City Travel Research Articles

Investigating the Multifaceted Impact of Urban Environment on Winter Green Travel in Cold Regions: An Empirical Study of Shenyang, China

Green travel offers significant benefits, including reducing pollution and alleviating traffic congestion. Despite these advantages, green travel is less popular in cold regions, particularly during winter, due to comfort, convenience, and safety concerns. While climate factors are immutable, enhancing the urban environment can promote winter green travel. This paper examines the impact of urban environments on residents’ willingness to engage in green travel in cities located in cold regions during winter. Using data from Shenyang, China, a comprehensive structural equation model based on the stimulus–organism–response (S-O-R) theory was constructed, revealing the causal relationships and underlying structure between environmental factors and green travel willingness. The model demonstrates that social, built, natural, and travel environments collectively shape residents’ willingness to engage in green travel, with the social environment emerging as the most impactful factor. Additionally, this study identified two crucial mediating variables, travel perception evaluation and attitude towards green travel, which indirectly influence green travel willingness. This study also identifies nine critical factors—often underappreciated in traditional analyses—that should be prioritised in urban planning. These findings advance the understanding of green travel behaviour in winter cities by illustrating the complex interplay between environmental factors and individual attitudes while providing actionable guidance for fostering supportive social environments and strategically enhancing built and travel environments to promote green travel in cold climates.

Analysis of Behaviour Pattern of Bicycle-sharing Users Based on Complex Network: a Case Study of Beijing Downtown Area

Abstract. The introduction of the Bicycle-sharing System (BSS) has provided great convenience for residents for short travel in city. However, the parking lot planning and bicycle logistics distribution remain suboptimal, adversely affecting traffic order. Studying the spatial and temporal usage patterns can be helpful for better management of BSS. In this paper, we propose an analytical framework for detecting the bicycle-sharing pattern based on the community detection algorithms from complex networks to study the spatial-temporal patterns of usage.Firstly we identify the potential demand for bicycle among urban residents with a dataset from the BSS in Beijing downtown area. Then we construct a linkage network for modelling the BSS by applying community detection algorithms to identify regions of both high and low connectivity. Following this, based on the division of sub-areas, three indicators (graph density, cross-area travel demand, and confidence ellipses) are established for characterizing these sub-areas. Our findings include: (1) The usage pattern of the BSS within the downtown area consistently exhibits relatively stable clustering phenomena over time. (2) The usage pattern is related to the urban spatial structure, with significant differences between weekdays and weekends. (3) Residents tend to complete their cycling within the current sub-areas. (4) Generally, smaller sub-areas tend to have denser bicycle travel behaviour. These insights are vital for improving BSS parking lot planning and logistics distribution.

Intelligent Traffic Control with Convolution Neural Networks

In cities across the globe growing populations and more cars on the roads have led to worst traffic jams. This causes delays, stress higher fuel use, and more air pollution, with big cities feeling the worst effects. There's an urgent need to check road traffic density in real-time to control signals and manage traffic better. Our Smart Traffic Management System uses Convolutional Neural Networks (CNNs) and CCTV cameras to tackle this issue. This new approach allows for exact traffic density calculations, which helps adjust traffic signals based on how many vehicles are present. As a result, it eases congestion, speeds up travel, and cuts down on pollution. By using CCTV Cameras adding Convolutional Neural Networks, and tapping into the strengths of Computer Vision, our solution has a big impact on city travel. [4].

Effectiveness of the Role of the Rokan Hulu Regency Transportation Service in Monitoring Illegal Travel in Pasir Pengaraian City

This research aims to find out how effective the role of the Rokan Hulu district transportation service is in monitoring illegal travel in the city of Pasir Pengaraian. This study used descriptive qualitative method. The indicators in this research are input, process, output and outcome. This research was conducted at the Rokan Hulu Regency transportation service. Collecting data obtained through interviews, observation, documentation. The author's technique for determining informants uses the snowball sampling method. The snowball sampling method is a technique for taking data sources, initially the number is small and then becomes larger, this is because the few data sources are not able to provide satisfactory data, so look for other informants to use as data sources. Based on the research results, it can be concluded that the effectiveness of the role of the Rokan Hulu Regency Transportation Service in monitoring illegal travel in Pasir Pengaraian City is still not effective and optimal because what happens in the field in the monitoring process is only monitoring actions in routine operations and raids, but these activities are still rare. done. The inhibiting factors or obstacles for the Rokan Hulu district transportation service are that they are still careless in terms of supervision, lack of certainty and schedule in carrying out supervision, limited budget, lack of level of public awareness, and still difficulty for transport drivers in processing permits..

Understanding pedestrian movement using urban sensing technologies: the promise of audio-based sensors

While various sensors have been deployed to monitor vehicular flows, sensing pedestrian movement is still nascent. Yet walking is a significant mode of travel in many cities, especially those in Europe, Africa, and Asia. Understanding pedestrian volumes and flows is essential for designing safer and more attractive pedestrian infrastructure and for controlling periodic overcrowding. This study discusses a new approach to scale up urban sensing of people with the help of novel audio-based technology. It assesses the benefits and limitations of microphone-based sensors as compared to other forms of pedestrian sensing. A large-scale dataset called ASPED is presented, which includes high-quality audio recordings along with video recordings used for labeling the pedestrian count data. The baseline analyses highlight the promise of using audio sensors for pedestrian tracking, although algorithmic and technological improvements to make the sensors practically usable continue. This study also demonstrates how the data can be leveraged to predict pedestrian trajectories. Finally, it discusses the use cases and scenarios where audio-based pedestrian sensing can support better urban and transportation planning.

Set Moves: Constructions of Travel in Commercial Games for Children

During the long nineteenth century, Western publics experienced the invention and proliferation of commercial games for children. Card games, board games, and other parlor games were no longer for adults only; these new offerings formalized some aspects of what it meant for a child to engage in play. Many games centered travel, becoming sites for children to simulate adult agency in movement through space. This paper examines the stories told by narrative card games and board games about travel, especially travel within and between urban centers. The games present the city as microcosm of the world. Child players are invited to construct multiple national and ethnic identities as they pretend to be city travelers. The games attempt to teach children, and their caregivers, how to travel. I argue that the structures and aims of the games evolve over time, keeping pace with new mores surrounding work and leisure travel. I also argue for connections between games and the “set moves” of narrative fiction and theatre.

An Evaluation and Prioritization Framework for Pilot First- and Last-Mile Ridesharing Services

Ridesharing is part of the innovative shared transport regime which aims to maximize the utilization of mobility resources. Gaining knowledge of ridesharing’s impacts and how to assess them can significantly improve such services and thus contribute to their adoption among broader groups of travelers and to travel behavior change. This paper presents the framework deployed for assessing the impacts of a first-/last-mile ridesharing pilot in Athens, Greece, and capturing stakeholders’ (i.e., a researcher organization, a public authority and an infrastructure provider) point of view about planning objectives. Four impact areas are defined in total, and Key Performance Indicators (KPIs) are used. In parallel, in order to understand the stakeholder priorities when designing ridesharing services, the Analytical Hierarchical Process is implemented to estimate weights for each impact area. Increasing rail ridership is considered the top priority for all stakeholders during the planning phase for a first-/last-mile ridesharing service, which may have various implications for future initiatives. In total, 28 participants used the ridesharing service as drivers and passengers during the demonstration period. Results show that although a ridesharing service is expected to be an asset in daily transport for city travelers, the technological constraints currently burden its usage. However, as supported by demo results and travelers’ experience, there is great potential of ridesharing to contribute to a sustainable transport system and serve as a first- and last-mile solution to public transport.

Transport Object Detection in Street View Imagery Using Decomposed Convolutional Neural Networks

Deep learning has achieved great successes in performing many visual recognition tasks, including object detection. Nevertheless, existing deep networks are computationally expensive and memory intensive, hindering their deployment in resource-constrained environments, such as mobile or embedded devices that are widely used by city travellers. Recently, estimating city-level travel patterns using street imagery has been shown to be a potentially valid way according to a case study with Google Street View (GSV), addressing a critical challenge in transport object detection. This paper presents a compressed deep network using tensor decomposition to detect transport objects in GSV images, which is sustainable and eco-friendly. In particular, a new dataset named Transport Mode Share-Tokyo (TMS-Tokyo) is created to serve the public for transport object detection. This is based on the selection and filtering of 32,555 acquired images that involve 50,827 visible transport objects (including cars, pedestrians, buses, trucks, motors, vans, cyclists and parked bicycles) from the GSV imagery of Tokyo. Then a compressed convolutional neural network (termed SVDet) is proposed for street view object detection via tensor train decomposition on a given baseline detector. The method proposed herein yields a mean average precision (mAP) of 77.6% on the newly introduced dataset, TMS-Tokyo, necessitating just 17.29 M parameters and a computational capacity of 16.52 G FLOPs. As such, it markedly surpasses the performance of existing state-of-the-art methods documented in the literature.

A Spatial-Temporal Graph Convolutional Recurrent Network for Transportation Flow Estimation.

Accurate estimation of transportation flow is a challenging task in Intelligent Transportation Systems (ITS). Transporting data with dynamic spatial-temporal dependencies elevates transportation flow forecasting to a significant issue for operational planning, managing passenger flow, and arranging for individual travel in a smart city. The task is challenging due to the composite spatial dependency on transportation networks and the non-linear temporal dynamics with mobility conditions changing over time. To address these challenges, we propose a Spatial-Temporal Graph Convolutional Recurrent Network (ST-GCRN) that learns from both the spatial stations network data and time series of historical mobility changes in order to estimate transportation flow at a future time. The model is based on Graph Convolutional Networks (GCN) and Long Short-Term Memory (LSTM) in order to further improve the accuracy of transportation flow estimation. Extensive experiments on two real-world datasets of transportation flow, New York bike-sharing system and Hangzhou metro system, prove the effectiveness of the proposed model. Compared to the current state-of-the-art baselines, it decreases the estimation error by 98% in the metro system and 63% in the bike-sharing system.

15-min Cities: the Potential of a Medium-Sized Polycentric Latin American City.

Urban sustainability and sustainable mobility have become the central focus of sustainable development initiatives. The city of 15 models seeks to ensure that urban development is sustainable. This paper evaluates the current state of mobility and the use of sustainable transport in the specific context of the city of Antofagasta, which, due to its characteristics of urban expansion and its mining activity, has been considered an international reference case. In particular, we study how the current urban structure shapes the city's travel patterns and identify opportunities for public policy actions to focus their investment and urban intervention efforts on the essential aspects that make it possible to achieve 15- or 20-min territories. The results reveal the need for urban development initiatives to focus on improving the supply of goods and services in areas with low installed capacity, promoting the culture of micro-neighbourhoods, and encouraging cycling. In particular, only 10% of trips, for all purposes and all modes of transport, are completed in less than 15min. And about 58% of trips, for all purposes and all modes, are completed in less than 30min. In the marginal effects of the multinomial logit model, a one-unit increase in travel time increases the probability of choosing to travel by public transport by 63% and decreases the probability of walking by 41%.

A mode shift Bayesian network model for active travel demand management policies

Promotion of mode shift from private to public transportation is one of the difficult tasks in modern travel demand management (TDM) especially for travelers in auto-dependent cities. This study investigates the role and impact of two active travel demand policies, i.e. incentive program and info-mobility system, on encouraging mode shift to public transportation with a questionnaire survey. The incentive program provides monetary or other form of incentives to encourage travelers to alter their travel behavior spatially or temporally. The info-mobility system refers to the use of information technology to disseminate real time travel information to travelers. A total of 670 respondents are surveyed in the Klang Valley region, Malaysia. Bayesian Network Modeling (BNM) is adopted as the analysis tool to predict the traveler mode shift intention. The developed model, termed as Mode Shift Bayesian Network Model (MSBaysnet), shows that: (1) the presence of an incentive program could change travelers’ perceived convenience of using public transportation, especially if they stay in the vicinity of public transportation stations; (2) the info-mobility system should be considered as a crucial component of an integrated public transportation system; (3) Bayesian Network has an advantage in modeling complex interactions of multiple TDM strategies; (4) no standalone TDM strategy works in promoting mode shift intention and synergistic effect of multiple policies is required to encourage mode shift. The findings derived from this study can aid policy maker in formulating useful mode shift strategies to improve public transportation ridership.

Sustainable transport modes, travel satisfaction, and emotions: Evidence from car-dependent compact cities

This study investigates how the use of sustainable transport modes relates to travel satisfaction (general evaluation of travel) and travel affect (emotions during travel) in car-dependent compact cities. Thereby, the study provides evidence on sustainable mobility and travel-related well-being in a context of compact urban form but inadequate provisions for public transport, walking, and cycling. A mixed-methods approach was applied comprising quantitative and qualitative analyses of data from the two major cities of Greece, i.e., Athens and Thessaloniki. Travel satisfaction and travel affect are found to be highest for those who walk for commuting, independently of travel time and other factors. Conversely, travel satisfaction and travel affect are lowest for public transport users, largely due to very long travel times but also poor public transport services in one of the two cities. Results indicate that the experience of traveling by public transport, car, and motorcycle within urban areas greatly depends on transport provision and policies. Overall, findings support the idea that to shift to pleasant, satisfying, and sustainable mobility in car-dependent compact cities, car restrictions should be accompanied by massive improvements in public transport, high-quality walking and cycling infrastructure, and an integrated coordination of different modes.

An Examination of the Land Use Determinants of Travel: A Case Study of Calicut City in India

Several travel studies focus mainly on mode shifting. Again, most travel studies have focused on mandatory trips. But the influence of land use on travel is rarely verified in all these studies. This paper examines the influence of land use measures on travel in a medium-sized city, India. The travel characteristics like number of trips, person-km and person-hr of travel by various modes and for various purposes are analysed separately. Land use is characterised by population density, employment density, land use intensity, land use mix and accessibility. During the modelling process, the explanatory variables are subjected to transformation to get over the nonlinearity issue. Statistical analysis reveals that a balanced mix of various land use activities causes people to travel less by any mode and for any purpose. Such studies can help the city planners formulate effective transport policies to improve the quality of transport within the city.

FORENSIC-MEDICAL EVALUATION OF INJURIES RECEIVED DURING OPERATION OF PERSONAL MOBILITY DEVICES: THE STATE OF THE PROBLEM (REVIEW)

The article analyzes literature data on modern aspects of traffic injury. Some factor criteria for traffic injury are singled out and identified how they have changed with the modernization of modern vehicles. Тhe data concerning injuries associated with the use of modern personal mobility devices, such as kick-scooters, electric scooters, electric unicycles, electric hover boards, skateboards, roller skates and similar devices were analyzed. Prospects for studying this problem and its value for modern forensic traumatology are outlined. Traffic injury is one of the most common problems today, as it is one of the main causes of death of the young population and ranks first among the causes of death due to injury. In particular, on the territory of Ukraine, the number of killed in car accidents each year reaches 400,000. Тhis scientific research was carried out with the aim of conducting an analysis of literary assets on the problem of studying car injuries associated with the operation of modern electric means of personal mobility. Due to new technological features of modern vehicles, the appearance of new types of transportation facilities, such as kick-scooters, electric scooters, electric unicycles, electric hover boards, skateboards, roller skates and similar devices, except for traditional issues, answers to which are widely covered in the fundamental works of the last century, new questions are posed to the experts, conditioned new, previously undescribed signs of traffic injury the requirements to the level of the scientific validity of the expert's conclusions are growing, which require appropriate methods of expert research. However, despite the full range of data provided, the problem associated with the study of injuries received on kick-scooters, electric scooters, electric unicycles, electric hover boards, skateboards, roller skates and similar devices is little studied. This type of vehicle was first introduced in November 2017 and become quite common today. The main task of this type of vehicle is to facilitate travel in large cities. Despite the ease and accessibility of operation, this type of transport is quite fast and can pose a danger to drivers and other road users. Therefore, forensic experts received new challenges today related to the study of the complex of injuries in drivers and pedestrians resulting from the operation of electric scooters, the mechanism of their formation, the study of signs of characteristic injuries to the driver and pedestrians’ data. However, despite all the work done, its results in most cases are statistical in nature and do not provide a comprehensive picture of the mechanism of injury and forensic-medical evaluation of the consequences of injury. There is also an open question related to the study of the characteristic’s injuries of drivers and pedestrians, the establishment of differential traumatic criteria specific to the driver and pedestrians. There is also an open question related to the study of the feature of injuries and establishment of differential traumatic criteria specific to drivers and pedestrians. Despite the availability of literature on this issue, the rapid spread of personal mobility devices on the roads, as well as the increasing number of related injuries, initiates the arising of new expert tasks that arise during forensic-medical examinations of this injury and outlines new prospects for studying this problem in the context of forensic medicine.

Conceptual Framework of Event Management in Tourism

Events in tourism are often seen as image builders related to destination profile, market positioning and providing a competitive marketing advantage. In addition to their spending on the event, external visitors are likely to spend money on travel, accommodation, goods and services in the host city or region, which is a major benefit of event organizing and a sought-after effect of tourism entrepreneurs. All these positive effects require choosing the right approach in the management of tourist events. The publication aims to develop the conceptual framework of event management in tourism. In this regard, the peculiarities of the event management and manager's activity are explained and guidelines for strategic development are proposed.

Strategic Intelligence and its Impact on Development of Tourist Guide: An Analytical Study for Opinions of a Sample of Managers at Travel and Tourism Companies in City of Baghdad

Both of researchers aim through the research to clarify the relationship between Strategic Intelligence and its impact on Development of Tour Guide , invest research in the tourism companies active in the tourism sector to show the added value achieved by the tour guide in the companies surveyed, and to identify the extent to which the criteria for developing the skills of the tour guide are implemented by the surveyed community, The researchers started with a major problem represented by the limited ability of these companies to provide long-term plans for the development of their tour guides, and the research came to determine the relationship and impact between strategic intelligence as an independent variable and its impact on the development of the tour guide as a dependent variable. Research and answering questions and testing the validity of hypotheses, the analytical descriptive approach was adopted as a scientific methodology in the current research, and the research was adopted on the basis of (questionnaire), which is the main tool for data collection and personal interviews, so the research included analyzing the opinions of a sample of some company managers Tourism and travel in the city of Baghdad by (210) a questionnaire distributed to all directors of tourism companies, and the use of a set of statistical measures and methods. Partnership and strategic alliances.

The effect of neighbourhood and urban center structures on active travel in small cities

Densification is the key intervention strategy proposed in the urban sustainability planning literature. Nevertheless, the blueprint for action is still vague, and especially so in small cities. Is, for example, the premise for and reward of densification relatively transferable between city scales? In addition, does difference in centre structures and distribution of facilities in small cities have an implication for active travel? By focusing on three Norwegian small cities, this paper addresses how built environment and attitudes influence active travel behaviour in small cities with different centre structures. Using descriptive statistics, ANOVA test and negative binomial regression on survey data, the paper finds that attitude towards active travel as well as accessibility significantly influence walk/bike trip frequency. Moreover, variation in small-city centre structure has an important implication for active travel but the effect varies between facility types. • Theoretical premise on the causal mechanism between urban form and travel behaviour in small city context is laid out. • City-scale built environment factors are strong predictors of average accessibility by active modes in small cities. • Attitude towards active modes strongly contributes to the propensity for active travel when alternative modes are available. • Distribution of facilities that optimizes active travel in a small city differs by facility categories.

Smart biking and traditional biking

Purpose: The purpose of this publication is to present the most important features with which the smart biking is characterized. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: Smart biking is a transformative approach that integrates modern technology and innovative solutions into urban transportation, revolutionizing cycling as a mode of travel in smart cities. By merging traditional cycling with cutting-edge advancements, smart biking enhances the overall cycling experience, focusing on safety, connectivity, and community engagement. This concept aligns seamlessly with the core principles of smart cities, emphasizing data-driven planning, environmental sustainability, and seamless integration with public transportation to create a bike-friendly urban environment. The development of dedicated bike lanes, cycle tracks, and bike-sharing systems showcases the smart city's commitment to improving cycling infrastructure and encouraging its adoption as a preferred mode of transportation. By providing real-time information and mobile apps, smart biking empowers cyclists to efficiently plan their routes, while advanced safety features and IoT technology enhance cyclist safety on the roads. Furthermore, smart biking fosters a sense of community among cyclists through social platforms, promoting an active and engaged cycling community. Originality/value: Detailed analysis of all subjects related to the problems connected with the smart biking in smart city. Keywords: smart biking, smart city, quality of life, biking, smart mobility. Category of the paper: literature review.

Active travel and paratransit use in African cities: Mixed-method systematic review and meta-ethnography

Active travel, as a key form of physical activity, can help offset noncommunicable diseases as rapidly urbanising countries undergo epidemiological transition. In Africa a human mobility transition is underway as cities sprawl and motorization rises and preserving active travel modes (walking, cycling and public transport) is important for public health. Across the continent, public transport is dominated by paratransit, privately owned informal modes serving the general public. We reviewed the literature on active travel and paratransit in African cities, published from January 2008 to January 2019. We included 19 quantitative, 14 mixed-method and 8 qualitative studies (n = 41), narratively synthesizing the quantitative data and meta-ethnographically analysing the qualitative data. Integrated findings showed that walking was high, cycling was low and paratransit was a critical mobility option for poor peripheral residents facing long livelihood-generation journeys. As an indigenous solution to dysfunctional mobility systems shaped by colonial and apartheid legacies it was an effective connector, penetrating areas unserved by formal public transport and helping break cycles of poverty. From a public health perspective, it preserved active travel by reducing mode-shifting to private vehicles. Yet many city authorities viewed it as rogue, out of keeping with the ‘ideal modern city’, adopting official anti-paratransit stances without necessarily considering the contribution of active travel to public health. The studies varied in quality and showed uneven geographic representation, with data from Central and Northern Africa especially sparse; notably, there was a high prevalence of non-local authors and out-of-country funding. Nevertheless, drawing together a rich cross-disciplinary set of studies spanning over a decade, the review expands the literature at the intersection of transport and health with its novel focus on paratransit as a key active travel mode in African cities. Further innovative research could improve paratransit's legibility for policymakers and practitioners, fostering its inclusion in integrated transport plans.

Toward a Healthy Urban Living Environment: Assessing 15-Minute Green-Blue Space Accessibility

Exposure to green-blue space has been shown to be associated with better physical and mental health outcomes. The advent of COVID-19 has underlined the importance for people to have access to green-blue spaces in proximity to their residences due to pandemic-related restrictions on activity space. The implementation of the 15-min concept, which advocates that people should be able to reach locations of essential functions like green-blue spaces within 15 min of active travel, can bring green-blue spaces nearer to where people live. Nonetheless, there is still a lack of understanding of the social and spatial (in)equality in 15-min green-blue space accessibility by active travel in cities seeking to embrace the concept, such as Hong Kong. This study explores 15-min green-blue space accessibility by walking and cycling in Hong Kong to reveal the distribution of disadvantaged neighborhoods. The results show that neighborhoods in Kowloon’s districts are the most disadvantaged in accessing green-blue spaces within 15 min of active travel. Our study provides policymakers with valuable insights and knowledge conducive to formulating policies aimed at reducing inequality in 15-min accessibility.