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Railways are a mode of public transportation that can carry large numbers of passengers and commodities and can cover long distances quickly. Based on these advantages, the railway is a mode of transportation that is in great demand by people as their choice of transportation. Thus, this will increase the intensity and frequency of departures, thereby triggering opportunities for errors to occur that threaten passengers' safety. Currently, the paper needs to present risk assessment activities in railways comprehensively. This paper will systematically review the literature on risk management concepts, risk assessment techniques, standards, and guidelines for risk management in railways. It also groups the literature to provide directions and recommendations for distances that future researchers can examine. This study encompasses a review of 60 publications on risk management, risk assessment, and risk analysis in railways from reputable and highly indexed journals over the last ten years. Subsequently, an analysis was conducted on the characteristics of models, methods, and techniques proposed in railway risk assessment. Several countries' standards, regulations, and guidelines on railway safety will also be described. The number of studies examining risk assessment at level crossings is minimal, whereas most accidents occur in this area. Many countries have legislation and guidelines but are still general and do not detail risk assessment activities in areas with a high level of risk. [ABSTRACT FROM AUTHOR]

In late 2019 the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a pandemic in 2020 and continues in 2021 and came to be known as the COVID-19 pandemic (Ciotti et al. [3]). Data from this survey are used in the paper with title I Exploring the Factors Affecting Travel Behaviors During the Second Phase of the COVID-19 Pandemic in the United State i s by Jiao and Azimian ([8]). This paper reports on findings from a survey questionnaire collected from approximately 480 respondents throughout India about their before the pandemic and during the pandemic long-distance travel. In addition to dramatic decreases in the use of public transportation they find habits before the pandemic play a significant role in the after the pandemic changes in travel behavior. [Extracted from the article]

Assesses the Scottish government's document on transportation policy entitled 'Travel Choices for Scotland.' Problems related to increasing car ownership; Objectives of modal integration and sustainability; Growth in the use of motor vehicles; Public transportation improvements; Importance of land-use planning to the transport system.

Shared mobility is transforming the way we move around cities and is challenging consolidated transport modes such as the private car, taxi and public transit. While shared mobility has immense potential to improve the efficiency of personal transport and, hence, reduce emissions, this paper makes the case that shared mobility per se is not sufficient to achieve this important goal. Rather, shared mobility services should be designed and integrated with other transport modes having carbon emission reduction as an explicit optimisation goal. This observation prompts a call for the development of accurate models and analytical tools for the estimation of the city-level benefits of different forms of shared mobility, and of their integration. Examples of these tools are briefly reviewed and discussed in this paper. [ABSTRACT FROM AUTHOR]

Bikeshare, as a convenient transport mode, can address the first- and last-mile travel needs of metro trips while generating many environmental benefits, such as reducing the use of environmentally unfriendly transport modes and lowering the carbon emissions of the urban transportation system. This paper takes bikeshare as a feeder mode of metro stations (BS-FMMS) as the research object and compares the spatial and temporal differences in the carbon emission reduction benefits of BS-FMMS on workdays and non-workdays by using the framework of BS-FMMS carbon reduction benefit analysis and the methods of time-series analysis, spatial aggregation analysis, and box plot analysis. The results show that the carbon emission reduction benefit of bikeshare has obvious morning and evening peaks on workdays, while it tends to be stable without obvious peaks during the day on non-workdays. From the perspective of spatial distribution, the carbon emission reduction benefits of BS-FMMS are more significant in the metro station areas in the south of Baoan district, the west of Nanshan district, the central of Longhua district, and the south of Futian district in Shenzhen city, and the metro stations where the carbon emission reduction benefits of the non-workday are greater than those of the workday are mainly concentrated in Nanshan district, Futian district, and Luohu district. There is a significant positive correlation between BS-FMMS ridership and carbon emission reduction. These findings can provide clear policy implications for the decarbonization development of urban transportation systems. [ABSTRACT FROM AUTHOR]

Multimodal transportation is a modern way of cargo transportation. With the increasing demand for cargo transportation, higher requirements are being placed on multimodal transportation multi-objective routing optimization. In multimodal transportation multi-objective routing optimization, in response to the limitations of classical algorithms in solving large-scale problems with multiple nodes and modes of transport, the limitations of directed transportation networks in the application, and the uncertainty of transport time, this paper proposes an optimization framework based on multi-objective weighted sum Q-learning, combined with the proposed undirected multiple-node network, and characterizes the uncertainty of time with a positively skewed distribution. The undirected multiple-node transportation network can better simulate cargo transportation and characterize transfer information, facilitate the modification of origin and destination, and avoid suboptimal solutions due to the manual setting of wrong route directions. The network is combined with weighted sum Q-learning to solve multimodal transportation multi-objective routing optimization problems faster and better. When modeling the uncertainty of transport time, a positively skewed distribution is used. The three objectives of transport cost, carbon emission cost, and transport time were studied and compared with PSO, GA, AFO, NSGA-II, and MOPSO. The experimental results show that compared with PSO, GA, and AFO using a directed transportation network, the proposed method has a significant improvement in optimization results and running time, and the running time is shortened by 26 times. The proposed method can better solve the boundary of the Pareto front and dominate the partial solutions of NSGA-II and MOPSO. The effect of time uncertainty on the performance of the algorithm is more significant in transport orders with high time weight. With the increase in uncertainty, the reliability of the route decreases. The effectiveness of the proposed method is verified. [ABSTRACT FROM AUTHOR]

The daily trips of urban residents in different transport modes reflect the urban mobility pattern and the latent spatial structure of the city, which is seldom addressed in the literature. A network-based cluster model is applied in this paper based on multimode transit big data. Thus, the urban spatial form can be observed at different levels according to the travel modes and distance, differing from traditional geographic structures. This paper will identify the urban mobility pattern and the corresponding spatial form by taking the Beijing metropolitan area as a study area. Origin–destination data at the traffic analysis zone level were collected, covering shared bike, bus, and metro. The results show that the metro trips reflect the single-center feature of Beijing. However, the multicenter development trend can be revealed by bus and shared-bike data. This paper finds that shared bike supports the establishment of subcenters as a new transport mode. The urban spatial form presents a complex feature of multiple levels and spatial diversity due to the comprehensive effect of multiple travel modes. The study results can provide a basis for the planning of transit network and urban equilibrium land use and development. [ABSTRACT FROM AUTHOR]

Park-and-Ride (P&R), referring to the transfer between private cars and public transportation, is a public policy and travel mode that advocates green travel to reduce traffic congestion in big cities. Through an analysis on the development and focus of P&R research in China and abroad, this paper examines the research progress and explores the research trend on P&R from the perspective of travel mode choice, transfer demand forecast, location planning, operational management, and benefit evaluation. It points out that, compared with the research abroad, the P&R research in China is insufficient on the subjects of transportation planning and benefit evaluation. It proposes that, in future, research should focus more on planning, management, and benefit evaluation of P&R, so as to enhance the intelligent management of transportation system and promote the implementation of policies supporting P&R development. [ABSTRACT FROM AUTHOR]

Cellular signaling data have become increasingly indispensable in analyzing residents' travel characteristic. Especially with the enhancement of positioning quality in 4G-LTE and 5G wireless communication systems, it is expected that the identification accuracy of fine-grained travel modes will achieve an optimal level. However, due to data privacy issues, the empirical evaluation of the performance of different identification methods is not yet sufficient. This paper builds a travel mode identification model that utilizes the gated recurrent unit (GRU) neural network. With 24 features as input, this method can identify four traffic modes, including walking, bicycle, car, and bus. Moreover, in cooperation with the operator, we organized an experiment collecting cellular signaling data, as well as the corresponding GPS data. Using the collected dataset as ground-truth data, the performance of the method presented in this paper and other popular methods is verified and compared. The results indicate that the GRU-based method has a better performance, with a precision, recall, and F score of 90.5%. Taking F score as an example, the outcome of the GRU-based method is about 6% to 7% higher than methods based on other machine learning algorithms. Considering the identification accuracy and model training time comprehensively, the method suggested in this paper outperforms the other three deep learning-based methods, namely, recurrent neural network (RNN), long short-term memory network (LSTM), and bidirectional long short-term memory network (Bi-LSTM). This study may provide some insights for the application and development of cellular signaling-based travel information collection technology for residents in the future. [ABSTRACT FROM AUTHOR]

Real‐time individuals' destination prediction is of great significance for real‐time user tracking, service recommendation and other related applications. Traditional technology mainly used statistical methods based on the travel patterns mined from personal history travel data. However, it is not clear how to predict the destinations of individuals with only limited personal historical data. In this paper, taking the public transportation metro systems as example, we design a practical method called practical model with strong interpretability and predictability to predict each passenger's destination. Our main novelties are two aspects: (1) We propose to predict individuals' destination by combining personal and crowd behavior under certain context. (2) An explanatory model combining discrete choice model and neural network model is proposed to predict individuals' stochastic trip's destination, which can be applied to other transportation analysis scenarios about individuals' choice behavior such as travel mode choice or route choice. We validate our method based on extensive experiments, using smart card data collected by automatic fare collection system and weather data in Shenzhen, China. The experimental results demonstrate that our approach can achieve better performance than other baselines in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

The use of smartphone tracking is seen as the way forward in data collection for travel behavior studies. It overcomes some of the weaknesses of the classical approach (which uses paper trip diaries) in terms of accuracy and user annoyance. This article evaluates if these benefits hold in the practical application of smartphone tracking and compares the findings of a travel behavior survey using smartphone tracking to the findings of a previous paper survey. We compare three phases of the travel behavior study. In the recruitment phase, we expect smartphone tracking to make people more willing to participate in surveys, given the innovative nature and reduced burden to participants. However, we found the recruitment of participants equally challenging as for classical methods. In the data collection phase, however, we observe that participants entering the smartphone tracking survey are much more likely to complete the data collection period than when using paper trip diaries. Because of the limited burden, the risk of drop-out from the survey is significantly lower, making the actual data collection more efficient, even for longer survey periods. Finally, in the data analysis phase, the travel behavior indicators derived from smartphone tracking data result in higher average trip rates, shorter average trip lengths and a higher share of active modes (bike, walking) than the results from the paper survey. Although this is explained by more complete and more consistent trip registration, this finding is problematic for comparability between surveys based on different methods, both for longitudinal monitoring (comparability over consequent surveys) and for benchmarking (comparability over geographical areas). Therefore, it is crucial to clearly report the applied data collection methods when describing or comparing travel indicators. In surveys, a combined approach of both written trip diaries and smartphone tracking is advised, where each method can complement the shortcomings of the other. [ABSTRACT FROM AUTHOR]

Place-based accessibility measures communicate the potential interaction with opportunities at a zone that populations can access. Recent research has explored the implications of how opportunities are counted by different accessibility methods. In conventional measures, opportunities are multiply counted if more than one zone offers access to the same opportunity. This multi-count of opportunities leads to values of accessibility that are difficult to interpret. A possible solution to enhance the meaning-making of accessibility results is by constraining the calculations to match a known quantity. This ensures all zonal values sum up to a predetermined quantity (i.e., the total number of opportunities). In this way, each value can be meaningfully related to this total. A recent effort that implements this solution is spatial availability, a singly-constrained accessibility measure. In this paper, we extend spatial availability for use in the case of multiple modes or more generally, heterogeneous population segments with distinct travel behaviors. After deriving a multimodal version of spatial availability, we proceed to illustrate its features using a synthetic example. We then apply it to an empirical example of low emission zones in Madrid, Spain. We conclude with suggestions for future research and its use in evaluating policy interventions. [ABSTRACT FROM AUTHOR]

Wireless Power Transfer (WPT) technology has been developing rapidly in recent years. Electric Vehicles (EVs), as an emerging mode of transport, also benefit from the WPT technology. Various EV manufacturers have different coupling structures, which can lead to incompatibility problems between the coils. Meanwhile, due to the human parking, misalignment between the transmitting and receiving coils may occur. To solve these problems, this paper proposes a reconfigurable bipolar coil structure with both interoperability and misalignment tolerance. A 200-W experimental prototype is built, which can achieve 84.33% and 84.76% system transmission efficiency with vertical and horizontal bipolar coils. The effectiveness of the proposed reconfigurable bipolar coil is finally verified by comparing the computational and experimental results. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines what facilitates the swift reconfiguration of freight movements across transport modes in the wake of a major disaster. Design/methodology/approach: A qualitative research approach focussing on the New Zealand (NZ) domestic freight transport operations in the wake of the 2016 Kaikōura earthquake is used with data collected through 19 interviews with 27 informants. The interviews are thematically analysed by using the framework method. Findings: The paper provides rich and detailed descriptions of the ability of a freight transport system to recover from a disaster through rapid modal shifts. This paper identifies nine factors enabling modular transport operations and highlights the critical role of physical, digital, operational and inter-organisational interconnectivity in the aftermath of a disaster. Originality/value: Although the management of freight disruptions has become a prevalent topic not only in industry and policy-making circles, but also in the academic literature, qualitative research focussing on the ability of commercial freight systems to adapt and recover from a disaster through rapid modal shifts is limited. This qualitative study sheds light on the mechanisms underlying the continuity of freight operations in the wake of a disaster and provides a comprehensive understanding of modular transport operations and the ability of freight systems to keep goods moving. [ABSTRACT FROM AUTHOR]

This paper evaluates a congestion management concept involving conversion of two existing general-purpose freeway lanes per direction on an 8-lane freeway (with 4 lanes per direction) to priced lanes offering free access for high-occupancy vehicles, in conjunction with cash payments to incentivize a sufficient number of commuters to travel as passengers in transit, carpools or vanpools such that congestion on the remaining free lanes would be no worse than it was before the conversion. Building on prior research, we use a refined modeling process to explore the viability of implementation of the concept on the eastern segment of the Capital Beltway in the Washington, DC metro area. The results of the analysis suggest that the strategy can benefit users of shared travel modes and toll-payers, improve travel speeds on toll-free general-purpose lanes, generate significant surplus revenues to support capital investments and operating subsidies for shared travel modes, and can absorb traffic growth through 2040. [ABSTRACT FROM AUTHOR]

Ambient data is generated from a collective of smart devices, connected environments and pervasive platforms, so well-integrated and finely tuned that we no longer think about connecting, syncing, or controlling. Pers Ubiquit Comput. https://doi.org/10.1007/s00779-020-01371-w 7 Ahmed A, Outay F, Zaidi SOR, Adnan M, Ngoduy D (2020) Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data. Pers Ubiquit Comput. https://doi.org/10.1007/s00779-019-01333-x 3 Beg A, Qureshi AR, Sheltami T, Yasar A (2020) UAV-enabled intelligent traffic policing and emergency response handling system for the smart city. [Extracted from the article]

Staying within the 2 °C (preferably 1.5 °C) limit requires fast and fundamental system changes, also in urban passenger transport. Shifting car traffic to environmentally friendly transport modes is one central strategy to make urban transport more sustainable and climate friendly. However, in most cities car use remains high. Therefore, this paper analyzes what course change is needed regarding direction, scale and speed of change for urban sustainability and climate protection reasons. The paper analyzes the role of modal shift as a strategy in itself and in relation to land-use (avoid) and efficiency (improve) measures. The paper draws on insights from European frontrunning cities and explorative forecasting scenarios calculated with the sophisticated integrated land-use transport model "Ruhr Region 2050". The paper suggests that a significant reduction of urban car use is needed (direction) that roughly equals a fast halving of car use (scale), which has proven feasible under the current socio-political conditions by annual reduction rates of 0.5 to 1.5 percentage points of the trip-based modal share of car use (speed). Significantly reducing car use requires comprehensive and high-intensive measures that go far beyond usual practices. Modal shift measures need to play a crucial role in integrated approaches with land-use (avoid) and efficiency (improve) measures because they have the potential to significantly reduce car use and CO2 emissions and because they can produce comparatively fast effects – which makes modal shift measures first aid approaches to achieve a fast "bending of the curve" of excessive car use and growing CO2 emissions. [ABSTRACT FROM AUTHOR]

This paper shows how the methodologies used in current practice might lead to an underestimation of energy consumption by different passenger transport modes, and also offers recommendations for improvements to these methodologies. The first recommendation is related to energy consumption rates. The studies reviewed use traditional energy consumption rates based on transportation demand, such as kilowatts-hour per vehicle-kilometre or kilowatts-hour per passenger-kilometre, and include other rates based on transportation supply which might prove useful. Second, energy consumption rates are dependent on factors, and the introduction of homogeneous units which are independent of these factors therefore offers a significant improvement when comparing transport modes. Third, the use of a vehicle energy consumption equation will improve the quality of the assessments. Fourth, we propose that the coefficients which define the energy consumption equation should be broken down to determine market niches and sources for improvements in energy consumption in the vehicle categories. [ABSTRACT FROM AUTHOR]

The modern urban transportation service network could be split into unrestricted and restricted networks depending on whether travelers face limitations in route selection. Along with the continuous expansion of the city, it is difficult for travelers to find a more reasonable travel solution when confronted with such a complex transportation service network, which combines both unrestricted and restricted networks, especially for the park-and-ride (P&R) travel mode. This paper addresses the issue of route analysis in modern urban transportation service systems to provide travelers with reasonable travel solutions based on multiple types of transportation services. An improved A* algorithm is proposed to address the optimal path analysis for restricted networks to provide reasonable travel solutions for public transportation trips. Furthermore, by establishing the topological relationship between restricted and unrestricted networks, this paper presented an improved A* algorithm based on hybrid networks that solves the optimal path analysis problem for P&R trips, bringing convenience to many urban travelers. [ABSTRACT FROM AUTHOR]

This research paper analyzes urban travel mode preference in Addis Ababa using a survey distributed to 457 public transit users. The article highlights the details of individual travel and then discusses the implications of the travel patterns for transport policy in the city. The study employed percentages and run multinomial logistic regression to analyze the relationship between mode choice, travel characteristics and socio-economic features of individuals. In terms of mode choice and the influential factors, the analysis shows that income, age, travel expenditure and distance are the determining factors that affect mode choice. It was also found that the privately owned public transport, Taxi (mini-bus) and Higer (midi-bus) form the dominant mode of transport used by closely half percent (41.3%) of the survey respondents. On the basis of our analysis, we suggest that policies have to be devised to make government owned public transport service better in order to support a shift from using low occupancy vehicles to high occupancy vehicles which ultimately solve the problem of congestion and environmental pollution. [ABSTRACT FROM AUTHOR]

Demand-responsive feeder transit (DRFT) is an emerging urban public transport mode with the advantage of offering flexible door-to-door services in the high-speed railway hub area. However, the existing bus scheduling schemes can hardly meet personalized and diversified passenger transfer demands in the station-city integrated high-speed railway hub, reducing the attractiveness of DRFT. This paper studies the DRFT scheduling problem considering static and dynamic travel demands under the background of mobility as a service (MaaS). An information-based DRFT system framework is proposed, where the K-means clustering algorithm is implemented to select target bus stops from regional road networks for passengers to get on and off. A two-stage mixed integer programming model is first formulated to generate operational routes and optimize the static and dynamic scheduling before and after departure. The objective functions reflect the operating benefits of public transport enterprises and the travel costs of passengers, and the demand characteristics in different driving directions are taken into account in the model. Then, an improved genetic algorithm is developed to solve the model, which is called the genetic algorithm-exact algorithm (GA-EA) in this paper. Finally, the proposed model and algorithm are evaluated using the case study of the Nanjingnan Railway Station area. The experiment results show that the optimal scheme can provide a 100% demand-response rate, reasonable service time, and valid driving routes. In addition, compared with GA, the average search time of GA-EA is shortened by 43.5% and the total objective function value is increased by 2.16%. The findings in this paper can provide practical guidance on DRFT scheduling and improve the efficiency of bus feeder service. [ABSTRACT FROM AUTHOR]

Mobility-as-a-Service (MaaS) system is regarded as one of the emerging solutions to offer integrated, seamless, and flexible multi-modal mobility services as an alternative to privately owned mobility resources. MaaS is expected to change the way users will choose their modes of transport to reach their daily activities, and how service providers will generate profits, cooperate, and compete. To successfully deploy MaaS to reach the intended goals, it is critical to develop feasible and sustainable models that capture the diverse needs of customers as well as the diverse and often competing objectives of service providers. This paper aims to provide a general modelling framework and a critical and descriptive analysis of the relevant literature relating all main actors in the MaaS ecosystem, and identify and discuss all factors that are considered relevant, focusing on the actor's decision-making processes and their correlations. This review shows the large variety and interaction of factors influencing MaaS adoption and their impact on forecasting MaaS appeal. It is also observed that current travel behaviour and multi-modal transport models are not fully capturing the diverse travel needs and choices of potential MaaS users. Recent advancements in agent-based simulation and discrete choice modelling offer potential solutions to address this gap, and future research should aim in that direction. Finally, the review analyses the interaction between MaaS actors, including customers, service providers, the government, and the MaaS Broker, highlighting the complexity of the modelling process comprising all actors of the MaaS ecosystem. Therefore, it is recommended to prioritise future research in exploring these areas. [ABSTRACT FROM AUTHOR]

The current paper is based on data collected within the framework of the Inter-Connect PLUS project, with a focus on incorporating new norms before, during, and after the COVID-19 pandemic. A questionnaire was conducted in four countries of the Adriatic-Ionian (ADRION) Region: Italy, Slovenia, Croatia, and Albania. The collected data from the survey was analyzed to draw conclusions about the travel modes citizens used before, during, and are willing to use after the pandemic. The paper closes with recommendations, in the form of a Roadmap, highlighting the potential positive impact of the pandemic on the future of sustainable mobility. [ABSTRACT FROM AUTHOR]

The article discusses the origin, destination and mode of travel in urban areas reflecting that development of a trade area is independent of distance traveled by people. It informs that 40 percent trips have home as their destination or origin whereas remaining trips ends in a non-residential area. It reveals that trips may be made by suitable mode of conveyance such as car, auto-riksha and buses.

This paper evaluates various modes of transport against the dual requirements of Net‐Zero carbon emissions and user convenience, in particular, speed of travel and cost of transportation. Results show that when operated across a whole country, battery‐powered ePlanes have the lowest energy use as measured by well‐to‐wing efficiency of other high‐speed transport systems such as the UKs HS2 and conventional diesel rail systems. This condition may not hold for extremely high passenger numbers per hour as seen in metropolitan areas with high density populations. Various proposed disruptive technologies lower cost of ownership when combined with changes in the transport paradigm that has rarely been explored in other papers. [ABSTRACT FROM AUTHOR]

Existing research rarely examines the subjective and objective built environment of river valley-type cities in relation to travel mode choice, particularly overlooking the heterogeneity among travelers in these cities. In this paper, based on questionnaire survey data and built environment data, terrain spatial perception (TSP) is introduced to expand the theory of planned behavior (TPB), and a Structural Equation Model (SEM) is established. Factor analysis and path analysis are conducted using SPSS and AMOS to estimate latent variables. An integrated model of SEM and random parameter Logit model (RPLM), which can not only analyze the psychological perception factors of commuters in river valley-type cities but also consider the heterogeneity of psychological perception, was constructed to analyze the impact of personal attributes, objective built environment factors, and psychological latent variables on the commuting mode choice behavior of public transport users in river valley-type cities. The results indicate that the five observation indicators corresponding to the proposed terrain spatial perception latent variables can better explain the terrain spatial perception of commuters in river valley-type cities. Different from plain cities, the subjective and objective built environment of river valley-type cities notably influence the travel behavior of commuters. Moreover, the parameters of terrain spatial perception follow a normal distribution, indicating that the sensitivity of different commuters to the terrain spatial perception of river valley-type cities is heterogeneous. The results of our study can provide a reference for alleviating traffic issues in valley cities. [ABSTRACT FROM AUTHOR]

With the continuous development of large-scale engineering projects such as construction projects, relief support, and large-scale relocation in various countries, engineering logistics has attracted much attention. This paper addresses a multimodal material route planning problem (MMRPP), which considers the transportation of engineering material from suppliers to the work zones using multiple transport modes. Due to the overall relevance and technical complexity of engineering logistics, we introduce the key processes at work zones to generate a transport solution, which is more realistic for various real-life applications. We propose a multi-objective multimodal transport route planning model that minimizes the total transport cost and the total transport time. The model by using the ε − constraint method that transforms the objective function of minimizing total transportation cost into a constraint, resulting in obtaining pareto optimal solutions. This method makes up for the lack of existing research on the combination of both engineering logistics and multimodal transportation, after which the feasibility of the model and algorithm is verified by examples. The results show that the model solution with the introduction of the key processes at work zones produces more time-efficient and less time-consuming route planning results, and that the results obtained using the ε − constraint method are more reliable than the traditional methods for solving multi-objective planning problems and are more in line with the decision maker's needs. [ABSTRACT FROM AUTHOR]

Recently, new travel options such as micromobility and shared transport systems have been introduced in many urban areas in Spain, which are intended to increase the sustainability and accessibility of cities. The Covid-19 pandemic has boosted the use of these new individual travel modes. The aim of this paper is to analyze travel behavior and wellbeing of users of these new urban solutions compared to traditional transport. Face-to-face and online surveys were carried out during the Summer of 2021 in Valencia (Spain) to collect information regarding travel behavior and wellbeing. Participants were habitual users of all urban travel modes, including those who also used motosharing, carsharing or private e-scooters. 2225 valid responses were obtained after data cleaning and validation. Satisfaction with Travel Scale (STS) is used to explore subjective wellbeing of users of new and traditional transport modes. Results show that current users of motosharing and private e-scooters were former users of public transport, while users of carsharing used to utilize more car and motosharing before. On the other hand, active transport is associated with higher satisfaction compared to new urban modes, while they provide more satisfaction than urban public transport. [ABSTRACT FROM AUTHOR]

While high-speed rail networks involve significant public expenditure in the name of the whole nation, scholars have paid little attention to the share of the population served by this modern transport mode. Studies have favoured perspectives that either neglect population volumes or include them but cannot offer a worldwide assessment. Public authorities favour passionate statements about network length and cruising speed but at the same time they neglect the populations served. In contrast, this paper offers a worldwide comparison of populations served by high-speed rail services in 15 countries. We found the range is wide (7%−94%) and depends on several factors beyond network length, including network design, urbanisation patterns, technical characteristics and domestic vs. international purposes. [ABSTRACT FROM AUTHOR]

Promoting the shift from private cars to micromobility (e.g., bike, e-bike, scooter) can represent a valuable action to improve city sustainability and liveability. Micromobility can help to replace trips by individual private cars (e.g., daily short round trips) as well as to improve coverage and accessibility of transit services, and, subsequently, to reduce the traffic impacts (e.g., pollutant emissions). It can be seen as a potential solution to move people more efficiently in urban areas, as well as to push people towards a more active mobility behaviour, contributing to the well-being goals. In this context, the paper, rather than inferring the users' propensity to change their travel mode, proposes a methodology to identify car trips that can be considered the most compatible with micromobility. Estimation of the potential demand (e.g., the upper level of car trips that could be replaced by micromobility) is carried out by exploiting the opportunity offered by floating car data (FCD) for characterising car trips. Its goodness is therefore evaluated through an application to a real case study (i.e., the city of Trani, Apulia Region, Southern Italy), divided into seventy traffic zones, and where a FCD dataset of about 5,200 trips was available. The FCD allowed the car trips to be characterised (e.g., origin and destination, path features) instead of using the traditional surveys. The results indicate that a significant share of daily car trips can be substituted (i.e., the most compatible) by micromobility (31% of car round trips in the case study), with considerable potential environmental gains (traffic emission reduction; less than 21% of total emissions from private cars). Results can be of interest to local authorities in integrating micromobility in urban mobility planning and promoting new sustainable transport alternatives, as well as to transport companies for designing new appeal services. The developed methodology is parametric and uses easy-to-obtain data available worldwide; thus, it can be easily transferred to other city contexts. [ABSTRACT FROM AUTHOR]

• This paper reviews factors influencing shift to public transport. • The focus is on developing countries. • The findings highlight a modal shift from motorcycles to public transport. • The findings highlight a theoretical framework for the modal shift. Most studies on commuter and public transport mode choice rely on theoretical frameworks that draw boundaries between the utility function, social-ecological system, demographic and socio-economic attributes, and psychological theory. While models predicting the shift towards public transport are commonly applied in developed countries, there is a lack of similar studies that construct these models in developing countries. In addition, in some developing countries, the motorcycle is one of the main private motorised travel modes. Therefore, the modal shift from motorcycles to public transport in Southeast Asia to reduce private mobility is one of the important topics to examine. This paper presents a systematic literature review, utilising a comprehensive search strategy across electronic databases and reputable sources to identify directed acyclic graphs (DAGs), revealing factors influencing the choice and intention to shift to public transport. Data synthesis from selected studies highlights the intrinsic and extrinsic variables influencing public transport use, motorcycle use, and the modal shift to public transport. The study also proposes a theoretical framework for the modal shift in usage from motorcycles to public transport. [ABSTRACT FROM AUTHOR]

Optimization transportation cargo and passengers between ports and regions are very important, because industrial regions are located some distance from ports. The demand for energy request for the movement of transport is a necessity in the modern world. Transport and activity called transportation are used daily, everywhere, and a lot of energy is needed to power the various transport modes. Today different transport modes are being used to transport passengers and cargo. It is quite common to use road transport, which can transport passengers and cargo from door to door. Considering alternative possibilities (road, railway and/or inland waterway transport), it is important, based on theoretical and experimentation, to identify optimal solutions. In finding transport modes that are either most technically or economically effective, we could unearth possible solutions which would require minimal energy use. Unfortunately, with increased transportation, this often leads to traffic congestion on the roads, which requires additional energy (fuel). This situation generates requirements from many stakeholders in terms of finding ways to decrease the transportation time and energy (fuel) consumed by transport modes. A theoretical method evaluation is conducted on the optimal transportation possibility that minimizes transportation time and energy (fuel) use by employing graph theory, which is presented in this paper. The scientific contribution is the development of a transport modes comparative index, which is then used for evaluations. This paper presents possible alternative transportation conditions based on a multi-criteria evaluation system, proposes a theoretical basis for the optimal solutions from an eco-economic perspective that considers energy, and provides for experimental testing during a specific case study. The final results from the case study provide recommendations and conclusions. [ABSTRACT FROM AUTHOR]

The attractiveness of public transport is not high and therefore it is obvious that private transport is the preferred mode of transport. The interest in public transport has declined even more since the outbreak of the COVID-19 pandemic, during which passengers feared the rapid spread of the disease in public vehicles. As a result, the habit of traveling individually has increased. This paper highlights the massive increase in private transport in the V4 Countries by the use of private vehicles and the related decrease in use of public transport. It also presents some of the relevant tools of the Smart City concept that could improve the use of public transport in cities. This paper is aimed at highlighting the current use of public bus transport (including public transport) in the V4 countries vis-a-vis the ongoing COVID-19 pandemic and highlighting the information and communication technology (ICT) - related means of incentivization. [ABSTRACT FROM AUTHOR]

Aim: Active transportation referring to non-motorized modes of transport is promoted and popularized both in practice and in the scientific literature, while their use for urban freight transport has been largely neglected. Thus the main scope of the paper is to indicate the development potential of micromobility use in urban freight transport and to check its influence on urban sustainability. Methods: The authors have hypothesized that active means of transport, with a focus on micromobility, have great development potential in freight transportation in cities. The implemented methods for analyzing the relationship between users' characteristics, micromobility, and its impact on urban sustainable development, were logit and probit modelling. The authors' system includes an analysis of factors connected with the topics of sustainability and micromobilty, that have met an essential scientific gap that this paper addresses. Logistic (logit) regression is used mainly for binary, ordinal, and multi-level outcomes to find the probability of success (i.e. occurrence of some event). Probit regression, however, is primarily used in binary response models and assumes the normal distribution of data. Results: The main finding of the article has led the authors to the statement that active means of transport, including micromobility have great development potential in freight transportation in cities. Conclusions: Knowledge of the acceptance of micromobility solutions is essential for municipal authorities in shaping the development of urban transport systems. Thus proper strategies and actions need to be prioritized to leverage the sustainability-related co-benefits of active transport. [ABSTRACT FROM AUTHOR]

After entering the 21st century, China's national economy has shown a rapid growth momentum, the comprehensive transportation system has been continuously improved, the road traffic infrastructure has made remarkable achievements, and the modern logistics industry has also risen rapidly and grown rapidly, which has greatly changed the market demand for road transport hubs. The road transport hub is the main node of the road transport network, the hub of passenger and freight distribution of road transport, and the organizational center for the interconnection of road transport and other transport modes and the development of comprehensive transport. Highway transportation hub is an important part of highway transportation infrastructure and plays an important role in highway transportation. The planning scheme evaluation of highway transportation hub is a multi-attribute decision making (MADM). This paper intends to propose a MADM methodology based on cross-entropy (CE) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for planning scheme evaluation of highway transportation hub. First of all, this paper extends the cross entropy method under the IVIFSs to propose the interval-valued intuitionistic fuzzy number CE(IVIFN-CE) method, it enlarges the application range of the CE method. Secondly, a new MADM model for planning scheme evaluation of highway transportation hub based on IVIFN-CE algorithm is proposed. [ABSTRACT FROM AUTHOR]

A range of studies have found that immigrants generally start out using different travel modes but over time they 'assimilate' toward adopting similar travel modes to the general population. These studies tend to focus on 'when' and 'if' travel assimilation occurs, with some studies using socioeconomic factors to explain 'why' this occurs. But few studies have explored the role of culture, attitudes and other 'soft' factors in shaping the process of travel assimilation among immigrants. In Australia, South Asians have been the largest and fastest growing immigrant group, and as skilled migrants they face few 'hard' barriers to car use. The aim of this paper is to explore the interaction between cultural influences, attitudes and initial travel experiences upon arrival in Australia on long-term travel assimilation amongst South Asian immigrants. Qualitative interviews with 20 South Asian immigrants were used to identify a range of cultural and psychosocial factors, such as perceptions towards travel modes and gender-based cultural norms. Attitudes and behaviours evolve during their early years in Australia, beginning with a 'honeymoon period' – a phase where all travel modes are seen as positive – before car use begins to dominate. The findings have implications for how we understand the interactions between attitudes, cultural practice and travel behaviour and how they evolve over time. They also imply that policymakers have only a narrow window of time to encourage sustainable transport among South Asian immigrants before the travel 'honeymoon period' wears off. [ABSTRACT FROM AUTHOR]

The inauguration of high-speed rail (HSR) services is often associated with renewed expectations of revitalization of local tourism activity in sparsely populated regions. However, the empirical literature on the actual ex-post effects of this transport mode is scarce. This paper contributes to this line of research by estimating the causal impact of the HSR on the number of visitors in three small cities located in low-density areas in Spain. Our results, using the synthetic control method, robustly show that the ex-post causal effects of the HSR on overnight visitors are insignificant and, if any, they seem to exert a negative influence rather than a positive contribution. This suggests that smaller cities should be very cautious about the short-run expected impacts of transport improvements, and policy makers and planners should be aware of the actual contribution of such investments in their assessment of the net social benefits of HSR projects. [ABSTRACT FROM AUTHOR]

Aiming at the problem of multimodal transport path planning under uncertain environments, this paper establishes a multi-objective fuzzy nonlinear programming model considering mixed-time window constraints by taking cost, time, and carbon emission as optimization objectives. To solve the model, the model is de-fuzzified by the fuzzy expectation value method and fuzzy chance-constrained planning method. Combining the game theory method with the weighted sum method, a cooperative game theory-based multi-objective optimization method is proposed. Finally, the effectiveness of the algorithm is verified in a real intermodal network. The experimental results show that the proposed method can effectively improve the performance of the weighted sum method and obtain the optimal multimodal transport path that satisfies the time window requirement, and the path optimization results are better than MOPSO and NSGA-II, effectively reducing transportation costs and carbon emissions. Meanwhile, the influence of uncertainty factors on the multimodal transport route planning results is analyzed. The results show that the uncertain factors will significantly increase the transportation cost and carbon emissions and affect the choice of route and transportation mode. Considering uncertainty factors can increase the reliability of route planning results and provide a more robust and effective solution for multimodal transportation. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) have been made possible by advances in sensing and computing technologies. However, the high cost of AVs makes privatization take longer. Therefore, companies with autonomous vehicles can develop shared autonomous vehicle (SAV) projects. AVs with a high level of automation require high upgrade and use costs. In order to meet the needs of more customers and reduce the investment cost of the company, SAVs with different levels of automation may coexist for a long time. Faced with multiple travel modes (autonomous cars with different levels of automation, private cars, and buses), travelers' travel mode choices are worth studying. To further differentiate the types of travelers, this paper defines high-income travelers and low-income travelers. The difference between these two types of travelers is whether they have a private car. The differences in time value and willingness to pay of the two types of travelers are considered. Based on the above considerations, this paper establishes a multi-modal selection model with the goal of maximizing the total utility of all travelers and uses the imperial competition algorithm to solve it. The results show that low-income travelers are more likely to choose buses and autonomous vehicles with lower levels of automation, while high-income travelers tend to choose higher levels of automation due to their high value of travel time. [ABSTRACT FROM AUTHOR]

Until recently, laboratory testing of packaged systems has been undertaken by simulating vertical vibrations alone. However, with increasing demand for a reduction in packaging waste, the use lightweight systems, such as stretch film, is increasing. Such containment systems are susceptible to the lateral forces generated by the pitch and roll vibratory motion of vehicles due to road surface unevenness. If laboratory simulation is to be realistic, multi‐axial motion must be taken into account and an understanding of the relationships between the random heave, pitch, and roll vibrations is essential. This paper uses vibration data collected from a number of transport vehicles traveling along typical urban and suburban routes to establish the nature and level of the multi‐axial vibrations that exist. These are presented with average Power Density Spectra (PDS) as well as statistical distributions of the moving root‐mean‐square (rms). The paper analyses the data for correlation of the rms levels with respect to nonstationarity. This is important when simulating nonstationary (randomly fluctuating rms) vibrations for heave, pitch and roll. These statistical correlation functions are used to manage the relative rms levels of each of the three Degrees of Freedom (DoFs) when undertaking vibration simulations using multi‐axis vibration test systems. The results show that the relationships between the moving rms of heave, pitch and roll vibrations are not strongly correlated but can be characterized statistically as joint distributions to enable realistic simulation of multi‐axial random vibrations of road transport vehicles under controlled laboratory conditions. [ABSTRACT FROM AUTHOR]

Summary: Gamification is a new theme that has been applied in different fields and has contributed to different types of behavioural change. This paper aims to describe how gamification is adopted in the context of transportation. Methods: We performed a systematic mapping of the scientific literature of Web of Science and retrieved 211 studies. After the inclusion and exclusion criteria were applied, 66 studies were selected. After the full texts were read, 30 studies remained to be analysed. Findings: The results show that the most commonly used gamification elements are goals/challenges and points. Gamification provides support for outcomes such as changing travel behaviour, improving driving behaviour and encouraging bicycle commuting. The use of gamification has changed the behavior of travelers, promoted sustainable travel modes, encouraged safe driving, reduced carbon dioxide emissions and reduced energy consumption. Although gamification has achieved many positive results related to transportation, there are still many difficulties and challenges. [ABSTRACT FROM AUTHOR]

With the increase in global car ownership, the demand for traffic safety is very strong. Research shows that drivers account for more than 90% of global traffic accidents. Driverless cars can reduce traffic accidents caused for these reasons and greatly improve traffic safety. At the same time, driverless real-time path planning can select the best driving route for vehicles, reduce traffic congestion, and improve the efficiency of transportation. To sum up, driverless vehicles are considered an important solution to ensure traffic safety, improve traffic efficiency, reduce energy consumption and pollution, and change travel mode. An intelligent driverless vehicle is a key component of the intelligent transportation system, which organically combines various functions such as. Among them, path tracking and motion control play a very important role in intelligent driverless technology. At the same time, accurately tracking the desired feasible path and stable motion control are the basis of intelligent unmanned driving. Based on this, this paper uses artificial intelligence technology to study the path control and behavior decision-making of intelligent driverless trucks, and an improved tracking control method is proposed. Through this improved method, the intelligent unmanned vehicle can track the desired feasible path under different curvatures more accurately and stably. Finally, through the road test experiment of the intelligent unmanned vehicle experimental platform in the actual environment, the effectiveness of the scheme design and related algorithms of intelligent unmanned vehicle motion control in this paper is verified. [ABSTRACT FROM AUTHOR]

Metros constitute an important form of public transport in large cities throughout the world. Because metro transport encompasses long distances and large areas, many metro passengers must transfer to other transport modes to complete their journeys. This paper will review the recent literature on metro-related transfers and will summarize and discuss the key findings and issues regarding transfers between metros and other transport modes. A considerable number of studies in different countries have explored transfer behavior, the influencing factors that are related to metro-related transfers, and travelers' perceptions of and satisfaction with these transfers. The paper will discuss the characteristics of travel behavior that is associated with metro-related transfers and could provide important implications to improve travelers' perceptions of and satisfaction with these transfers. In addition, it will offer recommendations on aspects of the built environment that could facilitate transfers between metros and other travel modes. The paper could provide policy guidance for the integration of public transit and active and private transport and could be valuable in directing future research in this field. [ABSTRACT FROM AUTHOR]

The article offers information on the modification of the U.S. Environmental Protection Agency (EPA) regional emission model known as SMOKE for Europe (SMOKE-EU). It mentions that SMOKE-EU is capable of producing Community Multiscale Air Quality (CMAQ) ready emissions not only in Europe but also in Western Russia, Turkey and North Africa. The purpose of the modification is to develop a flexible model capable of producing high resolution emission data for Chemical Transport Models (CTM).

This article, titled "Editorial," is from the Transactions on Transport Sciences journal. The focus of this issue is on modes of transportation that are not related to private cars, such as walking, cycling, public transport, and micro-mobility. The topics discussed include mode choice, user satisfaction, attitudes towards new modes like e-scooters, and the effectiveness of measures to shape mode choice. The articles highlight the need for policies prioritizing public transport infrastructure, improving preconditions for sustainable travel, and addressing customer satisfaction with existing transportation options. The papers also emphasize the importance of influencing mode choice through evidence-based measures and the willingness of policymakers to support investments in transportation improvements. [Extracted from the article]