Journal of Transport Geography最新文献

In this paper, we propose a conceptual framework to elucidate transport-related social exclusion (TRSE) in rural China. Drawing from participant observations across 146 villages in Guangdong (2643 rural residents), we illuminate the multifaceted nature of TRSE in Chinese villages. In term of interregional transport challenges, rural residents are socially excluded due to inadequate transport infrastructure and services. In contrast, within the microcosm of intravillage transport, residents adeptly harness available transport resources to craft exclusionary strategies.

This emergent form of TRSE, distinct from previous paradigms, sees villagers deploying transport as an instrument to deliberately exclude the Other based on the depth and nuances of their interpersonal relationships. This exclusion manifests through unique characteristics: the nebulous contours of marginalised groups, mutual exclusion between rural residents, ethical ambivalence, and its profound resonance with traditional cultural norms. Given the intricate layers that seem to eclipse the phenomena observed in urban contexts, we underscore the imperative for a more nuanced exploration of TRSE in rural landscapes.

Transportation research on Latine migrant workers has increased in the past decade, revealing the difficulties that can arise for migrants who are often undocumented, isolated, and subject to unfair treatment at work. This study focuses on the transportation experiences and challenges of migrants from Latin America residing in the largely rural border state of Vermont. We conducted semi-structured interviews with Latine migrant workers to better understand their mobility and quality of life. We find that the legal landscape and resource access (including drivers' licenses, personal vehicles, and personal networks) are major contributors to rural migrant workers' mobility, which in turn contributes to quality of life. Difficulty accessing transportation was not strongly tied to financial resources, instead stemming from a lack of knowledge of transportation resources as well as legal and social contexts that prevent participants from feeling safe when leaving their homes. Driver privilege cards increased independence and mobility for many migrant workers interviewed, although some respondents shared that feelings of safety diminish the closer one gets to the U.S.-Canada border. All participants without a car and license reported paying for “raites” to get from one place to another. Our findings highlight the importance of individual transportation access for migrant workers living in a rural context. Expanding access to permissive driver's licensing laws and investing in organizations and programs that strengthen community ties and improve information dissemination (including native language options) are crucial to making mobility and community resources accessible to all migrants.

This study introduces a novel method for assessing spatial access to supermarkets in the United States, addressing limitations of the US Department of Agriculture Food Access Research Atlas definition. Our method eliminates the food desert poverty requirement and derives empirical time-based thresholds that reflect a nuanced urban/rural spectrum and regional differences in normative drive times. Using these thresholds, we identify more than 66 million individuals experiencing suboptimal food access, distributed across 30,011 census tracts. Travel time thresholds ranged from 2.93 to 7.17 min (sd = 1.09) in urban blocks, 5.86 to 19.21 min (sd = 1.93) in suburban blocks, 2.68 to 12.98 min (sd = 1.81) in large rural blocks, and 9.74 to 28.13 min (sd = 3.39) in small rural blocks. The shortest thresholds were found in urban centers around New York City, Chicago, and Los Angeles, while the longest were in sparsely populated regions of Northern California, the Southwest, and the Great Plains. Our approach represents a significant methodological advancement in food access research and can be applied to measure variation in geographical access to other community resources and services.

In the context of first/last mile, the bicycle-transit intermodality could lessen accessibility problems of stations and stops, reducing the need for feeder services. Although extensively addressed in developed countries, bicycle-transit is less studied in Global South metropolises, where distinct usage patterns are observed. Thus, this research aimed to model the choice behavior of the low-income population for bicycle-transit integration in Fortaleza - Brazil, a large Latin American city with a deployed bike-sharing system focused mainly on bike-bus integration. A Stated Preference (SP) survey was conducted addressing socioeconomic and trip characteristics, as well as policy variables such as bicycle parking and cycleways/lanes. SP data allowed the estimation of nested and mixed logit models representing choice behavior, and sample segmentation was used to identify heterogeneity among different groups of individuals. The results show that investing in bicycle infrastructure could stimulate bike-bus integration in Fortaleza; however, their relative importance depends on the analyzed individual strata. Findings also indicate the influence of public and road safety issues, as well as gender, income, and trip characteristics such as purpose and access distance.

This study explores the optimization of shared-bike station locations, emphasizing the cycling role in low-carbon mobility and local economic revitalization. A unique aspect of this research is the incorporation of the retail activity index in determining station locations, land-use mix, transit proximity, and population and employment densities. A novel weighting method, combining the multi-criteria decision method “Criteria Importance Through Inter-criteria Correlation (CRITIC)” with Ensemble-based predictive algorithms (Random Forest, XGBoost, Gradient Boosting), was developed to evaluate these factors. Using a geographic information system-based spatial model, this study conducted a suitability analysis by applying these weights to assess and propose bike station sites. The findings from the Seoul case indicate a balanced land-use mix, a low number of transactions linked to cyclists, and a significant gap in multimodal transport integration. The weighting results revealed a high priority for transit proximity and retail activity in station placement. Suitability scores across districts revealed significant variability, suggesting the need for greater integration of cycling policies into urban planning. High-scoring districts, such as Gangnam-gu and Seocho-gu, offer insights for improvements in less suitable areas. This study advocates expanded cycling planning, focusing on enhancing access to public transit and retail areas.

The scientific layout of child-friendly facilities in the community is of great significance to children's daily activities and healthy growth, which is also a vital concern of the United Nations. However, there is little evidence to prove the intrinsic mechanism of children's daily travel behavior and daily travel destinations. Therefore, this study takes 118 communities in Shuangliu District, Chengdu, as an example and uses a eXtreme Gradient Boosting (XGBoost) model to explore the non-linear effects and threshold effects of children's daily travel distance on their travel mode choices by considering different destinations of children's daily travel in the communities. We found that children's daily travel distances and destinations are vital for their travel mode choice, especially the most significant effect of travel distance. For different children's daily travel destinations, travel distance has a more substantial threshold effect on children's non-walking travel mode choice. Therefore, to scientifically and rationally distribute child-friendly facilities in the community, which may help children's healthy development, a child-friendly city should be planned, constructed, or renewed through the internal logical relationship between children's daily travel destinations, travel distances, and travel mode choices should be considered comprehensively.

Understanding bike usage patterns is essential for increasing bike demand, evaluating the effectiveness of bike facilities, and improving the quality of the bike system. This study aims to identify factors that influence bike usage for zone-based departure and arrival trips. It also seeks to address knowledge gaps by comparing private and dock-based public bikes, as well as use on weekdays and weekends. This study employed GPS trajectory data from 12,106 private bikes and 29,776 dock-based public bikes over one week in Seoul, South Korea. The dataset comprises zone-based physical characteristics and cycling patterns for 19,153 census zones. To tackle the problem of excessive zero values for bike demand in many zones, zero-inflated negative binomial models were employed for analysis. The findings suggested that realized detours, arising from natural barriers and a lack of infrastructure, are associated with a reduction in arrival trips on weekends but an increase in departure trips on weekdays. Behavioral detours, linked to route preferences, tended to decrease usage of public bikes on weekdays. Departure and arrival trips increased in districts with a higher level of mixed land use and larger commercial areas on weekdays. Moreover, bicyclists tended to prefer districts with longer separated bikeways, while bike usage was likely to decrease in districts with a high floating population and vehicle lanes. These findings provide valuable insights into cycling usage patterns and associated factors, encouraging more extensive use of bikes.

While there is a global shift to electric vehicles (EVs), few studies have comprehensively quantified the relative contribution of individuals' demographic characteristics, alternative transportation choices, and built environment (BE) attributes to EV ownership. Applying extreme gradient boosting decision trees to the 2020 regional household travel data in Wuhan, this study estimate the respective effects of these factors on EV ownership. The results emphasize the contribution of the BE and alternative travel options in predicting EV ownership and reveal a nonlinear relationship between variables. The distance to the city center, density and charging station facilities are identified as key factors influencing EV ownership. The study revealed a positive correlation between household ownership of conventional cars and EVs, indicating a tendency for households possessing conventional cars to acquire extra EVs, thereby transitioning into multi-car households. The findings also suggest that, in addition to the emissions reduction benefits, planners should be concerned about the potential urban issues that may result from vehicle electrification. The study provides empirical evidence for urban planners to inform policy interventions aimed at guiding the sustainable development of emerging mobility modes.

Against the backdrop of the strong market expansion of free-floating bikeshare systems (FFBS), the future of government-funded station-based bikeshare system (SBBS) is a matter of controversy. Merely relying on point density analysis proves to be inadequate in reflecting the flow characteristic, this paper employs a flow clustering analysis to investigate the relationship between SBBS and FFBS. To recognize both bikeshare flow clusters with inhomogeneous density and shape in less time, we propose a two-step network-constrained bivariate flow clustering method that organically combines multiplex-network community detection and bivariate flow clustering method. The performance and applicability of the method in flow clustering detection is exemplified by the SBBS and FFBS systems in Nanjing. The results indicate that though FFBS outnumbers SBBS in terms of bikes, there are still specific flow clusters where SBBS performs better. Spatiotemporal patterns of flow clusters reveal that about one-third of flow clusters dominated by FFBS move from the metro station to the business district during the morning peak, while more SBBS-dominated flow clusters (55.4%) move from the residence to the metro station. Conversely, during the evening peak, flow clusters are observed in the opposite direction. Nevertheless, if the difference in bike numbers is significant, SBBS will be at a disadvantage. It is necessary for SBBS to prioritize resource allocation towards target groups and advantageous areas to prevent decentralized development. Our findings contribute to a more profound comprehension of the interplay between SBBS and FFBS, thereby offering more informed recommendations for strategically aligning the functions of bikeshare systems.

The progression of shared mobility across Europe is remarkable. While station-based car and bike sharing have a more extended history, particularly in major European (capital) cities, recent advancements in modal types and operational models have significantly transformed the shared mobility landscape. Rapid expansion by private organisations has broadened access to shared mobility services across Europe. However, not all European cities are considered potentially viable markets due to local factors such as stringent regulatory frameworks and unfavourable economic conditions. The composition of the local offerings influences how citizens use these services, impacting travel behaviour and the local transport networks differently. Therefore, understanding the availability of various shared mobility schemes across Europe is essential for comprehending the market structure, its development, the providers' decision drivers, and the potential consequences for local transportation systems.

First, this paper presents data on various segments and features of the shared mobility market across European cities with more than 100.000 inhabitants. Second, two cluster approaches, i.e. k-means and latent class clustering analysis (LCCA), are conducted to structure this European market. Third, the contextual characteristics, such as socio-demographics, the built environment and the geography, are compared among the clusters using Dunn testing.

The results depict that the market is very fragmented, ranging from cities with a minimal offer (i.e. one type of modality available) to cities with a very competitive market consisting of numerous modalities and operators.

As expected, the most comprehensive offer of shared mobility is found in cities with the highest economic potential, measured by GDP per capita and population size. However, these cities tend to impose stricter regulations and invest in public schemes, especially for bike and car sharing, affecting the share of private operators. This may explain why private scooter sharing companies are willing to operate in smaller cities that initially seem to lack the economic conditions to accommodate a profitable sharing scheme. In cities where scooters are absent, mainly in Dutch cities, free-floating moped- and bike-sharing schemes have acted as a surrogate. Still, the comprehensiveness of the offer in these cities is considerable, suggesting that even with strict regulatory frameworks, other factors like infrastructure can create an attractive environment for operators. Overall, shared mobility is well-developed in European cities, meaning that many people are already aware of or have access to some form of shared mobility. This provides opportunities for other less-developed modalities, such as cargo bicycles, to further expand and offer specific use cases for car replacement. Therefore, future research could follow up on market developments to understand how various segments evolve an