mobility and to achieving the 2050 carbon neutrality objective. Accompanying measures such as new bus routes and tramways connected to LEx stations as well as bicycle lines, park and ride, and pedestrian facilities should be implemented to ensure that LEx achieves its full impact on the modal shift and active mobility. However, the findings in this study demonstrate that more than half of the LEx's accompanying measures are overdue; planning quality, national co-funding, and municipal support are key factors for reducing delays in their implementation. Notably, these empirical findings hold across the Greater Geneva area despite the institutional peculiarities of the Swiss and French political and administrative systems. This case study adds to the literature regarding European border studies by analysing the consequences of a cross-border environment on territorially bounded projects. [ABSTRACT FROM AUTHOR]

Commuting flows refer to the regular movement of people from their homes to workplaces. The spatial heterogeneity of commuting flows indicates the uneven spatial distribution of places of residence, employment, or job-residence connections. Understanding the characteristics of spatial heterogeneity in commuting flows is vital for effective transportation planning. However, limited by the scarcity of flow data, traditional research on commuting flows predominantly focuses on the spatial distribution of employment, residence, and job-residence connections individually, which fails to unveil the spatial heterogeneity of commuting flows. In this study, we examined the spatial heterogeneity of commuting flows in Beijing using mobile phone data. We analyzed the degree of heterogeneity and the aggregation scale of commuting flows. The results showed that (1) the degree of spatial heterogeneity varies between different regional pairs, and (2) the aggregation scale of commuting flows varies with distance; moreover, the longer the distance, the larger the aggregation scale of commuting flow distribution, and dominant heterogeneous clusters expand from the center to the periphery. These findings enhance the strategic planning of public transit. In less densely populated areas such as those outside the Fifth Ring Road, efficiency can be boosted by new bus routes. In contrast, denser areas such as those within the Third Ring Road, may benefit from an integrated approach: establishing new rail systems alongside expanded bus services to optimize commuting. [ABSTRACT FROM AUTHOR]

This paper proposed an eight-phase transit signal priority control method, CBQL-TSP, based on a hybrid decision-making approach combining cooperative game theory and reinforcement learning, aiming to address the low efficiency of transit signal priority control in intelligent transportation systems. The method abstracted the allocation of bus signal priority into a multi-objective decision-making problem with an eight-phase signal sequence, refining the signal phase sequence into priority and non-priority phases, and constructing a cooperative game model. The paper introduced a hybrid decision-making algorithm, CBQL, to solve the multi-objective decision-making problem of eight-phase signal timing. The algorithm calculated the marginal contributions of each game member by solving the Shapley value function and constructed the state transition probability equation based on the Shapley value ratio. Compared to conventional control methods, CBQL-TSP incorporated the fairness principle of cooperative game theory and the adaptive learning ability of Q-learning, enabling dynamic adjustment of signal timing based on real-time traffic conditions. This method offered higher flexibility and efficiency in priority signal control. This paper established a simulation test platform to compare the average waiting car count and average travel time under different demand levels, evaluating the stability and efficiency of the method. The experimental results demonstrate that the proposed method exhibits higher stability. Furthermore, the overall average travel time is reduced by approximately 24.57%, and the average travel time for buses is reduced by about 37.40%. CBQL-TSP demonstrates higher control efficiency at bus-priority intersections, significantly reducing both overall and bus average travel times. [ABSTRACT FROM AUTHOR]

Pre-peak fare discount policies have become increasingly common in urban transit services and show potential to spread morning peak-hour demand. This study analyzes the departure time choice behavior of interregional bus passengers during morning hours. A mixed logit model is applied to estimate the probability of shifting departure time as a function of fare discount rate, in-vehicle congestion, and other influential factors, accommodating heterogeneity of passenger preferences. The analysis data are obtained through a stated preference survey, which is conducted to passengers who regularly use the interregional bus in Seoul metropolitan area. Choice models are segmented by departure time periods (peak, pre-peak, and post-peak) and occupation types (fixed time worker, flexible time worker, and student). Marginal utilities of the unobserved preferences are estimated to suggest policy implications. From the experimental analysis, target passengers for shifting departure time during peak hour are suggested as flexible time workers and students. [ABSTRACT FROM AUTHOR]

Taxis not only substitute for but also complement bus transit. With the complementary relationship, taxi trips reveal the origin-destination pairs where the level of bus service is low. This study attempts to utilize taxi data to identify potential weak links in the bus network. An evaluation methodology is proposed using taxi trips to evaluate the bus routes by incorporating accessibility measures at the stop level and convenience measures at the route level. With over 52,000 taxi orders collected in Jiading District of Shanghai, China, the corresponding alternative bus trips are simulated and then classified into 16 types of patterns according to the stop-level and route-level measures. The top five types, accounting for 78% of all trips, are selected for visual and quantitative analysis. The findings show that the proposed methodology can well assist bus agencies to improve service efficiency with better planning and design of bus routes. [ABSTRACT FROM AUTHOR]

Recess, the bus ride home, the school corridor and other grey areas are ambiguous for both teachers and students and fall under less institutional regulation. The purpose of this study was to examine the ways teachers would react when they encounter students' informal political comments in the grey areas. We presented vignettes to 71 Palestinian teachers and 64 Jewish teachers in Israel and asked them what they would have done in a similar situation in their classroom. Teachers' reactions were on a continuum ranging from avoidance and passivity to engaging in multidimensional mediation. Differences between Jewish and Palestinian teachers were found, and they reflect power relations between the Jewish majority and the Palestinian minority, which involve Palestinian teachers being more reluctant to engage in controversial public issues due to their minority status. [ABSTRACT FROM AUTHOR]

Faced with the land use heterogeneity and trip distribution non-equilibrium along the corridor connecting urban district and rural area, the operation characteristics of the all-stop bus, the express bus and the shuttle bus running on the transportation corridor should be given full consideration, as well as the tradeoff between passenger trip cost and bus operation cost during the peak-hour period. In order to realize the reliable decision of bus resources configuration for urban-rural public transportation, a bi-objective programming model of multi-modal urban-rural bus operation scheme is established, where the decision variables include the departure frequency of different bus modals, the terminals of shuttle buses, and the stop scheme of express buses, under the constraints of departure interval, passenger volume, vehicle occupancy, section capacity usage and modal competition. To validate the feasibility of proposed optimization model, an urban-rural bus corridor from Rural Jasmine Ecological Park in Hanjiang District to West Xiangyang Bridge in Songqiao Town was chosen as a study case, and the operation organization scheme of three bus modals were solved by the mathematical solver Lingo using mixed integer programming. Meanwhile, the scheme differences under different subobjective weights were discussed, taking into account the uncertain passenger demand and operation supply. The result shows that the increase of passenger trip cost weight will increase the departure frequency of all three bus modals, while the increase of operation cost weight will decrease the total operating vehicles, but the stop frequency at middle stations for express buses will increase accordingly. Compared to the current operation scheme, the optimized scheme can greatly enhance the section capacity usage at a slight sacrifice of passenger trip time with fewer bus vehicles. [ABSTRACT FROM AUTHOR]

Performance-based subsidy allocation schemes are typically intended to satisfy a single policy goal (e.g. social welfare maximization) and often do not include objective approaches to quantifying bus service efficiency. This paper proposes a framework for network data envelopment analysis and introduces an innovative transit subsidy allocation scheme with a fixed budget that fulfills multiple policy criteria. The proposed basic scheme minimizes the maximum deviation from efficient allocation in proportion to the operating scales across all routes in a two-stage production system. Multiple policy criteria are then added to the basic scheme as additional goal components. The proposed scheme is evaluated by using an empirical dataset of 344 subsidized intercity bus routes collected from 20 Taiwanese bus operators. The results demonstrate that the subsidies allocated on the basis of the proposed scheme can satisfy the policy criteria incorporated into the scheme. The proposed modeling framework is flexible, and therefore, local governments can easily incorporate policy criteria into the scheme according to their own interests and needs. [ABSTRACT FROM AUTHOR]

Public transportation system is one of the most effective ways to conserve energy and reduce carbon emissions. However, the traditional public transportation system does not provide customized service and cannot guarantee the arrival time to destination. To address these issues, we formulate the minimum shared bus scheduling problem to minimize the number of shared buses such that all orders can be completed under constraints of deadlines and capacity of shared bus. We propose the approximation algorithms, S‐MBSA for the shared bus with strong endurance and E‐MBSA for the large‐scale order scenario, to solve the minimum shared bus scheduling problem. We further formulate the constrained maximum revenue shared bus scheduling problem to maximize the revenue under the limited number of shared buses, and propose an approximation algorithm, CMRBSA, to find the shared bus route schedules. Through the extensive simulations, we demonstrate the significant superiority of S‐MBSA and E‐MBSA in terms of number of shared buses. Furthermore, CMRBSA outperforms the benchmark algorithms significantly in terms of revenue. [ABSTRACT FROM AUTHOR]

To improve the traffic efficiency of bus at a group of intersections and reduce their delay, this paper develops a speed guidance strategy for buses under travel time control at intersection groups. The approach considers the influence of bus departure time, bus station arrival rate, and bus station dwell time. Simulation experiments are carried out on three consecutive intersections along Jinshan Avenue in Fuzhou, China. Results show that the average travel time of buses, the average delay of buses, and the average delay per capita in the priority direction are reduced by 5.5%, 9.9%, and 9.4%, respectively. The optimal rate of the average number of bus stops reached 15.2%. The indicators of the non-priority direction of social vehicles are not significantly affected. It shows that the efficiency of buses has improved after implementing the speed guidance strategy at the intersection groups without affecting the social vehicles as far as possible. [ABSTRACT FROM AUTHOR]

An investigation is reported on bus bunching and its spatiotemporal patterns that considers six bus routes in Kolkata City, West Bengal, India. With historical GPS data as inputs, bunching occurrences are identified using the spatiotemporal–density-based spatial clustering of applications with noise (ST–DBSCAN) algorithm. To determine the impact of bunching on various bus stops, k-means++ clustering was used on top of ST–DBSCAN, and subsequently, spatiotemporal bunching patterns were investigated. Some bus stops are consecutively impacted by bunching; however, others are impacted in an isolated manner. To capture the spatiotemporal propagation of bunching, a new indicator termed the propagation ratio is proposed, which could classify the bunching as propagating or isolated. Bunching occurrences are propagating for some bus routes and isolated for others, which justifies the need to prioritize routes displaying propagating nature. Of interest, bunching is identified on high and low-frequency bus routes, which indicates the need to relook at the operational planning of all the bus routes regardless of their frequency. At times, excessive bunching is detected during lean periods of the day, which suggests the necessity of modifying the dispatching headways that are based on passenger demand during these lean periods. The outcomes from this work further indicate that all the bus stops along a bus route are not equally impacted by bunching. The spatiotemporal cluster plots could successfully capture the initial bunching occurrence points and their variation with time, which could provide an opportunity for the operators to apply time-varying remedial measures. The insights developed from this work could be used advantageously by operators and policymakers for mitigating bus bunching and improving the urban bus service. [ABSTRACT FROM AUTHOR]

Many emerging commercial services are based on the sharing or pooling of resources for common use with the aim of reducing costs. Businesses such as delivery-, mobility-, or transport-as-a-service have become standard in many parts of the world, fulfilling on-demand requests for customers in live settings. However, it is known that many of these problems are NP-hard, and therefore both modeling and solving them accurately is a challenge. Here we focus on one such routing problem, the Ride Pooling Problem (RPP), where multiple customers can request on-demand pickups and drop-offs from shared vehicles within a fleet. The combinatorial optimization task is to optimally pool customer requests using the limited set of vehicles, akin to a small-scale flexible bus route. In this work, we propose a quadratic unconstrained binary optimization (QUBO) program and introduce efficient formulation methods for the RPP to be solved using metaheuristics, and specifically emerging quantum optimization algorithms. [ABSTRACT FROM AUTHOR]

Public transport service reliability is crucial for all stakeholders, including users, operators, and society. Bus bunching, where two or more buses on the same route travel closely together, significantly undermines service reliability. This paper reviews bus bunching, its causes and consequences, and control strategies from demand, supply, and decision-making perspectives. It identifies gaps in the literature, emphasising the need for realistic evaluations of control methods and real-world applications. The paper reveals that most bunching solutions prioritise operators over public transport users, and the trade-offs posed by these methods require further examinations. Hybrid methods combining holding with other measures have outperformed standalone holding methods but need real-world testing. User-centric approaches, such as encouraging and incentivising passengers to choose less crowded vehicles or wait, have demonstrated some potential in alleviating service bunching. However, their effectiveness in real-world applications present important research directions. In summary, the practical classification and framework presented in this review can assist policymakers in making informed and optimised decisions by considering various variables and performance measures involved in the process, and in finding balanced solutions for passenger and operator. [ABSTRACT FROM AUTHOR]

To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volumes from and to bus stops was constructed with land use elements between bus stop TAZs and the upstream and downstream collections of bus stop TAZs. Building upon this, the passenger flow volumes from and to 38 bus stops in the Xueyuan Square area of Dalian during weekday morning peak hours were taken as the experimental objects. The basic estimation models of two gravity sets corresponding to passenger flow volumes from and to bus stops were constructed using the bus travel generation based on the aggregation of area-based origin unit method and the bus travel distance impedance based on the probability density method. Finally, the reliability of the estimation method of passenger flow volumes from and to bus stops was verified by regression fitting between the surveyed values of passenger flow volume and the estimated values of the basic models. The results indicate that the fuzzy estimation and transformation of bus travel based on land use elements, which serves as a crucial lever for facilitating strategic alignment in transit-oriented development (TOD), can be effectively achieved by using the area-based origin unit method to aggregate bus travel generation and the probability density method to evaluate the bus travel distance impedance. [ABSTRACT FROM AUTHOR]

In this paper, we develop a multi-objective integrated optimization method for feeder buses of rail transit based on realistic considerations. We propose a bus stop selection method that considers the influence of shared motorcycles, which can score the importance of alternative bus stops and select those with the highest scores as objectives. The objective of the model in this paper is to minimize both the travel costs of passengers and the operating costs of the bus company. This is achieved by optimizing feeder bus routes, the frequency of departures, and interchange discounts to enhance the connectivity between feeder buses and rail transit. In addition, to ensure the feasibility of generated routes in the real road network, a genetic algorithm encoded with priority is used to solve this model. We use the Xingyao Road subway station in Kunming as an example, and the results show that the optimization method is effective. [ABSTRACT FROM AUTHOR]

Many universities are transforming campuses by responding to globally significant, locally specific, economic, political, and social imperatives. Some are implementing urban and regional transformations in higher education delivery to increase student access and diversity. Their success can depend upon infrastructures provided by other parties. Public transport is an example. Transit accessibility and equity affect quality of life, livelihoods, life course, and liveability in cities. Growing numbers of international studies consider factors shaping student travel to and from university campuses by public transport; fewer address local socio-spatial experiences of travel. Informed by debates about differential accessibility of suburban and city campuses, we examined student experiences at an Australian regional university undergoing transformation. We report on a study assessing multiple trips to and from two campuses to five destinations. Rich insights were drawn from experiences of antisocial behaviour, vulnerability, and sub-optimal service provision and reveal why some students think public transport is a mode of last resort. Universities and their stakeholders need to know more about student experiences of mobility. Such knowledge could inform tailored transport interventions and universities' willingness to encourage public transport providers to view their services as infrastructures of care. [ABSTRACT FROM AUTHOR]

A route positioning system is a technology that identifies the current route when driving from one stop to the next, commonly found in public transportation systems such as shuttle buses that follow fixed routes. This is especially useful for smaller-scale services, such as shuttle buses, where using expensive technology and sensors for location tracking might not be feasible. Particularly in urban areas with tall buildings or mountainous regions with lots of trees, relying solely on GPS can lead to many errors. Therefore, this paper suggests a cost-effective solution that uses just one camera sensor to accurately determine the location of small-scale transportation services on fixed routes. For this, this paper uses a single-stage detection network that quickly identifies objects and tracks them using a simple algorithm. These detected features are compiled into a "codebook" using the bag-of-visual-words technique. During actual trips, this pre-created codebook is compared with landmarks that the camera sees. This comparison helps to determine the route currently being traveled. To test the effectiveness of this approach, this paper used the route of a shuttle bus on the Gachon University campus, which is similar to a downtown area with tall buildings or a wooded mountainous area. The results showed that the shuttle bus's route was recognized with an accuracy of 0.60. Areas with distinct features were recognized with an accuracy of 0.99, while stops with simple, nondescript structures were recognized with an accuracy of 0.29. Additionally, applying the SORT algorithm to enhance performance slightly improved the accuracy from 0.60 to 0.61. This demonstrates that our proposed method can effectively perform location recognition using only cameras in small shuttle buses. [ABSTRACT FROM AUTHOR]

This article proposes a particular strategy to proceed with a progressive electrification of public transport systems in cities. Starting from a bus operation model, the possible electrification of two routes is analyzed, one urban and another extra-urban in the city of Pisa. An estimate is made of the energy uses associated with certain operating modes. The maximum level of consumption is estimated at approximately 280 kWh per day per bus for the urban route and excluding some special days, less than 215 kWh per day for the extra-urban route, for which a hybrid bus is proposed. Starting from an estimate of the daily consumption for the management of the two routes, the sizing of a photovoltaic (PV) plant distributed on some modular shelters which serves to power the same routes, is carried out. The resulting system has a power of the order of 190–200 kW. The modular solution is also outlined, and an installation is proposed. The analyzed case lends itself to being easily replicated. [ABSTRACT FROM AUTHOR]

Public transportation systems, including trams and buses, play a crucial role in urban traffic. However, these traditional modes of transport have some well-known drawbacks, such as long distances between stops, lengthy waiting times, and a lack of privacy. In response to these challenges, an innovative mobility concept called "FLAIT-train" offers potential solutions. The FLAIT-train operates on regular roads and aims to provide DOOR-2-DOOR transport, addressing the issues associated with fixed stops and offering increased accessibility and convenience. In its initial phase, the FLAIT-train operates on exclusive lanes, but it is designed to integrate with other traffic eventually. The vehicle technology of FLAIT-trains closely resembles that of battery electric autonomous vehicles. To assess whether FLAIT-trains can be used as a suitable alternative to conventional public transportation systems, this paper employs traffic simulations that consider key performance indicators, including the average waiting time per passenger, maximum waiting time of a single passenger, average in-vehicle time per passenger, and average occupancy rate of the vehicles. Using SUMO software ("Simulation of Urban Mobility", version 1.12.0), a night bus service scenario is meticulously designed and generated. Within this scenario, both FLAIT-trains and conventional buses are simulated under identical conditions and based on statistical data. [ABSTRACT FROM AUTHOR]

In order to enhance passenger willingness to choose buses for commuting and to reduce the operating costs and tailpipe emissions of bus companies, a bus scheduling model is established. The model aims to minimize the sum of the operating costs of the bus company, the costs associated with the loss of passengers' interest, and the cost of tailpipe emissions. It considers constraints such as maintaining an average load factor of the buses above 60%, ensuring a departure interval of greater than 5 min during non-peak hours and less than 30 min during peak hours, and limiting the maximum number of buses allocated to a route. The passenger flow is divided into peak hours and nonpeak hours according to the survey of passenger flow during each period of a bus operation on a route in Nanjing City, China. A genetic algorithm is employed to solve the proposed bus scheduling model and determine the total costs during peak and non-peak hours. After designing the parameters of the genetic algorithm, optimal departure intervals and bus numbers for a day's operation cycle on a given route are calculated using a weighting method. [ABSTRACT FROM AUTHOR]

In social networks research, geographical distance between places of residence partially explains patterns of friendship ties in semi-isolated communities like classrooms or schools. For example, individuals that live close to one another are more likely to be friends than chance alone predicts. Explaining this pattern, researchers often argue that distance approximates meeting opportunities: when individuals live nearby, they are more likely to meet, both by chance and deliberately. This paper discusses the effect of distance in post-Soviet urban space and argues that, at least in this context, shared access to public transit explains the structure of social relationships better than geographical distance. I model the pattern of friendship ties among a cohort of 145 high-school students considering the distances between residential locations and the available public transit. Results suggest that students that live along the same bus routes are more likely to be friends than those who just live close to one another. I conclude with a discussion about how research in the post-Soviet region can enrich debates about the association between the social and spatial. [ABSTRACT FROM AUTHOR]

The public transportation system is critical in meeting the demands of the rapidly growing population and increased mobility. Thus, providing and improving public services has become an urgent need in recent years. This study aims to evaluate the level of Baghdad's public transport system using a variety of criteria, including public transport availability, and comfort level. Service level is a method used to develop transport infrastructure labels based on a specific analysis. The importance of evaluating road operational performance services to improve bus service delivery is based on the concept of service level. The relatively high performance of bus service delivery can affect the level of satisfaction of its users. The availability of public transportation is analyzed in terms of frequency, service coverage, and hours. This study assesses the level of service for five specific major bus routes in Baghdad (4, 12, 45, 61, and 113). Survey processes were used to collect data. The results indicate that all lines according to service hours were at the level of service "E". While the service frequency is within the service levels "A", "B", and "C", and transit-auto travel time is within the service levels Class "B", and "C". This study contributes to being a useful guide for developing a comprehensive plan for the level of service and improving the quality of bus service. [ABSTRACT FROM AUTHOR]

In Thailand, diesel buses are notorious for their poor energy efficiency and contribution to air pollution. To combat these issues, battery electric buses (BEBs) have emerged as a promising alternative. However, their high initial costs have posed challenges for fleet management, especially for agencies such as the Bangkok Mass Transit Authority (BMTA). This study aims to revolutionize BEB fleet management by developing an energy model tailored to the BMTA's needs. The methodology consists of two crucial steps: analyzing BMTA bus routes and designing fleet management and charging systems. Through this process, the study seeks to determine the maximum number of BEBs that can be operated on each route with the fewest chargers possible. The results reveal exciting possibilities. Within the city bus landscape, two out of five BMTA bus routes show potential for transitioning to BEBs, provided they meet a maximum energy requirement of 200 kWh every two rounds. This analysis identifies routes ripe for BEB adoption while considering the limitations of battery size. In the next step, the study unveils a game-changing strategy: a maximum of 13 BEBs can operate on two routes with just four chargers requiring 150 kW each. This means fewer chargers and more efficient operations. Plus, the charging profile peaks at 600 kW from 4:00 to 8:00 p.m., showing when and where the fleet needs power the most. However, the real eye-opener? Significant energy savings of THB 10.44 million per year compared to diesel buses, with an initial investment cost savings of over 37%. These findings underscore the potential for BEB fleet management to revolutionize public transportation and save money in the long run. However, there is more work to be done. The study highlights the need for real-time passenger considerations, the development of post-service charging strategies, and a deeper dive into total lifetime costs. These areas of improvement promise even greater strides in the future of sustainable urban transportation. [ABSTRACT FROM AUTHOR]

Urban transportation systems are increasingly burdened by traffic congestion, a consequence of population growth and heightened reliance on private vehicles. This congestion not only disrupts travel efficiency but also undermines productivity and urban resident's overall well-being. A critical step in addressing this challenge is the accurate prediction of bus travel times, which is essential for mitigating congestion and improving the experience of public transport users. To tackle this issue, this study introduces the Hybrid Temporal Forecasting Network (HTF-NET) model, a framework that integrates machine learning techniques. The model combines an attention mechanism with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers, enhancing its predictive capabilities. Further refinement is achieved through a Support Vector Regressor (SVR), enabling the generation of precise bus travel time predictions. To evaluate the performance of the HTF-NET model, comparative analyses are conducted with six deep learning models using real-world digital tachograph (DTG) data obtained from intracity buses in Cheonan City, South Korea. These models includes various architectures, including different configurations of LSTM and GRU, such as bidirectional and stacked architectures. The primary focus of the study is on predicting travel times from the Namchang Village bus stop to the Dongnam-gu Public Health Center, a crucial route in the urban transport network. Various experimental scenarios are explored, incorporating overall test data, and weekday and weekend data, with and without weather information, and considering different route lengths. Comparative evaluations against a baseline ARIMA model underscore the performance of the HTF-NET model. Particularly noteworthy is the significant improvement in prediction accuracy achieved through the incorporation of weather data. Evaluation metrics, including root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE), consistently highlight the superiority of the HTF-NET model, outperforming the baseline ARIMA model by a margin of 63.27% in terms of the RMSE. These findings provide valuable insights for transit agencies and policymakers, facilitating informed decisions regarding the management and optimization of public transportation systems. [ABSTRACT FROM AUTHOR]

To optimize the evacuation process of rail transit passenger flows, the influence of the feeder bus network on bus demand is pivotal. This study first examines the transportation mode preferences of rail transit station passengers and addresses the feeder bus network's optimization challenge within a three-dimensional framework, incorporating an elastic mechanism. Consequently, a strategic planning model is developed. Subsequently, a multi-objective optimization model is constructed to simultaneously increase passenger numbers and decrease both travel time costs and bus operational expenses. Due to the NP-hard nature of this optimization problem, we introduce an enhanced non-dominated sorting genetic algorithm, INSGA-II. This algorithm integrates innovative encoding and decoding rules, adaptive parameter adjustment strategies, and a combination of crowding distance and distribution entropy mechanisms alongside an external elite archive strategy to enhance population convergence and local search capabilities. The efficacy of the proposed model and algorithm is corroborated through simulations employing standard test functions and instances. The results demonstrate that the INSGA-II algorithm closely approximates the true Pareto front, attaining Pareto optimal solutions that are uniformly distributed. Additionally, an increase in the fleet size correlates with greater passenger volumes and higher operational costs, yet it substantially lowers the average travel cost per customer. An optimal fleet size of 11 vehicles is identified. Moreover, expanding feeder bus routes enhances passenger counts by 18.03%, raises operational costs by 32.33%, and cuts passenger travel time expenses by 21.23%. These findings necessitate revisions to the bus timetable. Therefore, for a bus network with elastic demand, it is essential to holistically optimize the actual passenger flow demand, fleet size, bus schedules, and departure frequencies. [ABSTRACT FROM AUTHOR]

As an innovative public transport, the customized bus has rapidly grown. To improve the efficiency of customized bus and satisfy customers' personal requirement, a mixed-integer programming model is proposed to optimize the stop assignment for customers and route scheduling for buses with walking distance constraints and travel time constraints. As an variants of vehicle routing problem, the formulated model on large-scale instances is intractable to solve for commercial solvers. Therefore, an exact algorithm based on branch and price is developed to solve the model, in which a labeling algorithm is designed for the pricing problems. Numerical experiments and a real-world case in Dalian are conducted to validate the effectiveness of the proposed model. The computational results show that the tailored algorithm can yield an optimal solution within a significantly shorter time than that of CPLEX. Some managerial implications are also obtained based on sensitivity analysis, which may be potentially useful for bus companies. [ABSTRACT FROM AUTHOR]

To examine the risk associated with bus riding and identify transmission chains, we investigated a COVID-19 outbreak in Germany in 2021 that involved index casepatients among bus-riding students. We used routine surveillance data, performed laboratory analyses, interviewed case-patients, and conducted a cohort study. We identified 191 case-patients, 65 (34%) of whom were elementary schoolchildren. A phylogenetically unique strain and epidemiologic analyses provided a link between air travelers and cases among bus company staff, schoolchildren, other bus passengers, and their respective household members. The attack rate among bus-riding children at 1 school was ≈4 times higher than among children not taking a bus to that school. The outbreak exemplifies how an airborne agent may be transmitted effectively through (multiple) short (<20 minutes) public transport journeys and may rapidly affect many persons. [ABSTRACT FROM AUTHOR]

Providing accurate information about bus travel times can help passengers plan their itinerary and reduce waiting time. However, due to various uncertainty factors and the sparsity of single-route data, traditional travel time predictions cannot accurately describe the credibility of the prediction results, which is not conducive to passengers waiting based on the predicted results. To address the above issues, this paper proposes a bus travel time prediction intervals model based on shared road segments, multiple routes' driving style similarity, and the bootstrap method. The model first divides the predicted route into segments, dividing adjacent stations shared by multiple routes into one section. Then, the hierarchical clustering algorithm is used to group all drivers in multiple bus routes in this section according to their driving styles. Finally, the bootstrap method is used to construct a bus travel time prediction interval for different categories of drivers. The travel time data sets of Shenyang 239, 134, and New Area Line 1 were selected for experimental verification. The experimental results indicate that the quality of the prediction interval constructed using a data set fused with multiple routes is better than that constructed using a single-route data set. In the two cases studied, the MPIW of the three time periods decreased by 101.04 s, 151.72 s, 33.87 s, and 126.58 s, 127.47 s, 17.06 s, respectively. [ABSTRACT FROM AUTHOR]

Demand Responsive Transit (DRT) responds to the dynamic users' requestswithout any fixed routes and timetables and determines the stop and the start according to the demands. This study explores the optimization of dynamic vehicle scheduling and real-time route planning in urban public transportation systems, with a focus on bus services. It addresses the limitations of current shared mobility routing algorithms, which are primarily designed for simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. The research introduces an route planning algorithm designed to dynamically accommodate passenger travel needs and enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based, multi-objective heuristic A* approach, offering a solution to the inflexibility and limited coverage of suburban bus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based on Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, route length, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposed algorithmsignificantly enhances route planning speed, achieving an 80-100-fold increase in efficiency over existing models, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. The study concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalable solution for improving urban mobility. [ABSTRACT FROM AUTHOR]

On-demand transit (ODT) has been widely piloted in recent years by many transit agencies in response to changing travel behaviour and preferences among people. Some agencies have adopted ODT to replace underperforming bus routes, as part of a continuous service planning process while others incorporated it within network re-design. All these trends highlight the critical need for transit agencies to have guidance for incorporating ODT into transit network planning both at the strategic, tactical, and service planning levels. Thus, the purpose of this research is to provide a discussion of the key guiding principles to facilitate the development of transit networks with integrated on-demand and scheduled services. To achieve this goal, a thorough review of the states of practice and research was conducted. Findings from the practice review were also reinforced through ODT practitioners' engagement in Canada. This paper provides discussions on the service goals and objectives of an integrated network design and highlights the key planning requirements for developing integrated networks. At the service planning level, the paper provides a discussion on service goals, service design parameters, and scenario development of ODT service. • On-demand transit (ODT) have grown in many cities around the globe, mostly as pilot projects. • Review of the literature and practice shows that planning for ODT is based on best practices , without "built" guidelines. • Principles of planning are discussed within two applications, the network design level, and the service planning level. • Opportunities of integration and mode selection criteria are defined to integrated ODT with existing bus network. • Simulation and analytical tools are useful to complement the principles of planning in the decision-making processes. [ABSTRACT FROM AUTHOR]

In recent years, virtual reality technology, which is able to simulate real-life environments, has been widely used in the field of intervention for individuals with autism and has demonstrated distinct advantages. This review aimed to evaluate the impact of virtual reality technology on safety skills intervention for individuals with autism. After searching and screening three databases, a total of 20 pertinent articles were included. There were six articles dedicated to the VR training of street-crossing skills for individuals with autism, nine articles focusing on the training of driving skills for individuals with ASD, and three studies examining the training of bus riding for individuals with ASD. Furthermore, there were two studies on the training of air travel skills for individuals with ASD. First, we found that training in some complex skills (e.g., driving skills) should be selected for older, high-functioning individuals with ASD, to determine their capacity to participate in the training using scales or questionnaires before the intervention; VR devices with higher levels of immersion are not suitable for younger individuals with ASD. Second, VR is effective in training safety skills for ASD, but there is not enough evidence to determine the relationship between the level of VR immersion and intervention effects. Although the degree of virtual reality involvement has an impact on the ability of ASD to be generalized to the real world, it is important to ensure that future virtual reality settings are realistic and lifelike. Again, adaptive models that provide personalized training to individuals with ASD in VR environments are very promising, and future research should continue in this direction. This paper also discusses the limitations of these studies, as well as potential future research directions. [ABSTRACT FROM AUTHOR]

Accessibility to public transport is a very important factor in determining the general transport accessibility of a given area. Commonly, the bus is the only alternative solution for a car in mobility. However, it is not possible to ensure the same level of possibility of traveling by bus for each location. As a consequence, there may be areas excluded from the service when there are not enough bus connections. On the other hand, the presence of the main transport routes (e.g., regional and national roads), as well as railways, significantly increases the possibilities of mobility with the use of public transport. The aim of the article is to diagnose direct bus connections in the Wrocław agglomeration but only between the immediate surroundings of Wrocław and itself as a core. One of the secondary aims is to identify areas with limited access to those connections and to propose solutions to the diagnosed problems. Two rings of municipalities around the city have been designated as the area of the Wrocław agglomeration as the immediate surroundings of the core. The main research method is the analysis of collected numerical data and using the empirical Bayesian Kriging method to determine areas of different levels of accessibility to bus transport. In addition, the capabilities of PTV Visum made it possible to perform modeling of bus connections. The 2021/2022 timetables of bus connections providing direct access to Wrocław were taken into account. The results of the study are proposals for solutions that may constitute directions for the development of passenger bus transport in the Wrocław agglomeration in order to improve the accessibility of bus transport within the Wrocław agglomeration. [ABSTRACT FROM AUTHOR]