Search Results (192)

Autonomous vehicles (AVs) have emerged as a promising sustainable urban mobility solution, expected to lead to enhanced road safety, smoother traffic flows, less traffic congestion, improved accessibility, better energy utilization and environmental performance, as well as more efficient passenger and freight transportation, in terms of time and cost, due to better fleet management and platooning. However, challenges also arise, mostly related to data privacy, security and cyber-security, high acquisition and infrastructure costs, accident liability, even possible increased traffic congestion and air pollution due to induced travel demand. This paper presents the results of a survey conducted among 654 residents who experienced an autonomous bus (AB) service in the city of Trikala, Greece, in order to assess their willingness to use (WTU) and willingness to pay (WTP) for ABs, through testing a range of factors based on a literature review. Results useful to policy-makers were extracted, such as that the intention to use ABs was mostly shaped by psychological factors (e.g., users’ perceptions of usefulness and safety, and trust in the service provider), while WTU seemed to be positively affected by previous experience in using ABs. In contrast, sociodemographic factors were found to have very little effect on the intention to use ABs, while apart from personal utility, users’ perceptions of how autonomous driving will improve the overall life standards in the study area also mattered. Full article

Analyses of student mobility are typically conducted in an urban environment and are informed by socio-demographic or trip attributes. The prevailing focus is on individual modes of transport, different groups of commuters travelling to campus, students’ behavioural perceptions, and the totality of student trips. This paper starts with the identification of the determinants of student mobility that have received insufficient research attention. Utilising surveys, the study captures the mobility patterns of a sample of 1014 students and calculates their carbon footprint (CF; in kg/academic year) to assess whether the factors neglected in previous studies influence differences in the actual environmental load of student commuting. A regression analysis is employed to ascertain the significance of these factors as predictors of sustainable student mobility. This study exclusively focuses on the group of student commuters to campus and analyses the trips associated with compulsory activities at a suburban campus that is distant from the university centre and student facilities, which changes the mobility context in terms of commuting options. The under-researched factors identified in this research have not yet been quantified as CF. The findings confirm that only some of the factors neglected in previous research are statistically significant predictors of the local environmental load of student mobility. Specifically, variables such as student employment, frequency of class attendance, and propensity for ride-sharing could be utilised to forecast and regulate students’ mobility towards more sustainable patterns. However, all of the under-researched factors (including household size, region of origin (i.e., past experiences), residing at term-time accommodation while studying, and the availability of a family car) have an influence on the differences in CF magnitude in the studied campus. Full article

In the context of promoting sustainable mobility, walking and cycling have been widely recognized for their environmental and health benefits. However, a notable gap often exists between residents’ motivation to engage in these modes and their actual behavior. This study focuses on this motivation–behavior discrepancy and explores how heterogeneous information interventions—within the constraints of the existing built environment—can effectively influence residents’ travel psychology and behavior. Drawing on Protection Motivation Theory, this study aims to uncover the psychological mechanisms behind travel-mode choices and quantify the relative impacts of different types of information interventions. A travel survey was conducted in Yangzhou, China, collecting data from 1052 residents. Cluster analysis was performed using travel psychology data to categorize travel motivations and examine their alignment with actual travel behavior. A random forest model was then employed to assess the effects of individual attributes, travel characteristics, and information intervention attributes on the choice of walking and cycling. The results reveal a significant motivation–behavior gap: while 76% of surveyed residents expressed motivation to walk or cycle, only 30% actually adopted these modes. Based on this, further research shows that informational attributes exhibit a stronger effect in terms of promoting walking and cycling behavior compared to individual attributes and travel characteristics. Among these, health-related information demonstrates the maximum efficacy in areas with well-developed infrastructure. Specifically, health-related information has a greater impact on cycling (21.4%), while environmental information exerts a stronger influence on walking (7.31%). These findings suggest that leveraging information to promote walking and cycling should be more targeted. Full article

This study investigates the factors affecting the choice of school travel mode among students in Mersin, Türkiye, focusing on walking, private car, public transit and school bus. A two-step modeling approach was adopted. First, a latent class cluster analysis (LCCA) was applied to identify subgroups of students with similar characteristics. Then, separate multinomial logit (MNL) models were estimated for each cluster. The data come from the 2022 Urban Transport Master Plan household survey and include 2798 students from 2092 households. The results show that trip distance is the most consistent and significant factor across all clusters, as increasing distance makes students more likely to use motorized modes instead of walking. Gender also demonstrates a consistent influence in specific clusters, where male students are less likely to travel by private car. Similarly, residing in a single-family house consistently increases the likelihood of car use in multiple clusters. Conversely, the influence of household structure, parental education, income, and household size differs significantly between clusters, underlining the importance of considering group-level differences in school travel behavior. These findings suggest that policies aiming to promote sustainable school travel should be sensitive to the needs of different student groups. Integrating land use and transportation planning may help to support active and shared modes of travel. Full article

Background: The United States has the highest number of immigrants in the world, with over 46 million foreign-born residents as of 2022. A growing number of migrants originate from Latin America, driven by factors such as economic instability, food insecurity, and crime. This study explores their experiences and perceptions regarding trust in the criminal justice system (CJS) in both their home countries and the United States. Methods: This study surveyed 500 migrants at a transitional institution in a U.S.–Mexico border city in the summer of 2023. The survey assessed confidence in law enforcement, immigration officers, courts, and government institutions using a 5-point Likert scale. Results: Migrants reported significantly higher confidence in the U.S. CJS compared to that of their home countries. Multivariate analysis revealed that satisfaction with border officials, documentation status, English proficiency, and health were positively associated with confidence in the U.S. CJS, while employment status, traveling with family, and fear of crime correlated with lower confidence. Conclusions: This study highlights the stark contrast in migrants’ confidence levels between their home countries and the U.S. criminal justice system. While migrants view the U.S. system as more legitimate, challenges such as fear of crime and legal uncertainties persist. Full article

Rational parking allocation criteria are critical in addressing urban parking challenges and promoting the sustainable development of urban transportation. It has been common practice to reduce parking allocation for buildings according to the extent of the public transportation accessibility; however, the calculation of reduction coefficients lacks scientific rigor. This research proposes an estimation approach for reduction coefficients of parking allocation according to public transportation accessibility. First, public transportation accessibility is analyzed using Javier Gutiérrez’s weighted-average travel time model, optimizing the existing parking zoning scheme. Second, a multinomial logit model is built based on residents’ trip survey data to assess the cross-elasticity of the public transportation accessibility (travel time) with the probability of car travel. Third, the reduction in the private-car-travel probability is approximated as a parking reduction, and the reduction in the public transportation accessibility is translated to a reduction in the parking allotment, using cross-elasticity as a bridge. Finally, an empirical study is conducted on Nanjing’s central urban area, analyzing the reduction ratios within different parking zones around metro stations within specific distances and the interaction effects of these two scenarios to verify the rationality of the calculated reduction coefficients. According to the study, parking allocation standards in Zones I and II can be reduced by 10.6% and 7.5%, respectively, based on Zone III standards, while parking allocation standards within 100 m, 300 m, and 500 m of metro stations can be reduced by 17%, 12%, and 8%, respectively, based on the original standards. This paper can serve as a reference for the development of parking standard policies for public buildings. Full article

This study investigates the relationship between demographic factors and travel motivations among Generation Z leisure tourists through the lens of the Travel Career Pattern (TCP) theory. More specifically, the research focuses on how gender, age, and area of residence influence the travel motivations of Generation Z. Using a quantitative approach, data were collected from 303 respondents aged 18 to 28 through an online survey. The questionnaire assessed 14 motivational factors and analyzed them in relation to the participants’ demographic characteristics using linear regression models. Results indicate that gender and age significantly influence travel motivations, with women showing higher interest in personal development and social relationships, while men prioritize nature and adventure. Furthermore, rural residents exhibit greater motivation for autonomy, self-development and self-realization, while urban residents lean towards novelty and social interactions. The findings offer valuable insights for tourism marketers, emphasizing the importance of creating segmented marketing campaigns based on demographic factors. It also contributed to overcoming the lack of studies that specifically cover this interrelation between the motivational factors of Generation Z and the demographic factors of age, gender and area of residence. Nevertheless, this study also has limitations, such as the use of a non-representative sample and the focus on quantitative methods, suggesting that future research should adopt qualitative approaches and examine additional demographic variables to gain deeper insights into youth travel motivations. Full article

This study investigates the factors influencing urban residents’ interest in and visits to forests and explores strategies to promote forest space utilization. A survey was conducted among 5000 residents of Tokyo’s 23 wards, one of the world’s most densely populated urban areas, using an online questionnaire. The collected data were analyzed using least absolute shrinkage, selection operator (LASSO) logistic regression, and piecewise structural equation modeling (pSEM). The analysis revealed that nature experiences in current travel destinations, particularly scenic walks, had a significant positive effect on both forest interest (standardized path coefficient = 0.19) and forest visits (0.30). These experiences were also significantly influenced by childhood nature experiences and frequent local walks. Conversely, factors negatively affecting forest visits included the lack of private vehicle ownership (−0.13) and increasing age (−0.21). While previous studies suggest that older individuals tend to visit natural areas more frequently, our findings indicate the opposite trend. One possible explanation is the low car ownership rate among Tokyo residents, which may limit accessibility to forests. These findings provide valuable insights for policy design, particularly regarding strategies to enhance forest accessibility and engagement among urban populations. Full article

This study explores the driving factors of household energy consumption in high-density residential areas of Beijing and proposes targeted energy-saving strategies. Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. SHAP analysis revealed that key factors varied by season but included floor level, daily travel distance, building age, greening rate, water bodies, and household age. The findings inform strategies such as optimizing workplace–residence layout, improving building insulation, increasing green spaces, and promoting community energy-saving programs. This study provides refined data support for energy management in high-density residential areas, enhances the application of energy-saving technologies, and encourages low-carbon lifestyles. By effectively reducing energy consumption and carbon emissions during the operational phase of residential areas, it contributes to urban green development and China’s “dual carbon” goals. Full article

While extensive research has examined how major life events affect travel habits, less attention has been paid to the impact of minor environmental changes on commuting behavior, particularly regarding shared autonomous vehicles (SAVs). This study investigated how daily disruptions and incremental environmental changes influence commuter behavior patterns and SAV adoption in Shanghai, applying the theory of interpersonal behavior framework. The study surveyed 517 Shanghai residents, examining travel satisfaction, commuting habits, psychological factors (such as habit strength and satisfaction), and attitudes towards SAVs. Structural equation modeling was employed to test hypotheses about psychological factors influencing SAV adoption, while logistic regression analyzed how these factors affected mode choice across different disruption contexts. Analysis revealed that psychological factors, particularly habit and satisfaction, were stronger predictors of SAV adoption than attitude-based factors. Route obstructions and workplace relocations significantly increased SAV consideration. Even minor, recurring disruptions, such as construction zones, showed strong effects on commuting behavior, supporting the habit discontinuity hypothesis and emphasizing the importance of minor disruptions in driving behavioral change. The study extends the theory of interpersonal behavior by integrating habit discontinuity theory to explain how minor disruptions drive SAV adoption. This research provides actionable insights for urban planners and policymakers, recommending that SAV trials and targeted interventions be implemented during infrastructure changes or other commuting disruptions to promote SAV adoption and foster more sustainable transportation systems. Full article

Autonomous vehicles (AVs) and shared mobility constitute two of the “Three Revolutions” that portend major changes to surface transportation. AVs promise to reduce accidents, expand accessibility, and decrease congestion, while shared mobility provides the benefits of automotive transportation without requiring the purchase of a vehicle or the ability to drive it. Despite great promise to alleviate the negative externalities imposed by transportation, there remains much to be understood about the combined diffusion and impact of AVs and shared mobility. There is little demonstrated experience and application of AVs to the public, and how and where people would use automated shared mobility relative to their current travel is largely unknown. This study advances our understanding by utilizing an intercept survey of 232 respondents in Ann Arbor, Michigan who had made a discretionary trip to one of two central and two suburban locations. The novel approach of using intercept surveys allows us to gather more valid data about the willingness of respondents to replace the mode they just used for either a privately owned or a shared AV and do so for the trip purpose most conducive to using such a vehicle. We incorporate descriptive and spatial analyses and then utilize multinomial logit models to predict the factors influencing the encouragement or discouragement of substituting a private and a shared AV for their previous trip. We found that active mobility and transit trips work in competition with private AVs, while youth encourages interest. Meanwhile, active mobility, increasing age, and one of our measures of density discourage interest, while female respondents and the same measure of density increase interest. The results suggest that future efforts to facilitate the adoption of shared AVs target areas of the city that are relatively dense and residents in these areas where a shared AV would enhance individuals’ mobility. Full article

Individuals in social housing heavily depend on the surrounding infrastructure and services. There is a gap in understanding the needs of vulnerable groups regarding access to these resources. From the lens of spatial justice, we explored the specific needs of financially limited residents, considering affordability, service levels, and service quality. Surveying 660 individuals across 13 communities in Guangzhou, we firstly assessed the accessibility to facilities by using travel data. Subsequently, a principal component analysis revealed key factors influencing individuals’ satisfaction, including proximity to essential amenities, efficient service, high-quality education, affordability of commercial establishments, and access to healthcare services. While proximity to basic facilities achieves satisfaction, it falls short of ensuring fulfilment in healthcare, commerce, and education service quality. Satisfaction varies by community location and age, with newer communities, especially those established post-2010 in outlying areas, struggling to uphold spatial justice. Full article

Urban parks play a vital role in enhancing residents’ well-being, making it essential for decision-makers and designers to understand the factors influencing park satisfaction to improve park attributes. While existing studies primarily focus on internal park characteristics, this study investigates the diverse ways that external environmental factors influence park satisfaction. Using moderated regression models, we examined six factors, i.e., the quality of neighborhood compound greenspaces, perceived home–park distance, walking difficulty, the convenience of coordinating other trips, external environmental quality, and perceived travel safety, in Chongqing, China. Based on an intercept survey of 301 residents, five factors significantly impacted park satisfaction. Notably, the quality of compound greenspaces and trip coordination convenience were critical determinants, showing large correlations with satisfaction. Enhancing environmental quality and travel safety along access routes is also crucial, as they directly enhance satisfaction and moderate the impacts of internal park quality. Reducing walking difficulties can encourage frequent park visits and strengthen the relationship between internal park quality and satisfaction. Interestingly, the perceived home–park distance had minimal impact, likely because the parks studied were in close proximity to participants’ homes. These findings highlight the importance of holistically considering both internal and external factors in urban park planning and design. Future research should explore additional external factors in diverse urban contexts. Full article

The Hokuriku Shinkansen is among the five main Shinkansen lines in Japan. It starts from the capital, Tokyo, and passes through the Hokuriku region (Nagano City, Toyama City, and Kanazawa City) before reaching the Kansai region (Kyoto City and Osaka City). In Japan, the Hokuriku Shinkansen is being developed to increase the number of visitors in the area by shortening travel times and ensuring transportation networks in the event of a disaster; the Kanazawa–Tsuruga extension was opened on Saturday, 16 March 2024. The shortened travel times with this opening are expected to increase the number of visitors to the Hokuriku region and other regions, such as the Tokyo metropolitan area. The Tsuruga extension opening will connect the Hokuriku region with the Tokyo metropolitan area through direct service; however, travel between the Kansai and Chukyo regions will require transfers at Tsuruga Station, which would reduce convenience. Consequently, the flow of people in the Hokuriku region is expected to change significantly after spring 2024. Therefore, this study conducted a questionnaire survey of Kanazawa residents in Ishikawa Prefecture prior to the opening of the Tsuruga extension to analyze its effect on the choice of modes of transportation for travel to the Kansai region. The Hokuriku Shinkansen was found to be the most popular route for travel to the Kansai region after the opening of the Tsuruga extension, and the Hokuriku Shinkansen users prioritized comfort during travel and shorter travel times. Moreover, a high proportion of Hokuriku Shinkansen users were unemployed and received pensions, whereas a high proportion of private automobile users were students, housewives, or other people with no income. Full article

Wrocław is the most congestion-challenged city in Poland. Improving the appeal of public transport over private car use could be an effective remedy for the city’s notorious congestion problems. This article evaluates public transport service quality in Wrocław from the passengers’ perspective. The quality assessment focused on two key areas: the quality of service that passengers expect (preference evaluation) and the quality they perceive are delivered by the transport organiser and operator (satisfaction evaluation). Both passenger preferences and satisfaction were assessed based on 14 selected transport service attributes, referred to as quality attributes. To carry out this analysis, the Analytic Hierarchy Process (AHP) method and the SUTI Indicator 4 (Public Transport Quality and Reliability), which is part of the Sustainable Urban Transport Index (SUTI), were employed. Data were collected via a survey questionnaire with a sample of 500 bus and tram users in the city. Statistical analysis of the data were performed using functions and commands available in Microsoft Excel. The resulting SUTI Indicator 4 values (42.6% for bus services and 45.9% for tram services) suggest that Wrocław residents are moderately satisfied with the current public transport system. The study reveals that the transport organiser and operator should prioritise attributes related to travel time, as their fulfilment levels are shown to be either low or moderate. Therefore, in order to encourage more car users to switch to public transport in Wrocław, emphasis should be placed on solutions that ensure punctual departures and provide passengers with greater confidence in reaching their destinations on time. Full article