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One key question about transport of active polymers within crowded environments is how spatial order of obstacles influences their conformation and dynamics when compared to disordered media. To this end, we computationally investigate the active transport of tangentially driven polymers with varying degrees of flexibility and activity in two-dimensional square lattices of obstacles. Tight periodic confinement induces notable conformational changes and distinct modes of transport for flexible and stiff active filaments. It leads to caging of low activity flexible polymers inside the inter-obstacle pores while promoting more elongated conformations and enhanced diffusion for stiff polymers at low to moderate activity levels. The migration of flexible active polymers occurs via hopping events, where they unfold to move from one cage to another, similar to their transport in disordered media. However, in ordered media, polymers are more compact and their long-time dynamics is significantly slower. In contrast, stiff chains travel mainly in straight paths within periodic inter-obstacle channels while occasionally changing their direction of motion. This mode of transport is unique to periodic environment and leads to more extended conformation and substantially enhanced long-time dynamics of stiff filaments with low to moderate activity levels compared to disordered media. At high active forces, polymers overcome confinement effects and move through inter-obstacle pores just as swiftly as in open spaces, regardless of the spatial arrangement of obstacles. We explain the center of mass dynamics of semiflexible polymers in terms of active force and obstacle packing fraction by developing an approximate analytical theory. [ABSTRACT FROM AUTHOR]

AbstractDynamic community division is crucial for comprehending the interactive structure and mechanism between residents and space. Currently, there is insufficient research on dynamic community changes in travel networks regarding travel distance. This study utilizes residents’ travel trajectories to construct a multi-layer network based on travel purposes. The study establishes methods for identifying travel network communities and analyzing community evolution influence. Dynamic characteristics of travel network communities at different distances are extracted. Results show that within 3–7 km travel distance, different travel network communities exhibit continuous spatial aggregation, whereas beyond 11 km, heterogeneity is observed. Moreover, communities within 3-7 km experience drastic dynamic evolution, whereas beyond 7 km, they tend to stabilize, forming a large-scale and fixed travel mode. This study enriches the dynamic interaction research of functional space from the perspective of distance, and the experimental results provide an effective reference for urban planning and management. [ABSTRACT FROM AUTHOR]

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

App-based mobility (ABM) is an umbrella term for several transport services enabled through a smartphone application. Ride-hailing is the most popular ABM service, and even more than a decade after its introduction, it continues to raise concerns about its impacts on urban mobility. Previous ride-hailing research has primarily focused on understanding such impacts. However, how ride-hailing affects accessibility and social exclusion remains an understudied topic. Prior research highlights this knowledge gap and proposes a framework linking ABM with transport poverty, (in)accessibility and the resulting transport-related social exclusion (TRSE). Yet, empirical evidence is lacking to test such a framework. This paper addresses this gap by providing empirical evidence on how ABM affects accessibility using survey data collected for three large metropolitan areas in Latin America. We follow three related lines of analysis. First, we compare ride-hailing to other transport modes based on the most regular trips reported in the survey. Second, we calculate novel social and transport (dis)advantage indices to extend the comparison of transport modes. Third, we shed light on why respondents have used ride-hailing services in the past. [ABSTRACT FROM AUTHOR]

The cover image is based on the Article A hybrid method for intercity transport mode identification based on mobility features and sequential relations mined from cellular signaling data by Fan Ding et al., https://doi.org/10.1111/mice.13229.. [Extracted from the article]

The proliferation of mobile phones has generated vast quantities of cellular signaling data (CSD), covering extensive spatial areas and populations. These data, containing spatiotemporal information, can be employed to identify and analyze intercity transport modes, providing valuable insights for understanding travel distribution and behavior. However, CSD are primarily intended for communication purposes and are not directly suitable for transportation research due to issues such as low spatial precision, sparse sampling granularity, and lacking traffic semantic features. This article proposes a Hybrid model for identifying individual intercity transport modes based on CSD. Several multidimensional mobility features are proposed that extract interpretable motion characteristics from CSD. A preliminary transport mode probability judgment is made based on the mobility features. Then, the complete transport mode is confirmed considering the temporal continuity correlation of the entire trace. Experiments confirm the Hybrid model's superior precision in identifying transport modes over baseline models, with an average F1 score of 0.92, maintaining high accuracy across various trajectory lengths. This model would support further studying individual intercity travel behavior patterns, aiding transportation planning and operational management decisions using CSD. [ABSTRACT FROM AUTHOR]

Reducing urban car traffic has become a global policy objective. A vital element in achieving this objective is the availability of shared mobility providers offering sustainable alternative travel modes such as micromobility, carsharing, and ridehailing. Despite policy and industry efforts, shared mobility options have failed to change the travel patterns of current car users. We explore this urban mobility challenge through an empirical study of 807 urban travelers. Our results show that car drivers estimate travel costs conceptually rather than rationally and consider both trip purpose and length. In particular, car users perceive longer and recreational trips as cheaper per distance driven than shorter and work-related trips. A segmentation analysis reveals that habitual and technology-averse car drivers are particularly susceptible to this skewed cost perception, unlike more frequent transit users. Embedding these results in a case study of current shared mobility options shows that these options are ill-adjusted to the preferences of car travelers but more attractive to current transit users, potentially leading to cannibalization. Based on these findings, we outline several strategies for mobility providers and policymakers to attract car drivers to shared mobility options, thereby contributing to solving the urban mobility challenge. • Car users perceive trip costs differently based on trip length and purpose (work versus leisure). • Longer and recreational trips are perceived as cheaper per distance driven than shorter and work-related trips. • Habitual and technology-averse car drivers are more susceptible to skewed cost perception compared to frequent transit users. • Current shared mobility offers are more attractive to transit users than car drivers, potentially leading to cannibalization. [ABSTRACT FROM AUTHOR]

A multi-objective solid transportation problem that includes source, destination, and mode of transport parameters may have fractional objective functions in real-life applications to maximize the profitability ratio, which could be the profit/cost or profit/time. We refer to such transportation problems as multi-objective fractional solid transportation problems. In addition, although most of the studies in the literature deal with the standard equality-constrained form of the multi-objective fractional solid transportation problem, the mixed-constrained type is addressed in this paper. With these mixed constraints, the multi-objective fractional solid transportation problem offers more flexible modeling of real-world problems that exist in many application areas, but mixed constraints also make the optimization process more challenging. This article presents an iterative fuzzy approach that combines the use of linear programming and the bisection algorithm using linear membership functions to obtain a strongly efficient solution. The algorithm's ability to convert a nonlinear problem into a set of linear problems is one of its main advantages, and it also decreases the amount of time needed to solve large-scale problems. A numerical example from the literature is adopted to illustrate the solution procedure. Moreover, large-scale instances are generated to further test the presented algorithm, and a comparison between the traditional fuzzy approach and the proposed method is presented. [ABSTRACT FROM AUTHOR]

The spread of e-commerce has transformed consumer habits and distribution. There is a need to improve the location of pickup points, starting from small inland areas to areas with particular travel problems, such as the one chosen, i.e. Enna, in the centre of Sicily. The following research focuses on a two-level analysis of the accessibility perceived by users and commercial vehicles. A series of indicators were defined to evaluate the supply in terms of accessibility, the construction of isochrones, and the selection of the walking mode of travel (by demand-user). Comparing the results obtained with the values of the resident population in the different areas adjacent to the sampling points, it emerged that, at present, the 12 presented sampling points do not have an optimised spatial distribution. The overall coverage is about 60% of the population, while all sampling points are generally easily accessible. The results form the basis for more in-depth analyses to improve urban logistics and last-mile services. [ABSTRACT FROM AUTHOR]

Pine Island Academy, present in Nocatee Community, Jacksonville, Florida, uses various modes of transport for picking up and dropping off children at school. The parents using private vehicles to pick up and drop off their kids tend to take a long time due to delays and congestion in their routes. Parents who use golf carts (GC) for this activity tend to take a short time to pick up and drop off their kids. Due to this, it is necessary to analyze the use of GC as an alternative mode of transport for children pick up and drop off while reducing delay and congestion. This paper uses VISSIM microscopic simulation for analysis whereby the traffic flow in the morning for drop-off and the afternoon for pickup was observed at different GC traffic compositions regarding the relative delay, queue delay, and travel times. From the analysis, it was observed that the delays and travel times for private vehicles decrease as the GC composition increases in the network. These results show that a GC may be suitable for picking up and dropping off children at school. This factor is further supported by the ANOVA test of significance. Due to the results from this paper, recommendations to the transportation agencies responsible for school management include promoting GC usage, establishing designated GC lanes to ensure smooth traffic flow and minimal interaction with other vehicles, implementing a multi-modal approach that includes GCs, and emphasizing safety training and awareness for GC users. [ABSTRACT FROM AUTHOR]

This study uses detailed data on exports from the European Union (EU-28) to non-EU countries to investigate the impact of global production fragmentation on the choice of transportation modes. The article finds a positive relationship between production fragmentation and air transportation. The study also finds that air transportation is more likely to be chosen for high-value products. Additionally, the positive effect of production fragmentation on the likelihood of using air transportation is more pronounced when goods are exported to medium-range markets, upper-middle-income countries, countries with better air transportation infrastructure, and time-sensitive products. [ABSTRACT FROM AUTHOR]

ABSTRACT The impact of population mobility and transportation choices on the environment is significant. Sustainable mobility policies require an understanding of evolving mobility patterns. This study examines global mobility variations across countries using COVID‐19 Community Mobility Reports. Employing the k‐medoids algorithm and Dynamic Time Warping, we analyzed mobility dynamics. Results reveal diverse changes in population mobility. Around 52 Global North countries exhibit approximately 10% reduction in professional activity‐related traffic post‐COVID‐19. Regarding urban green space mobility, only 29 countries exhibit strong seasonality, with summer traffic in the northern hemisphere peaking at about 150% higher than winter traffic. Three groups of countries are identified concerning public transport mobility: returning to pre‐pandemic levels, experiencing a 25% increase, and nearly doubling from pre‐pandemic levels. This underscores the key determinants for sustainable mobility policy implementation. Fifteen highly developed countries share similar mobility patterns across six areas studied, facilitating the exchange of sustainable mobility solutions and best practices. This research underscores the importance of understanding and addressing evolving mobility patterns for effective environmental policy planning. [ABSTRACT FROM AUTHOR]

In the twenty-first century, global warming has become one of the severe challenges. Around one-fourth of the total carbon footprint is contributed by transport vehicles. It is crucial to provide alternative solutions to unsustainable transportation systems. This study compares the present travel modes of students of the Capital University of Science and Technology, Islamabad, with the proposed sustainable travel mode. A campus survey (N = 565) was conducted to understand travel choices, travel times, origin and destinations, and student preferences, considering university buses and private vehicles. A comparison was made between the travel time analysis of university bus users and non-bus users. A sustainability analysis has been conducted to evaluate the effects of the present travel modes on students and the proposed university bus transport system. Five main factors were compared: fuel consumption and associated fuel costs, carbon and vehicular emissions, traffic noise pollution, traffic congestion, and accident ratio. The results show that 38% of students commute by private cars and 18% by motorbikes. Around 25% of the students avoid university buses due to long travel times, and 30% prefer because their parents ask them. On average, university buses take 56.8 min, and non-bus transports take 38.8 min for one-way travel. If all students travel by university busses, they could be 86% more sustainable in fuel costs and carbon emissions than non-bus travel modes. These results give useful policy implications for providing sustainable travel alternatives to educational institutions. [ABSTRACT FROM AUTHOR]

The post-growth literature has recently started to engage with transport and mobilities in more depth. However, despite its radical societal critique, it has done so largely in ways that either reproduce recommendations of the sustainable mobilities paradigm or apply context-independent post-growth frameworks without sustained empirical analysis. The literature has thereby largely “closed down” more open-ended explorations of what kind of transport and mobility futures are desirable and possible from a post-growth perspective. This article seeks to remedy this by highlighting the role of innovative practices in bottom-up initiatives that have been invisibilised, in expanding our imaginaries of possible post-growth transport and mobility futures. It builds on Deleuze and Guattari’s concept of the minor, an orientation towards difference-in-itself emerging immanently, to explore such innovative and experimental practices that may be of interest for post-growth transformations. We illustrate the minor’s usefulness by studying two bottom-up initiatives, a French railway cooperative and a German “rolling supermarket”, which we examine with a view towards “difference” that allows for open-endedness and the generation of questions. This article contributes to post-growth transport and mobility scholarship by advocating for a shift in three analytical focal points, building on the minor’s generativity: moving from a-contextual recommendations to examinations of socio-spatially specific transformation (1), from a concern for the “right” modes of transport to minorities (2), and from a near-exclusive focus on the public sector to a more diverse range of economic actors and practices (3). [ABSTRACT FROM AUTHOR]

Accurate assessment of bedload transport is a challenging task due to its variable nature in space and time. Bedload transport measurement techniques can be divided into two categories of direct and indirect methods. The focus of this study is on dune tracking as an indirect measurement method that has received much attention in recent years. However, a comprehensive workflow that allows the integration of this method into a routine measurement operation instead of or jointly with the direct sampling method has not been implemented yet. During a three-day measurement campaign conducted in the Rhine River, a detailed workflow for performing bedload transport measurements using the dune tracking method was introduced. Dune tracking validation was thoroughly evaluated, with significant efforts to simultaneously collect data using direct sampling. Direct measurements of bedload transport showed higher and more variable rates compared to dune tracking estimates. It was assumed that finer sediment fractions, moving as patches or small-scale superimposed bedforms were presumably not captured by the dune tracking. However, their significant contribution to bedload transport suggests that dune tracking estimates may have been underestimated. Further research is needed to explore how varying flow and sediment conditions affect bedload transport modes and measurement methods comparability. [ABSTRACT FROM AUTHOR]

Public transport systems worldwide experienced significant declines in usage during the COVID-19 pandemic due to lockdowns and work-from-home mandates. While numerous studies have examined these phenomena, there is still a need for empirical evidence that not only documents what occurred but also provides actionable insights for future transport planning. This study aims to enhance understanding of public transport passengers' mobility behaviors during different stages of the pandemic, using the Metropolitan Area of Porto, Portugal, as a case study. Automated Fare Collection data from 2020 were analyzed and compared with data from the pre-pandemic year of 2019. The analysis included temporal, spatial, spatio-temporal, and sociodemographic dimensions. Key patterns and trends identified include a rapid recovery of ridership post-restriction easing, homogenized daily travel patterns, varied impacts on different transport modes, and significant shifts in demographic travel behaviors. These findings highlight the resilience of public transport demand and suggest that adaptive scheduling, enhanced safety measures, targeted support for vulnerable groups, promotion of off-peak travel, investment in bus infrastructure, and encouragement of multi-modal transport are essential strategies. Implementing these strategies can help improve public transport planning and mitigate the adverse effects of future crises. [ABSTRACT FROM AUTHOR]

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

The Covid-19 pandemic has affected the entire world and changed many aspects of daily life, including transportation behaviour and preferences. This study examines the situation of transportation behaviour and preferences before and after the Covid-19 pandemic process through a survey study. A total of 471 people participated in the survey, and 30 questions were posed to participants regarding transportation modes preference, daily usage habits, public transportation usage rate, income status, perceived risk level of transportation systems, preferences before and after the pandemic process, and more. The answers were classified, evaluated and statistically analysed. The results showed that users were significantly affected by the Covid-19 process and changed their transportation mode preferences. The use of buses in urban journeys decreased, and the use of private vehicles significantly increased after the Covid-19 process. Hygiene was the key factor in travel, followed by the vehicle occupancy rate, ventilation, fare and travel time factors. The perceived risk levels of public transportation systems were ranked as metrobus, minibus (paratransit), bus, metro, tram and ferry. The study suggests that future transportation system designs should consider user preferences, as well as changes in education and working conditions, and pandemic conditions. [ABSTRACT FROM AUTHOR]

Integrated computational spectrometers with gate‐tunable nano heterostructures and reconstruction algorithms are attractive for on‐chip gas‐sensing spectrometers and have enabled versatile spectrum detectors. However, they require the selective and optical filtering capabilities of wavelengths, restricting their efficient implementation in narrow‐band photodetection. In this study, a printable spectral phototransistor is developed with high dynamic detectivity (1012 Jones and 105 Hz at −3 db bandwidth) modulated by a GeS2 nanosheet heterostructure at short‐wave infrared (SWIR) regime. Using the transport mode switching of carriers in a heterostructure and the polarization‐sensitivity of the GeS2 two‐dimension (2‐D) nanosheet, this SWIR spectral phototransistor demonstrates an accurate narrow‐band selective (96.7% accuracy) spectrum detector and performed a deep‐learning analysis of an artificial neural network (ANN). Furthermore, this GeS2 2‐D based spectral phototransistor, characterized by its high in‐plane anisotropy and electrically reconfigurable properties, extends the applicability of narrow‐band photodetection with 15 nm Full Width at Half Maximum (FWHM) to the recognition of trace‐gases at the parts per billion (ppb) level. [ABSTRACT FROM AUTHOR]

It is crucial to understand the mechanism of how people perceive and accept Shared Autonomous Vehicles (SAVs) to realize the benefits that they will bring to transport networks, including increased safety on the roads. Experience with semi-automated cars and Autonomous Vehicle (AV) demonstration projects has been shown to positively affect acceptance of AVs, however automated transport technologies have been adopted in practice for years such as automated railways and aircraft autopilot; whether there are any connections between exposure to automated railways and aircraft autopilot and acceptance of SAVs is not well known. We explored the connections between trust in safety, knowledge of, and experience with automated railways, aircraft autopilot, and ADAS and intention to use a SAV. We surveyed individuals from Korea National University of Transportation (KNUT) in Chungju, Korea (n = 226), who will soon be able to use a SAV service, and adopted a model based on the Technology Acceptance Model (TAM). We found there to indeed be a connection between exposure to and trust in the safety of existing automated transport modes and acceptance of a SAV. Constructs with the strongest effects were found to be trust in safety of automated transport, hedonic motivation, perceived ease-of-use, perceived usefulness, and knowledge of automated transport. Experience with automated railways, but not semi-automated cars, was found to negatively moderate the relationship between hedonic motivation and intention to use a SAV. We discuss the policy implications of these results. [ABSTRACT FROM AUTHOR]

Public transport ridership has been hit hard by the COVID-19 pandemic in many countries. Investigating passengers' public transport mode choice behavior during large-scale public health incidents can uncover the major influential factors and help propose policies and strategies to reduce the pandemic transmission and recover the public transport revenue. This study develops an integrated choice and latent variables (ICLV) model by income based on structural equation model to model passengers' public transport choice behavior during the normalized stage of the pandemic. The model considers passengers' socioeconomic attributes, travel attributes, and attitude-perception attributes, and can appropriately capture passengers' psychological latent attributes. Taking Beijing China as an example, we collect some revealed preference survey data online. The modeling results show that the risk perception as a mediator variable has a significant impact on mode preference. Moreover, the convenience of public transport has the largest influence on risk perception. These findings suggest that risk perception and the convenience of public transport play a major role in passengers' mode choice behavior. In addition, the impacts of the various influential factors on the public transport mode choices are significantly different across different income groups. Further, the ICLV model can achieve better performance and is superior to the traditional Multinomial Logit model. The modeling framework can help propose targeted and instructive strategies during the normalized stage of the pandemic by uncovering the major influential factors in passengers' public transport mode choices, which is applicable to similar pandemics in the future. • The socioeconomic attributes, travel attributes, and attitude-perception attributes are systematically considered to study passengers' public transport mode choice behavior during the normalized stage of the pandemic. • The integrated choice and latent variables (ICLV) model can appropriately capture the psychological latent attributes. • Risk perception has statistically significant impact on passengers' public transport mode choice behavior while the convenience of public transport mode has the largest influence on risk perception. • The ride-hailing and shared bike are commonly acknowledged as being less risky than subway and bus. • The effectiveness of the ICLV model considering different income groups is demonstrated through numerical experiments. [ABSTRACT FROM AUTHOR]

Estimating origin-destination (OD) demand is integral to urban, regional, and national freight transportation planning and modeling systems. However, in developing countries, existing studies reveal significant inconsistencies between OD estimates for domestic and import/export commodities derived from interregional input-output (IO) tables and those from regional IO tables. These discrepancies create a significant challenge for properly forecasting the freight demand of regional/interregional multimodal transportation networks. To this end, this study proposes a novel integrated framework for estimating regional and international (import/export) OD freight flows for a set of key commodities that dominate long-distance transportation. The framework leverages multisource data and follows a three-step process. First, a spatial economic model, PECAS activity allocation, is developed to estimate freight OD demand within a specific region. Second, the international (import and export) freight OD is estimated from different zones to foreign countries, including major import and export nodes such as international seaports, using a gravity model with the zone-pair friction obtained from a multimodal transportation model. Third, the OD matrices are converted from monetary value to tonnage and assigned to the multimodal transportation super network using the incremental freight assignment method. The model is calibrated using traffic counts of the highways, railways, and port throughput data. The proposed framework is tested through a case study of the Province of Jiangxi, which is crucial for forecasting freight demand before the planning, design, and operation of the Ganyue Canal. The predictive analytics of the proposed framework demonstrated high validity, where the goodness-of-fit (R2) between the observed and estimated freight flows on specific links for each of the three transport modes was higher than 0.9. This indirectly confirms the efficacy of the model in predicting freight OD demands. The proposed framework is adaptable to other regions and aids practitioners in providing a comprehensive tool for informed decision-making in freight demand modeling. [ABSTRACT FROM AUTHOR]

The unprecedented COVID-19 outbreak has significantly influenced our daily life, and COVID-19's spread is inevitably associated with human mobility. Given the pandemic's severity and extent of spread, a timely and comprehensive synthesis of the current state of research is needed to understand the pandemic's impact on human mobility and corresponding government measures. This study examined the relevant literature published to the present (March 2023), identified research trends, and conducted a systematic review of evidence regarding transport's response to COVID-19. We identified key research agendas and synthesized the results, examining: (1) mobility changes by transport modes analyzed regardless of government policy implementation, using empirical data and survey data; (2) the effect of diverse government interventions to reduce mobility and limit COVID-19 spread, and controversial issues on travel restriction policy effects; and (3) future research issues. The findings showed a strong relationship between the pandemic and mobility, with significant impacts on decreased overall mobility, a remarkable drop in transit ridership, changes in travel behavior, and improved traffic safety. Government implemented various non-pharmaceutical countermeasures, such as city lockdowns, travel restrictions, and social distancing. Many studies showed such interventions were effective. However, some researchers reported inconsistent outcomes. This review provides urban and transport planners with valuable insights to facilitate better preparation for future health emergencies that affect transportation. [ABSTRACT FROM AUTHOR]

E-scooter services have multiplied worldwide as a form of urban transport. Their use has grown so quickly that policymakers and researchers still need to understand their interrelation with other transport modes. At present, e-scooter services are primarily seen as a first-and-last-mile solution for public transport. However, we demonstrate that 50 % of e-scooter trips are either substituting it or covering areas with little public transportation infrastructure. To this end, we have developed a novel data-driven methodology that autonomously classifies e-scooter trips according to their relation to public transit. Instead of predefined design criteria, the blind nature of our approach extracts the city's intrinsic parameters from real data. We applied this methodology to Rome (Italy), and our findings reveal that e-scooters provide specific mobility solutions in areas with particular needs. Thus, we believe that the proposed methodology will contribute to the understanding of e-scooter services as part of shared urban mobility. [ABSTRACT FROM AUTHOR]

Morphological characteristics were measured for barchan dunes on Earth (2,686 dunes in 30 barchan fields) and Mars (720 dunes in 10 barchan fields) using satellite images. The data were used to (a) develop a new barchan classification system; (b) compare characteristics of barchans on Earth and Mars; and (c) assess whether barchans, in bulk, display allometric or scale‐invariant characteristics. Dimensional metrics were obtained for the width and length of barchan bodies, the width and length of barchans including the horns, and the length of each horn. Dimensionless metrics were derived for the ratios of the body width to the width between the tips of the horns (width ratio), the length of the entire barchan to the length of the body (length ratio), and the length of the longer horn to the shorter horn (symmetry ratio). The width, length, and symmetry ratios were used to classify barchans into eight types and compare the characteristics of their distributions on the two planets. From this analysis, it was established that, statistically, barchans on Earth are distinctive from those on Mars based on the morphometrics, with terrestrial barchans being, on average, of smaller size and more often symmetrical, while Martian barchans more often have convergent horns that are short relative to the central dune body and are more often asymmetrical. The analysis further reveals that barchan planform morphology can be considered scale‐invariant, and we argue that body width is the most appropriate measure representing barchan size. Plain Language Summary: Crescent‐shaped sand dunes (barchans) are widely found on Earth and Mars. Relative variations in the shape of these bedforms are thought to reflect differences in the planetary sand transport environment in terms of sand flux magnitudes, transport modes, and wind climate (speeds and directional variability). Comparing the shapes of barchans on Mars with those on Earth can generate hypotheses on how and why sand transport conditions and dune formation under the Martian atmosphere may be different. Satellite imagery analysis of 3,406 barchan dunes on both planets yields insights on planform dimensions (width and length of the dune body, lengths and divergence of the horns) as well as three shape indices (Width Ratio, Length Ratio, Symmetry Ratio) that were used to derive a classification of eight barchan types. Analysis shows that average barchan planform geometry displays fixed proportions over several orders of magnitude in size (scale‐invariance). Significant relative differences are apparent between the two planets, with barchans on Mars generally being much larger in absolute size but having shorter, more convergent and asymmetric horns than barchans on Earth. The study further suggests that the transverse width of the dune body is the best measurement to reflect the overall size of a barchan. Key Points: A classification of barchan types is derived by applying three morphometric indices to 3,406 dunes on Earth and MarsBarchan planform morphology can be considered a scale‐invariant property over orders of magnitudeDifferences in relative morphology reflect differences in planetary sand transport conditions and dune formation [ABSTRACT FROM AUTHOR]

The onset of autonomous inland shipping comes with regulatory challenges. First, regulations currently in place do not permit the operation of autonomous ships, mainly due to crewing requirements. Second, autonomous transport modes are deemed to be disruptive technologies that present a particular challenge to public regulators with regard to their potential for unforeseen risks and uncertainties inherent to their implementation. From a public regulator's perspective, it is, therefore, of the utmost importance to identify and regulate the factors currently hindering the introduction of autonomous inland shipping, on the one hand, and the newly emerging issues, on the other hand, to minimise potential risk and uncertainty as much as possible. This paper presents a systematic literature review which was conducted to answer the research question: What factors influence the regulation of autonomous inland shipping? Following the outcome of the literature review, various factors could be identified, and four main categories of factors were established: technological, infrastructure, institutional and socio-economic readiness. The identified factors were subsequently discussed with regard to their significance for the regulatory agenda in light of factors found in the literature on autonomous maritime ships. The findings are of relevance for public regulators and policymakers working in the field of autonomous inland shipping. Moreover, the results presented in this paper might be also of interest for those seeking regulatory innovation regarding autonomous processes in other modes of transport. [ABSTRACT FROM AUTHOR]

Passenger comfort significantly influences commuter satisfaction and mode preferences in urban transportation systems. To maintain competitiveness and attract more passengers, conducting continuous performance evaluations based on key performance indicators is commendable. Therefore, this study is aimed at conducting a mode‐wide comfort performance evaluation and comparisons to identify the strengths and weaknesses of respective mass transport alternatives found in Addis Ababa, Ethiopia. The study employs a comprehensive approach by integrating both subjective surveys and objective measurements on key comfort determinants, including in‐vehicle passenger loading, travel time, vibration, and sound, across five transport modes: minibus taxis, midi buses, PSETSE, Anbesa City Bus Service Enterprise (ACBE), and Sheger Mass Transport Enterprise (SMTE). Analysis of variance (ANOVA) reveals variations among transport modes, with minibus taxis emerging as the most comfortable, featuring a travel time of 1.7 min/km, 2.6 min/km during off‐peak and peak times of the day, respectively, and an average of 1.13 passengers per seat in both periods of the day. In contrast, midi buses are identified as the least comfortable, characterized by elevated noise production (77.46 and 80 dB) and an average vibration rating of 3.9 and 4.2 at peak and off‐peak periods of the day. Following midi buses, the ACBE exhibits the highest passenger loading and travel time (2.113 and 1.548 passengers per seat and takes 4.2 and 3.34 min) to cover 1 km during peak and off‐peak periods, respectively. The holistic evaluation demonstrates an average correlation of 81.75%, indicating a strong alignment between peak‐hour objective and subjective assessments. This could help commuters make relevant mode choice decisions and transport companies make market‐oriented decisions in this competitive environment. [ABSTRACT FROM AUTHOR]

Background: The processes of transport decarbonisation are complicated. In this paper, we adopt the Activity-Modal Share-Energy Intensity-Carbon Intensity of Fuel (ASIF) approach and propose a conceptual framework on the direct and indirect impact of COVID-19 on transport CO2 emissions. In the Chinese context, changes of carbon emissions associated with passenger and freight transport (including urban, rural, and inter-city transport) across different transport modes are estimated. Scenario analysis is then used to estimate the impact of COVID-19 on total transport carbon emissions up to 2030. Four scenarios, from minimal to significant behavioural changes and global recession associated with COVID-19, are generated. Results: Under the pandemic, the transport system in China was estimated to have produced 28% less CO2 emissions (1044.2 Mt) in 2020, when compared to 2019. Compared with the business-as-usual scenario, the estimated total transport carbon emissions in 2030 would drop by 6%, 15%, and 21% and 23% under the minimal-impact, low-impact, moderate-impact, and severe-impact scenarios, respectively. Conclusions: The results suggest that the processes triggered by COVID-19 alone will not be sufficient to meet the ambitious transport decarbonisation targets. To meet China's pledge under the United Nations Framework on Climate Change, the medium-term effects of COVID-19 must be combined with strong transport decarbonisation measures of modal shift and new energy applications. With these additional measures, it may be possible to advance the transport carbon peak before 2030. Lessons are relevant to other developing countries. [ABSTRACT FROM AUTHOR]

Over the past years, transport mode recognition has become a large field of research. However, flight as a type of transportation has been mostly overlooked. A system for flight detection might be useful for context-aware applications, but more importantly, it can be used to automatically manage airplane mode on smartphones. Smartphones transmit radio frequency signals which could potentially interfere with aircraft systems, and it is therefore important that devices enable airplane mode to avoid this problem. This paper proposes flyDetect, a method for automatic flight mode detection and an embodiment in the form of an app that demonstrates the viability of the method. Thus, the system uses the accelerometer and barometer in an Android smartphone, can detect the start and end of a flight, and notify other apps or systems on the device when this happens. Our evaluation shows that flyDetect meets the requirements set for the solution, and the results are very promising. [ABSTRACT FROM AUTHOR]

Although children are the primary users of many spaces, their voices are often unheard in transport planning. We therefore do not know much about children’s barriers or wishes regarding mobility. What is known, however, is that children have become less independent in their daily mobility, with parents (or guardians) increasingly driving children instead of allowing them to walk and cycle. The decline in active mobility is worrisome, since active mobility is beneficial to children, but incorporating children’s voices in transport planning can be conducive to increased active mobility of children. The objective of this paper is to explore the wishes and barriers of children regarding school commuting. Data was collected from a survey completed by 1251 pupils and through workshops with four schools in a residential neighbourhood in Brussels, Belgium. We found that there is a significant gap between the current and desired transport modes of pupils, with an important untapped potential for cycling. We also found that traffic safety is a predominant worry of pupils. Additionally, when suggesting the re-design of their school neighbourhood, the most recurring suggestions from pupils included walking and cycling infrastructure, and reduced access to the school neighbourhood for cars. [ABSTRACT FROM AUTHOR]

Freshwater shortage is a growing problem. Inspired by the Sarracenia trichome fog-trapping and ultrafast water-transport structure, a series of hierarchical textured surfaces with high-low ribs with different wettabilities was prepared based on laser processing combined with dip modification. Through fog-collection performance tests, it was found that the samples with superhydrophobicity and low adhesion had the best fog-collection effect. In addition, it was observed that the fog-collection process of different microstructured samples was significantly different, and it was analysed that the fog-collection process was composed of two aspects: directional condensation and directional transport of droplets, which were affected by the low ribs number and rib height ratio. A design parameter was given to create the Sarracenia trichome-like structure to achieve a fast water transport mode. This study provides a good reference for the development and preparation of fog-collection surfaces. [ABSTRACT FROM AUTHOR]

Electric micromobility vehicles are becoming increasingly popular in urban transport because they can reduce the high dependency on cars as a means of passenger transport, which contributes to increased levels of air pollution and congestion in many cities and on major transport routes. While e-mobility alternatives reduce negative environmental impacts, some studies have shown that this depends on the mode of transport that users choose to change. While these sustainable means of transport have clear benefits, most European countries are still struggling to integrate electric scooters into the transport ecosystem. Given the difficulties with integration mentioned above, our exploratory research aimed to find out whether and to what extent there is a significant correlation between the place of living and the use of electric scooters. We also investigated whether the use of electric scooters is affected by the availability of other micromobility devices in the area. The results demonstrate that neither the location of living space nor the availability of other mobility devices significantly influences user decisions to use electric scooters. [ABSTRACT FROM AUTHOR]

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

Shared Autonomous Vehicles (SAV), or robotaxis, are expected to be commercially available within this decade. This new transport mode has the potential to revolutionize travel, offering a level of service comparable to traditional taxis with much lower prices. This may attract travelers currently using other modes, impacting the economic sustainability of public transport as well as car ownership levels. We investigate this potential demand using a scalable SAV simulation framework. We do not establish a future equilibrium considering the interaction between all users on a detailed road network, but establish the potential demand for a large metropolitan area. Travelers can choose between their current mode and the new SAV mode, with fare and waiting times which depend on real-time demand. For our input data we train a statistical model on a large transport survey from Germany for an urban region, allowing us to generate a large number of trips with realistic characteristics. We conduct a sensitivity analysis to study the effect of several key parameters on the modal shift. We find that SAVs can be attractive to many active mode and public transport users unless regulations are put in place. Our results also show that due to SAV fleet constraints, changes in incentives for travelers currently using cars may have significant consequences on the behavior of other travelers. We further calculate key economic indicators for the fleet, which can inform the discussion on the fleet size and fare level that operators are likely to choose when maximizing their own profit. [ABSTRACT FROM AUTHOR]

After the May 12 earthquake in Wenchuan, numerous debris flow disasters occurred due to heavy rainfall. After the earthquake, disaster prevention and mitigation projects, such as the sand dam, played an essential role in safety. However, when the outflow of solid material exceeds the designed storage capacity of the sand dam, the debris flow overtopping the dam intensifies the scraping effect on the source material of the gully channel. This paper takes the "8.20" debris flow in the Chutou gully as the research object. A transport mode of the debris flow after dam overtopping is studied through comprehensive field investigation, theoretical analysis, and indoor model tests. A quantitative evaluation model is established for the scraping depth and scraping volume of dam-overtopping debris flow. The study results showed that once the debris flow overtops a dam, the loose source carried by the channel is involved in the entire migration process, enlarging the fluid scale and intensifying the damage along the channel. The results agree with the measurements and observations, with maximum relative errors of 5.81% and 14.70%, respectively. This shows model validity. Furthermore, the test results show that the debris flow scarping phenomenon in the γ=[1.4 t/m3, 1.6 t/m3] interval is the most significant. Overall, this study will help improve future engineering decisions, design strategies, and finding the best design solutions to minimize the risk of dam-overtopping debris flow disasters. [ABSTRACT FROM AUTHOR]

COVID-19 altered travel patterns in the U.S. Studies have analyzed the effect of the pandemic on travel mode, including working from home, but few have focused on automobile ownership—a relationship with potentially long-term consequences for accessibility, household budgets and debt, and policy efforts to meet climate goals. To understand the association between the pandemic and automobile ownership, we rely on a unique credit panel dataset from Experian and examine three different automobile loan-related outcome measures: annualized growth rate of new automobile loan balances, average new loan size, and the number of new loans. We focus specifically on changes across loans in neighborhoods by race/ethnicity, hypothesizing larger increases in automobile debt in Black and Latino/a neighborhoods, where workers are less likely to be able to telework. The annualized growth rate of new automobile loans increased during the pandemic across all neighborhoods by race/ethnicity, increasing most rapidly in Latino/a neighborhoods. Controlling for other factors, loan size increased similarly across neighborhoods by race/ethnicity. The increase in automobile lending in Latino/a neighborhoods, therefore, likely was explained by a significant uptick in the number of new loans. The growth in automobile lending during the pandemic was potentially prompted by pandemic-induced changes in the need for automobiles and facilitated by an expanded social safety net. As the pandemic and its various forms of public financial assistance recede, the findings underscore the importance of ongoing assistance in enabling automobile ownership or shared access among households with limited means whose livelihoods depend on the access that vehicles provide. • Annualized growth rates of new automobile loans increased during the COVID-19 pandemic across all neighborhoods. • Annualized growth rates of new automobile loans increased most rapidly in Latino/a neighborhoods. • New automobile loan size increased similarly across neighborhoods by race/ethnicity. • The increase in lending in Latino/a neighborhoods likely was due to a significant uptick in the number of new loans. • Policies should enable automobile ownership or shared access among poor households whose livelihoods depend on this access. [ABSTRACT FROM AUTHOR]

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

Tourism is a major source of income for many regions; however, its impacts on residents' daily lives are significant, especially regarding their travel behavior. Local transportation infrastructure is challenged by large tourist flows, and thus residents need to adapt to the new environment by changing their usual habits, such as travel mode, frequency, destination etc. In this study, a multinomial logistic regression mode choice model is developed to capture tourism impacts on residents' travel behavior, using data from the island of Rhodes, Greece. According to study findings, tourism has in fact an impact on residents' travel mode preferences, as they tend to opt for more agile modes such as motorcycles, instead of cars, and adopt defensive driving during tourist seasons. This study can facilitate public transport operators, planners, and municipalities in tourist regions, to apply effective policies to mitigate negative impacts of tourism in local traffic conditions. [ABSTRACT FROM AUTHOR]

Despite many years of research and rapid changes in the field of bicycle route choice modelling, a review of factors associated with cyclists' route choice decisions is missing. This paper reviews 33 studies that employed GPS data and statistical modelling to explain the route choice behaviour of cyclists on utilitarian trips. Factors associated with bicycle route choice are divided into network, contextual, and individual factors. Findings from this review demonstrate that a refined categorisation of model attributes is essential, as the preferences vary greatly between different route attributes. Moreover, the analysis indicates a strong influence of the local context on the attribute definitions and route choice preferences. Although some commonalities between studies w.r.t. the network factors (e.g. a preference towards bicycle infrastructure or avoidance of slopes) can be determined, many results are contradictory or intertwined with other factors. Specifically, results related to intersections, land use characteristics, and interaction with other modes of transport are not always conclusive and are strongly dependent on the local context. However, the explanation of some of the unclear effects can be facilitated by incorporating contextual or individual information in the models. Based on the analysis of the existing studies, this review encourages a joint consideration of studies employing quantitative and qualitative methods to explain cyclists' behaviour. Moreover, reporting model results in an accessible form (e.g. through relatable values or visualisation) is essential to build bridges between bicycle research and policymaking. Future research is encouraged to study cyclists' route choice decisions from the perspective of objective well-being, quantifying and modelling the influence of factors such as safety, health, energy expenditure, or noise exposure. [ABSTRACT FROM AUTHOR]

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The high-quality development of the Yellow River Basin is still facing the issue of imbalance and inadequacy, and it urgently requires the backing and assistance of a well-coordinated and efficient comprehensive transportation network system. Based on this purpose, this study uses a composite system synergy degree model incorporating "mode dimension + regional dimension" to analyze the evolution of this network. The results indicate the following: (1) Railway and air transportation surpass highway transportation in growth and synergy, though overall system synergy is still low. (2) Downstream areas are gradually taking the lead, and the orderliness of each subsystem is gradually becoming consistent. The complexity and variability of the composite system's synergy are high, with an overall low level of synergy. Overall, despite improvements in service capacity and quality, better integration of different transport modes and enhanced cross-regional cooperation are needed. This study reveals and analyzes in depth the complexity of the comprehensive transportation network system in the Yellow River Basin and its spatiotemporal characteristics of synergistic evolution. We propose suggestions for high-quality development at national, regional, and industry levels, fostering the continuous improvement of the system structure, which aids in overcoming the tangible obstacles faced by the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The average daily throughput of large-scale passenger high-speed railway stations is large, and the design of the inbound space connecting with the underground and other modes of transport affects the passengers' wayfinding behaviour and time spent, which in turn affects the efficiency of the inbound station. How to optimise the design of station entry space and signage arrangement becomes the key to shortening the station entry time. In this paper, eye tracking, spatial syntax, and semantic difference methods are used to evaluate the passenger's wayfinding process in the underground hub of a large high-speed railway station and the spatial syntax is used to quantify and analyse the wayfinding path segments, to explore the influence of the spatial attributes of different nodes and the spatial arrangement of the guiding signs on the passenger's wayfinding behaviour data and the difference in attention, and to find out that the connectivity of the wayfinding nodes, the area of the field of view, and the passengers' The study concludes that the connectivity and visual field area of wayfinding nodes have a strong positive correlation with the passengers' route choice time, which has less influence on the correct rate of wayfinding and can be taken into less consideration in the subsequent design. While analysing the spatial density of signs and the correct rate of wayfinding in the sample, it is concluded that the density of guide signs is maintained in the interval of 5–11‰, and at the same time, the number is sufficient to point to the destination is a more appropriate interval, and ultimately, the impact of the correct rate of wayfinding of the weighting of the following: signage focus on the time > density of information > density of key information > diameter of the pupil. The study analyses the influencing factors affecting passengers' wayfinding behaviour from a human factors perspective and provides feedback on the design of underground entry spaces in large passenger high-speed rail stations. [ABSTRACT FROM AUTHOR]

The predictors of urban trip mode choice and one of its important components, public transit ridership, have still not been thoroughly investigated using case studies in Central Europe. Therefore, this study attempts to clarify the correlates of mode choices for commute travel and shopping, and entertainment travel to distant places, as well as the frequencies of public transit use of university students, using a wide range of explanatory variables covering individual, household, and socio-economic attributes as well as their perceptions, mobility, and the nearby built environment. The correlation hypothesis of these factors, especially the role of the street network, was tested by collecting the data from 1288 university students in Krakow and developing Binary Logistic and Ordinal Probit models. The results show that gender, age, car ownership, main daily activity, possession of a driving license, gross monthly income, duration of living in the current home, daily shopping area, sense of belonging to the neighborhood, quality of social/recreational facilities of the neighborhood, and commuting distance can predict commute and non-commute mode choices, while gender, daily activity, financial dependence from the family, entertainment place, quality of social/recreational facilities, residential self-selection, number of commute trips, time living in the current home, and street connectivity around home are significantly correlated with public transit use. Some of these findings are somewhat different from those regarding university students in Western Europe or other high-income countries. These results can be used for policy making to reduce students' personal and household car use and increase sustainable modal share in Poland and similar neighboring countries. [ABSTRACT FROM AUTHOR]

The rise in private vehicle use causes traffic congestion on the road network and increases the social costs of the trips. Travel demand management (TDM) strategies are deployed to mitigate traffic congestion sustainably as these strategies spread travel needs in space and time by influencing individual travel behavior. Carpooling is a TDM measure used to decrease the use of single occupancy vehicles and promote shared mobility among travelers sharing the same origin-destination and following the same route. This study attempts to identify the correlations between the socioeconomic demographics of travelers and their carpooling potential considering the moral obligations. A questionnaire survey was conducted with the students of the University of Nizwa, Oman, and a total of 156 samples were collected. The results revealed a high interest of respondents in carpooling as a passenger as well as a driver. The respondent's moral obligations are high to carpool for the reduction in traffic congestion, air pollution, and energy consumption. The category analysis showed some differences in interests among different groups. The ordered regression analysis revealed that variables of gender, present travel mode, trip distance, car driving, and carpooling as passengers are significant in determining the moral obligations of the travelers. These results implicate that specific carpooling programs based on specific market segments have the potential for consideration and implementation. [ABSTRACT FROM AUTHOR]

To understand the dynamical and conformational properties of deformable active agents in porous media, we computationally investigate the dynamics of linear chains and rings made of active Brownian monomers. In porous media, flexible linear chains and rings always migrate smoothly and undergo activity-induced swelling. However, semiflexible linear chains though navigate smoothly, shrink at lower activities, followed by swelling at higher activities, while semiflexible rings exhibit a contrasting behavior. Semiflexible rings shrink, get trapped at lower activities, and escape at higher activities. This demonstrates how activity and topology interplay and control the structure and dynamics of linear chains and rings in porous media. We envision that our study will shed light on understanding the mode of transport of shape-changing active agents in porous media. [ABSTRACT FROM AUTHOR]

Background: Active commuting to school (ACS) can be an important source of physical activity for children. Schools are an important setting for policy-related ACS promotion. The purpose of this study was to examine the association between school policies and ACS, and to assess whether this relation varied by grade. Methods: This cross-sectional study used data from schools recruited to the Safe Travel Environment Evaluation in Texas School study (n = 94). The percent of trips made by active travel modes was measured through tallies among third to fifth grade classrooms from 5 school districts in Central Texas in 2018–2019. School ACS policies and practices were measured through 8 survey items aggregated into a score. Linear mixed effects models were used to assess the association between policies and ACS. Results: School health policy surveys and ACS data were collected from 69 elementary schools. An average of 14.6% of trips to/from school was made using active travel modes. Schools with higher numbers of policies had significantly higher percentages of students using active travel modes (P =.03), and for each additional policy, the predicted percentage of trips made by active travel modes was 1.46% higher. There was a significant interaction effect between school policy and grade, with stronger correlations among higher grades (P =.002). Conclusions: Results from this study demonstrate a correlation between the school policies designed to support walking and biking and ACS. Results from this study can be used to justify the use of school-based policy interventions to promote ACS. [ABSTRACT FROM AUTHOR]

The urban space community is the basic unit used to demonstrate the urban spatial structure, and the space community structure of island-oriented cities is different from that of general inland cities because they are formed based on the island and the inland, respectively. Through the case study of Xiamen, based on smart card data, this paper divides the obtained origin–destination data into local and global levels with trip cutoff thresholds. The distribution of city centers is analyzed by detecting the overall urban space community structure and the two-level intraisland and cross-island urban space community structure with the PageRank and community detection algorithms. The results revealed that: (1) in the spatial structure of the island-oriented city, the cores are clustered on the island, while the centers are distributed in bands and dots outside the island; (2) the community units are distributed across the island; and (3) the space community boundary of the island-oriented city is quite different from the artificially defined administrative unit boundary. To summarize, by enhancing the delineation of urban spatial communities using the Gaussian kernel function and least-squares cross-validation, improving the model granularity, and integrating data from multiple public transport modes, this paper achieved a more precise division of urban spatial community structures. Consequently, it revealed the distinctive urban form and developmental pattern of the island-oriented city, holding significant implications for investigating urban spatial layout studies. [ABSTRACT FROM AUTHOR]

In this paper we review the academic transportation literature published between 2014 and 2018 to evaluate where the field stands regarding the use and misuse of statistical significance in empirical analysis, with a focus on discrete choice models. Our results show that 39% of studies explained model results exclusively based on the sign of the coefficient, 67% of studies did not distinguish statistical significance from economic, policy or scientific significance in their conclusions, and none of the reviewed studies considered the statistical power of the tests. Based on these results we put forth a set of recommendations aimed at shifting the focus away from statistical significance towards proper and comprehensive assessment of effect magnitudes and other policy relevant quantities. [ABSTRACT FROM AUTHOR]

The issue of the effects of travel on subjective well-being (SWB) has recently attracted increasing interest in transport studies. A common finding is that travel affects SWB indirectly through out-of-home activities. However, little is known about how to operationalize this relationship. In this study, we proposed a conceptual model and estimated structural equation models relating travel mode use and activities with multiple SWB dimensions, including affective components (positive affect and negative affect) and cognitive components (belongingness, achievement, and confidence in coping). We used data from a national mobility project in Japan (N = 13,000) to estimate the postulated models. We found that while public transport use enhanced the cognitive components of SWB, it also had a negative effect on the affective components of SWB. Car use affected SWB in a more complex pattern; it promoted SWB by enabling leisure activities but also reduced SWB dimensions of belongingness and achievement through shopping activities. Active travel modes did not have a clear effect on SWB; for example, walking to school was associated with increased belongingness, whereas walking for shopping negatively influenced belongingness. Other contributing factors, such as COVID-19 worry, car access, and the 'going-out' problem-solving style, were also found to influence multiple dimensions of SWB. Overall, our study showed how the effects of activities on multiple dimensions of SWB varied with different travel modes, thereby revealing the indirect effect of travel mode use on SWB via activities. Suggestions for shaping transport policies towards SWB are also discussed. [ABSTRACT FROM AUTHOR]