Search

The global COVID-19 pandemic had an unprecedented impact on transportation worldwide. Significant decreases in transportation across all modes were evident and sustained as governments worldwide implemented various countrywide closures and quarantine restrictions to slow the spread of the virus. This paper quantifies and assesses daily vehicle counts by Federal Highway Administration (FHWA) vehicle classifications during the COVID-19 pandemic in New York and Florida throughout 2020. The study found that duringMarch and April of 2020, traffic among all investigated FHWA categories was significantly reduced in both Florida and New York. However, commodity carriers in both states were able to recover faster and remained more consistent than passenger vehicles. This pattern was also observed in both urban and rural communities in Florida. The findings of this work demonstrate how commodity carrier movements, assessed through FHWA vehicle category counts, were less impacted by the governmental restrictions during the pandemic than passenger transportation. While overall traffic volume dropped by more than half in most places at the height of the pandemic, larger commodity-carrying vehicles remained nearly unchanged from the prior year by June of 2020. This was likely because of the critical need to maintain trucking movements to sustain populations. Understanding how truck traffic and freight movements more broadly were impacted during the COVID-19 pandemic is critical in preserving the continuity of service and preventing supply shortages in the event of future outbreaks. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

Abnormal-trajectory detection can be used to detect fraudulent behavior of taxi drivers transporting passengers. Aiming at the problem that existing methods do not fully consider abnormal fragments of trajectories, this paper proposes an abnormal-trajectory detection method based on sub-trajectory classification and outlier-factor acquisition, which effectively detects abnormal sub-trajectories and further detects abnormal trajectories. First, each trajectory is reconstructed using the turning angles and is divided into multiple sub-trajectories according to the turning angle threshold and trajectory point original acceleration. The sub-trajectories are then classified according to the extracted directional features. Finally, the multivariate distances between angular adjacent segments are calculated to obtain the outlier factor, and abnormal sub-trajectories are detected. The sum of the lengths of the abnormal sub-trajectories is used to calculate the outlier score and identify abnormal trajectories. Based on experimental results using real trajectory datasets, it has been found that the proposed method performs better at detecting abnormal trajectories than other similar methods. [ABSTRACT FROM AUTHOR]

Ridesharing effectively tackles urban mobility challenges by providing a service comparable to private vehicles while minimising resource usage. Our research primarily concentrates on dynamic ridesharing, which conventionally involves connecting drivers with passengers in need of transportation. The process of one-to-one matching presents a complex challenge, particularly when addressing it on a large scale, as the substantial number of potential matches make the attainment of a global optimum a challenging endeavour. This paper aims to address the absence of an optimal approach for dynamic ridesharing by refraining from the conventional heuristic-based methods commonly used to achieve timely solutions in large-scale ride-matching. Instead, we propose a novel approach that provides snapshot-optimal solutions for various forms of one-to-one matching while ensuring they are generated within an acceptable timeframe for service providers. Additionally, we introduce and solve a new variant in which the system itself provides the vehicles. The efficacy of our methodology is substantiated through experiments carried out with real-world data extracted from the openly available New York City taxicab dataset. [ABSTRACT FROM AUTHOR]

Urban rail transit stations are crucial components of the urban rail transit network as they connect lines in the network structure and facilitate the collection and distribution of passenger flow during network operations. Effectively identifying critical stations that play a vital role in maintaining network structure stability and passenger flow transportation can help reduce operational risks and improve operational service levels. In this study, we propose a new perspective for assessing the importance of stations in the rail transit network and identifying critical stations by considering the characteristics of network structure and passenger flow. We apply the theory of multi-layer complex networks and treat the urban rail network as a multi-layer network consisting of facility layer, service layer, and passenger flow layer. By analyzing the attributes of each layer, we construct node importance indicators for each layer of the network. We integrate the facility and service layers based on their similar attributes to derive a node importance indicator for the facility-service layer, which can be used to identify critical stations in unweighted topology networks. Additionally, we fuse the attributes of the passenger flow layer using linear fusion to construct a node importance indicator for the multilayer network (NIMN). To assess the effectiveness of the node importance indicators in each layer and the NIMN indicator, we evaluate critical stations using indicators such as the largest connected percentage, network efficiency, and weighted network efficiency. Simulation results using Suzhou Rail Transit as an example demonstrate that the proposed method can effectively identify critical stations in both unweighted topology networks and multi-layer networks of urban rail transit. [ABSTRACT FROM AUTHOR]

[Display omitted] • The pandemic increased passengers' concerns of using public transportation. • An intervention addressing belief change by visualizing ventilation was evaluated. • The intervention had no effect on passengers' risk perception or well-being. • Main predictors of risk perception: general pandemic risk perception and crowding. • Main predictors of subjective well-being: comfort, salient fresh air, mask wearing. This study evaluated the effectiveness of a communicative intervention in addressing passengers' increased risk perception of getting infected with COVID-19 in public buses and thereby improving travel-related well-being after the pandemic. A pre-registered quasi-experimental field-study (N = 306) was conducted in two public bus line bundles. The intervention consisted of visualizing the fresh air supply in the bus via tinsel garlands. The intervention successfully increased passengers' awareness of fresh air supply in the bus (in the intervention group as compared to the control group; d = 0.25). However, this awareness did neither reduce passengers' risk perception, nor did it increase their subjective well-being in the bus. An explorative analysis identified crowding, and general COVID-19 risk perception as major predictors of risk perception on-board. The study revealed first-hand, real-time insights in bus passengers' risk perception, travel well-being and their major predictors during the out fading COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has caused unprecedented disruptions to public transportation services, passengers' mode choice preferences, and their behavioral pattern. Recent studies have updated the systemic shift from shared travel to private mode due to the perceived higher health risk of shared mobility. However, findings from these studies may not be applicable to public transport-oriented cities with very low rate of private car ownership. In the long term when we arrive at a stabilized 'New Normal', the need to promote public transport is likely to be re-emphasized with high priority. This study presents insights into the factors affecting public transport (PT) preferences and potential modal shifts within various modes of PT when proactive and reactive health control measures are implemented. An online stated preference survey was conducted in Hong Kong, where public buses, public light buses, MTR, and taxis are the popular modes of public transport. The regret-based panel mixed multinomial logit model was applied in this study, aiming to capture individual's regret aversion psychology in the context of the COVID-19 pandemic. The results of our random regret model suggest that travelers generally have lower regrets for the chosen mode when having passenger temperature screening, COVID tracing app, and more frequent disinfection, while seem to be unaware of the in-vehicle air quality. Interaction effects between health control measures and personal characteristics (e.g., age and risk attitudes) were also considered. Trip characteristics, including in-vehicle crowding level, fares, in-vehicle travel time, waiting time at a station, walking time, and trip purpose, were found to influence passengers' choices of travel modes. Policy simulations of possible changes in public transport modal preferences in the presence of various health control measures have also been undertaken. The findings suggest that overall health control measures are appreciated by passengers and do align with promotion of a return to public transport use. However, their effects are quite moderate and should be selectively used for different transport modes. Increasing service frequency can be a promising solution, which reduces crowding and waiting time of passengers using public transport modes, and reduces virus transmission risk. This study contributes to a better understanding of public acceptance and preference toward health control measures in public transport, and call for in-depth cost-benefit analysis in the related fields so that better response can be made in possible future public health crisis. • This study focusses on the public transport-oriented city. • Effects of proactive and reactive health control measures implemented for public transport are evaluated. • Travel modes of public buses, public light buses, MTR train, and taxis are considered. • Mixed random regret model with interaction effects is applied to capture individual's regret aversion psychology in the context of the COVID-19 pandemic. • Influences of trip characteristics, including in-vehicle crowding level, fares, in-vehicle travel time, waiting time at a station, walking time, and trip purpose, are examined. • Policy simulations of possible changes in public transport modal preferences in the presence of various health control measures are conducted. [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]

Transport, as an object of research and design, is directly influenced by other functional components of the territory, it is caused by them, but at the same time it determines them in terms of limitations and development. A comprehensive approach to the design of transport systems involves a wide range of analytical and synthetic activities. Transport and territory are interrelated, while transport is one of the main factors defining the functionality of territorial structures. The development of transport systems brings greater availability of work, services, and leisure activities. The transport solution in the territory must be directed towards the adequate satisfaction of the transport needs, which are characterized by the intensity of the transport relations in the territory, depending on the time and quality of the relocation. The article presents a methodology for the design of regional public passenger transport lines, in accordance with the principles of sustainable mobility, supporting the competitiveness of public passenger transport and the efficient use of resources. The proposed methodology presupposes an already completed and processed analytical phase of the transport planning process and includes the impact of public passenger transport on the external environment. The methodology is applicable under the conditions of designing a completely new transport service system, as well as in the process of reorganizing existing transport systems, including rail and bus transport. [ABSTRACT FROM AUTHOR]

Urban rail transit has the potential to utilize surplus capacity to carry out urban freight transportation during off-peak periods. Based on the characteristics of virtual coupling operation and organization mode, this paper comprehensively considers the competition between passenger flow and freight flow, takes the train stopping plan and train carriage allocation as the main decision variables, and takes the minimization of passenger waiting time and the maximization of average full load rate as dual objectives to construct a multi-objective optimization model of passengerfreight collaborative transport scheme of urban rail transit under virtual coupling conditions. The multi-objective optimization model is developed to obtain the system optimization of the train stopping plan, running plan, carriage allocation plan, and passenger-freight collaborative transport plan. Numerical experiments are designed to verify the model's validity, using Wuxi Metro Line 3 as an example, and the NSGA-II algorithm solves all experiments. The results of the algorithm show that, compared to the traditional single passenger transport with a fixed large coupling, the scheme in this paper can simultaneously improve the average full capacity of the whole line by about 38.5% during the study period with only 0.65 minutes increase in the average passenger waiting time for the same number of rolling stocks, which can effectively shorten passenger travel time and improve the quality of passenger service in urban rail transit while ensuring transport efficiency. [ABSTRACT FROM AUTHOR]

Mobility as a service (MaaS) is an emerging framework that integrates multiple transport services into a single and intuitive platform. This paper contrasts the urban passenger transport markets in developed versus developing economies to understand the challenges of integrating mobility services using the MaaS framework, with a focus on decarbonization and sustainability as societal goals. In addition, we conducted a Life Cycle Assessment of carbon emissions and energy requirements of travel alternatives in the city of Santiago, Chile, to shed light on the effects of multimodality as an environmental tool. A summary of findings follows. Data sharing and open data are new in developing countries, and thus more investment in data infrastructure is required so that MaaS can leverage digital technology and network optimization. If the scalability of MaaS is an open question in developed countries, it is more so in developing countries, owning to institutional and financial constraints that are present in the latter. The lack of public subsidies to support formal public transport is a key limitation for the implementation of MaaS schemes and multimodal frameworks in the developing world. Regarding formality, in countries with an informal public transport sector, a potential implementation of MaaS will be spatially constrained to those locations where public transport operates formally and frequently (BRT and rail lines), limiting its spatial coverage and posing social equity issues. In countries with scarce or no public funds available for the transport sector, MaaS could be used as a catalyst for a broad environmental and equity-seeking transport pricing reform which requires a direct involvement of public sector in both regulation and financial backing. We conclude that the formalization and general improvement of the public transport sector, the regulation of shared-mobility platforms including the formalization of the work of drivers, and the setting of proper pricing and subsidization instruments in the direction of internalizing the social costs of motorized traffic, are all prerequisites for any MaaS system that aims to improve economic efficiency, social equity, and sustainability. • Assess MaaS as a framework for decarbonization in developing world. • Discuss governance and equity issues in implementing MaaS. • Identify carbon policy for different cities to achieve sustainability. • Conduct a life cycle assessment to inform carbon strategies. • Scalability is a key challenge in both developing and developed worlds. [ABSTRACT FROM AUTHOR]

The high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic. [ABSTRACT FROM AUTHOR]

As an important part of the operation preparation process of the intelligent transportation system, the passenger flow distribution law and forecast can guide the urban rail transit to formulate a reasonable operation scheduling plan. Due to the complexity, multi-variables, and instability of traffic passenger flow data, accurate passenger flow prediction takes a lot of work. Based on a convolutional neural network, a causal convolution self-attention traffic passenger flow prediction model MTS-Informer framework is proposed. This method follows the changing law of auxiliary variables, adopts the stabilization method to reduce the instability of the original sequence, and uses the causal convolution feature to improve the ability of the model's self-attention mechanism to extract local information from the input sequence. The weakening effect of the self-attention mechanism ensures that it can learn similarly to the differential features in the original sequence data. In addition, the stationarity detection of the original sequence data is added. The experimental results show that the fitting degree of the sample data is significantly improved, and the standard error decreases between 10 and 40%, which verifies the effectiveness of the proposed modeling technique. It has higher prediction accuracy and operating efficiency and can provide a basis for urban traffic passenger flow prediction. [ABSTRACT FROM AUTHOR]

The high-speed railway has become an important passenger transport mode. Relying on the abundant passenger transport experience and expansive railway network, the high-speed freight train (HSFT) is feasible to be developed and has great application potential. As a critical component of HSFT, the cargo plays an important role in the overturning safety of HSFT under strong wind conditions. Previous studies about the aerodynamic performance of the high-speed train usually regarded the loaded carbody as an individual rigid body. Limited attention was paid to the variability inside the vehicle. In order to improve the running safety of HSFT under strong wind conditions, the multibody dynamics simulation is adopted to demonstrate the effect of cargo property on the overturning risk of HSFT under the aerodynamic loads obtained through the computational fluid dynamics (CFD) simulations. It is demonstrated that the inner side crosswind is more dangerous than the outer side crosswind. The speed of HSFT should be limited according to the cargo quantity, and the maximum speed for a fully loaded HSFT can be 305 km/h when the crosswind velocity is 20 m/s. The larger cargo density should be encouraged because it is good for train overturning safety in severe working conditions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a profound impact on global travel, resulting in significant disruptions to airport operations worldwide. The study on airport operations in Slovakia before, during, and after the COVID-19 pandemic found that passenger traffic and flight frequencies experienced significant declines during the pandemic, causing operational disruptions and financial challenges for airports. The research utilizes a mixedmethods approach, combining quantitative data analysis and qualitative insights from key stakeholders involved in airport management and operations. In the post-pandemic period, while there was some recovery, passenger numbers and flight frequencies remained below pre-pandemic levels. The study's results suggest that the aviation industry in Slovakia faces ongoing challenges in adapting to the new normal, with implications for future investments and strategies in airport management, capacity planning, and financial sustainability. [ABSTRACT FROM AUTHOR]

For the first time in spaceflight history the flight of a fully reusable launch system with rocket propulsion appears possible within the next couple of years. Apart from the implications for the orbital launch market, a fully reusable system could also enable an entirely new class of commercial point-to-point transport on Earth. Rocket propelled point-to-point systems promise the ability to transport passengers or cargo to any suitable landing site on Earth with extremely short travel times (typically less than 90 min). In this study the primary focus is on DLR-SART's SpaceLiner 7 vehicle concept with an initial comparison to Starship, currently being developed by SpaceX. The trajectories are identified using multi-objective optimization with evolutionary algorithms. These allow the identification of a solution space with regard to multiple objectives, in this case minimal overflight of populated areas and minimal peak heat flux, while still respecting other constraints (e.g. structural loads). The population disturbance is computed by using a global population density database and integrating the number of people along the flight track. Ideally, the solution space consists of a pareto-front which correlates to the most optimal solutions possible for all objectives. The mission analysis identifies various feasible trajectories around the world. Primarily, these routes are going along less populated areas such as the oceans and the polar regions. Especially the latter enable large longitudinal changes during the flight and consequently connecting distant places on Earth. The critical routes are large longitudinal crossings around the equator where land masses must be overflown. These shall be reconsidered and/or improved in the future. Comparing SpaceLiner to Starship, it is found that the mission profiles vary significantly. While SpaceLiner uses its high lift-to-drag ratio in the higher atmosphere to manoeuvre around large land masses, Starship can only follow the direct route. In contrast, Starship flies higher into space and thereby might avoid having large population disturbances on ground. Only the re-entry and landing are critical as it does not have significant cross range capability. As a design option for the next iteration of the SpaceLiner development, SpaceLiner 8, it is planned to assess the possibility of using a smaller wing to follow a similar coast through space like Starship and have a steep re-entry at the end of the flight instead of a prolonged glide. • SpaceLiner trajectory optimization using evolutionary algorithms. • Hypersonic point-to-point trajectories between major population centres on Earth. • Analysis and minimization of overflown population to avoid sonic boom disturbance. • Comparison of flight characteristics between SpaceLiner and SpaceX Starship. [ABSTRACT FROM AUTHOR]

Based on the analysis of the fundamental impact of transport infrastructure, the city and the agglomeration are increasingly interpreted as a set of historically composed residential and industrial districts formed in the areas of interchanges of different modes of transport. On the example of the City of Kyiv, the modeling of passenger flows in agglomerations of large developing cities is considered, in order to implement the provisions of a modern urban environment, based on transport analysis of the urban area, with further forecasting of passenger flows on the street-road network and choice of main types of citywide passenger transport in the city. Based on the calculation of the population and passenger formation of transport areas, a model of the city's transport infrastructure is represented, the distribution of passenger traffic by modes of transport is estimated. The results of experimental studies of the intensity of existing passenger flows and models of their definition in the agglomeration of the most valuable city are determined. And the ways to solve the problems of conflict between the city and transport are proposed. [ABSTRACT FROM AUTHOR]

Determination of transport demand is one of the key factors to solve many transportation problems. Existing methods for obtaining information about passenger mobility have significant shortcomings; currently, methods based on the collection, integration and analysis of big data (Urban computing, big data) are being increasingly used. Within the framework of this approach, a methodology has been developed for determining the passenger traffic by public transport from the operations of validating electronic travel tickets: smart cards, transport cards, magnetic cards, mobile phones or other electronic devices (Electronic Gadgets), their details are recorded in the Automated Fare Collection (AFC). In this work we have taken into account that the passenger can travel one, two or more segments before paying for the trip. On some routes, payment is made at the end of the trip. The article presents a methodology based on defining and evaluating the set of acceptable variants of the connectedness of the passenger trips' sequence, which takes into account many factors that influence the choice of travel routes by the passenger. For example, unlike existing solutions, the possibility of paying for travel at any point of the route is taken into account, not necessarily immediately after boarding the vehicle. Approbation of the considered methodology was carried out on the data of the Krasnoyarsk public transport system for April 2019. It has been proved that passenger traffic from the validation of electronic travel tickets allows us to estimate the parameters of public transport demand within the limits of acceptable statistical errors. [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 way the pandemic COVID-19 affecting the public railway transport in the South Bohemia currently is a much-debated issue. On both a theoretical and practical level, this paper aims to determine whether the pandemic COVID-19 influenced the quality of public railway transport in South Bohemia between the years 2020 and 2021. The results of the paper provide the unambiguous arguments which could have been foreseen. There is, however, dissatisfaction among individual groups of passengers as well as on the part of the state. The surveys point to the slowly improving state of the quality of public railway transport in the coming years. Statistical and mathematical methods confirm the overall weaker efficiency and stability of passenger transportation. The reason is the psychological and economic aspects due to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The efficiency of transportation systems has decreased due to restrictions to contain the spread of COVID-19. The purpose of the research was to analyze the efficiency of railways in connection with the impact of COVID-19 on rail transport itself. Thus, using data envelopment analysis we determined how the measures during the pandemic affected the efficiency of passenger and freight transport. The efficiency of the railway system was evaluated using a linear programming technique that measures the effectiveness of homogeneous decision-making units. The model's input variables consisted of technical attributes of railway tracks, while the output variables encompassed train operations, the conveyance of goods, and passenger transport. The results show the differences in railway efficiency between EU countries during the COVID-19 crisis. Our findings indicate that the COVID-19 crisis had a more substantial effect on the effectiveness of services than its impact on technical aspects. The results show the differences in railway efficiency between countries during the COVID-19 crisis. In the research, we found that the COVID-19 crisis had a negative impact on service effectiveness, as it decreased by more than 3%, while technical efficiency increased during the analyzed period, mainly at the expense of a lower number of train movements when transport equipment was not maintained. The differences between countries indicate the slow adoption of the necessary measures to mitigate the consequences of the COVID-19 crisis and the need for coordinated and flexible action by rail transport policymakers. [ABSTRACT FROM AUTHOR]

Purpose: Theadvanced air mobility (AAM) is defined by National Aeronautics and Space Administration (NASA) as safe, accessible, automated and affordable air transportation system for passengers and cargo, capable of serving previously hard-to-reach urban and rural sites. The purpose of this paper is to focus on explaining potential solutions, under study by the authors, which could support beyond visual line of sight (BVLOS) operations for goods delivery in a safe way. Design/methodology/approach: According to recent NASA-commissioned market studies, by 2030, there will be as many as 500 million flights a year for package delivery services and 750 million flights a year for passengers' transportation (AAM). A significant number of these aircrafts will be unmanned aerial vehicles, meaning that they are self-flying or autonomous, of which the smallest ones are quadcopters: they are relatively inexpensive and are capable to perform various tasks, such as aerial observation, crop monitoring and treatment, search and rescue, power line monitoring and goods delivery. On the other hand, there are still many difficulties in introducing them into medium- and low-risk BVLOS routine operations for goods delivery: unfortunately, there are no regulations and technologies yet that enable these operations. Findings: This conceptual paper outlines the studies about possible solutions, identified by authors, which could support BVLOS operations in a medium- and low-risk environment; in particular, the following aspects have been analysed: regulations, integrating control systems for drones, sensors (on board obstacle detection and avoidance), emergency management (emergency on ground system to identify safe landing areas), concepts of droneway (or flight corridors) and drones recovery hub. Originality/value: The purpose of this paper is to provide a conceptual description of the possible solutions, under study by the authors, which could contribute enabling the BVLOS operations in a medium- and low-risk environment. The paper aims describing the state of the art, terms of regulations, classifications and limitations and describing possible conceptual solutions that could guarantee safety in introducing unmanned aircraft system operations inside urban areas. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the railway passenger volume data are abnormal due to holidays and major events interfering with the prediction accuracy, the spline interpolation method is introduced to replace the abnormal passenger volume data. In addition, an improved particle swarm optimization (IPSO) is proposed to optimize the gradient difference acceleration law to combine and improve the predicted value and further improve the prediction accuracy of the railway passenger traffic. Finally, taking Beijing as the research object, the Holt exponential smoothing method and the BP neural network are selected to verify the effect of spline interpolation and IPSO-gradient difference acceleration law on prediction accuracy. The research results show that the spline interpolation method has a better prediction effect after processing abnormal passenger traffic data, and the improved particle swarm algorithm also shows better optimization ability and convergence speed when solving the double difference postulate. In comparison with the BP neural network, Holt exponential smoothing, simple averaging, and conventional redifference approaches, the IPSO-redifference acceleration method achieves a superior prediction performance, and the absolute values of the forecast error are reduced by 3.320%, 1.518%, 2.419%, and 0.602%. [ABSTRACT FROM AUTHOR]

This paper adopts the expansion intensity index, equal sector method, spatial autocorrelation, PCA-STIRPAT model, and geographic detectors to quantitatively reveal the characteristics and spatial-temporal driving factors of the construction land growth pattern in the CZT metropolitan area from 1990 to 2018. The results show that: (1) The construction land of CZT metropolitan area expanded slowly from 1990 to 2000, expanded rapidly from 2000 to 2010, and expanded slowly from 2010 to 2018. In the three stages, the main expansion directions of the construction land in the CZT metropolitan area are different. The direction of expansion of the Changsha metropolitan area changed from northeast to southwest, the expansion direction of Zhuzhou metropolitan area changed from southwest to west, and the expansion direction of Xiangtan metropolitan area changed from south to north. It can be seen that under the influence of the integrated construction of the CZT urban agglomeration, the expansion direction of the three cities tends to move closer to the central intersection. (2) From 1990 to 2018, the expansion of construction land in the CZT metropolitan area showed an overall trend of agglomeration. Wangcheng District and Changsha County of Changsha City were hot spots for construction land growth, while Lukou District of Zhuzhou City and Xiangtan County of Xiangtan City were extremely cold spots for construction land growth. (3) The dominant time driving factors for the expansion of construction land are local fiscal expenditure, fixed asset investment, highway passenger traffic, total population, number of employees, and number of patent authorizations. In a comprehensive view, socio-economic investment, population growth and technological progress are important driving forces for the expansion of construction land. Population and GDP are the dominant spatial driving factors for the expansion of built space. [ABSTRACT FROM AUTHOR]

This paper examines whether or to what extent San Francisco International Airport's (SFO's) purportedly high costs relative to other airports suppressed SFO's traffic demand and prolonged the recovery of passenger traffic in the period after the 11th September, 2001 terrorist attacks. A comparative analysis of the historical data shows that SFO's direct airport costs per enplanement (CPE) were higher than most other major airports in the post-9/11 period by a considerable margin, but that airport costs likely were not a significant factor in SFO's prolonged recovery. Airport costs likely did not affect airline profitability sufficiently to influence route and scheduling decisions, and it is unlikely that passenger demand was dampened by the pass-through of higher costs to airfares. This research suggests at best a tenuous relationship between airport rates and passenger activity, and at SFO the evidence does not suggest that an extremely high CPE relative to peer airports affected the pace of its slow return to pre-9/11 traffic levels. Rather, the slow return of traffic to SFO and its neighbour, Norman Y. Mineta San Jose International Airport (SJC), compared to the robust growth at Oakland International Airport (OAK) can be explained by traditional economic means. It also suggests that in a multi-airport region where each airport is somewhat specialised, an individual airport's over- or underperformance relative to its neighbours is more likely to be a function of economic geography than of any airport's rate-setting practices. If this conclusion holds true for other US airports, it emphasises the ability of airports to create capital plans and set rates and charges to make long-term investments in organic air traffic growth, ensuring that new entrant airlines have sufficient facilities to begin service and that existing airlines have sufficient capacity to grow. [ABSTRACT FROM AUTHOR]

This paper examines the ways an inter-municipality bus system for passengers improved its accessibility and affordability for end-users at regional level. Using archetype theory, we conducted a case-study in FÖLI, a not-for-profit organization tasked with collective transport of passengers by bus in Southwest Finland. We find that FÖLI implemented a radical revolutionary change by introducing a new framework for the carriage of passengers by bus at a regional level, in which a zone free and flat fare policy applies. The sequence of change became central; with a continuous reorientation linearity aiming to improve the accessibility and affordability of collective transport by bus for commuters. The paper contributes to archetype theory by examining the relevance of accessibility and affordability in the configuration process of designing and implementing change, and extending knowledge in this area. Specifically, for the first time, our research shows the way in which FÖLI used the accessibility and affordability policy as an interpretative scheme to design and implement the change process successfully. The practical implication is that municipalities understood the relevance of improving collective transport infrastructures (roads, systems and technologies) to attract commuters as a way of saving total costs to fund underperforming buslines. [ABSTRACT FROM AUTHOR]