Journal of Transport Geography最新文献

Evacuation after hurricane impacts appear (post-impact evacuation) has been underemphasized in empirical evacuation studies. This study uses well-examined factors for pre-impact evacuation and novel factors for post-impact evacuation in a sequential logit model for pre- and post-impact evacuation choices. Results show that the evacuation warning is the only factor that affected both pre-impact and post-impact evacuations. Demographics and housing characteristics are significant factors for pre-impact evacuation but not for post-impact evacuation, while residential damages and durations of utility outages are significant situational factors for post-impact evacuation. The durations of water and power outages had additive effects on the probability of evacuating after hurricane impact. Based on the results, we argue that the conventional assumption that sheltered-in-place residents will remain in the affected area, and the restoration planning and assistance generated with that premise will not be aligned with the demand of residents facing inhabitable living situations with damaged residences and prolonged utility outages. Agencies should consider extending the evacuation planning time horizon for storm events likely to induce severe damages and outages and prepare for evacuation during disrupted conditions.

Although much of the existing research on regional airports focuses on their contribution to regional economic development, regional airports in England, as in other deregulated markets, operate in a highly competitive market and not all have been able to sustain commercial flights. This paper examines the factors that have led to the cessation of commercial air services at English regional airports following liberalisation of the European air transport market in 1992. Six factors which have contributed to air service cessation are identified and potential futures for smaller regional airports discussed.

From a global perspective, climate change mitigation requires countries to consider Low-Carbon Development (LCD) policies, including “Low-Carbon Transport (LCT)” and decarbonization options, which should be ideally developed within a place-based scope. Due to the complex structure of the transportation sector, mitigation actions require not only technological but also behavioral shifts, which can be challenged by the existing legislative and socio-economic structure of a region. Therefore, it is essential to identify and assess barriers and opportunities (B&Os) as a necessary initial phase in the development of national mitigation strategies. Turkey voluntarily started climate change mitigation by preparing the legislative and political infrastructure as a part of the European Union Harmonization Process. Detection of B&Os in other dimensions required an in-depth evaluation of existing LCT barriers and instruments (B&Is) in the IPCC literature in terms of their applicability and priority for Turkey. A focus group study with transport sector representatives was conducted to evaluate 15 barriers and 19 instruments (proposing 285 B&I matrix combinations), followed by a brain-writing exercise that revealed 12 main barriers (i.e., a lack of measurable targets, an imbalanced modal split, a lack of institutional coordination and data archiving, etc.). Various opportunities have been identified, such as the increased utilization of Intelligent Transportation Systems and the timely adoption of vehicle and fuel technologies in the EU region. These opportunities would not only contribute to the development of a national climate change mitigation strategy but also facilitate the implementation of place-based action plans, including climate change action plans and sustainable urban mobility plans at the city level.

Severe weather events, such as snowfall, flooding and storms, may affect wide geographical areas and adversely impact discrete transport infrastructure networks (e.g. road, rail) at the same time, thus revealing the existence of geographic interdependencies between these networks. In this paper, we develop two accessibility-based measures to assess the impact of geographic interdependency on resilience based on the concepts of redundancy and substitutability, respectively. These measures are applied to the railway and long-distance bus networks in Scotland. Results reveal that the combined effect of redundancy and substitutability on the accessibility of locations offered by these discrete modes is reduced due to geographic interdependencies, with the extent of losses being positively associated with the spatial footprint of potential events. The results can be used to identify parts of the network where the potential impacts of geographic interdependencies are greatest, and thus require more in-depth scrutiny by network managers.

Although researchers and policymakers have proposed several ideas for improving the travel experiences of Persons with Disabilities (PWDs), they still face several barriers, especially in developing countries. This calls for a new sociological perspective aimed at contextualizing local disability policies and theories to create a disability-friendly society. This paper contextualizes the Ghana disability law through the lenses of Giddens' theory of structuration for the first time to understand the lived transportation barriers for PWDs. Questionnaire surveys involving 664 PWDs with physical, visual, auditory, and speaking impairments, key informant interviews, and field observations were triangulated. Results showed that all agents and structures, namely discrimination/facility managers' attitude, driver attitude, pedestrian behavior, design of facilities, and accessibility, are creating transportation barriers for PWDs in Ghana. Participants voiced exclusion from the design and implementation of transport facilities. Notably, discriminatory attitudes from commuters, drivers, and facility managers make PWDs feel marginalized. The lack of disability-friendly public buses/paratransit services and assistive technologies impedes PWDs' mobility to work, school, and health facilities. These findings show that although the Ghana disability law makes provisions for PWDs' mobility needs, there is weak enforcement. Thus, beyond improving infrastructure and access for PWDs, societal reorientation and enhanced enforcement of the laws are needed to foster empathy towards PWDs. The reorientation-based approach requires enhanced public sensitization, law enforcement, and regular consultation of PWDs in transport planning to improve the social order.

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications.

Regularity is typically defined based on the repetitive travel behavior of individuals, referring to how often travelers would utilize a specific service within a given spatio-temporal context. However, previous research on metro users' regularity primarily utilized basic metric, for example metro trip frequency, to measure regularity. What's more, metro smart card data typically encompasses time, spatial features, and card type information, lacking individual attributes such as age, gender, and type of residence, which limits in-depth analysis correlating individual attributes with travel behavior. The study obtained transit one-card data from Nanjing, China, which enabled us to extract metro user's travel and individual information. Thus, the entropy rate methodology was employed to measure metro users' regularity, while machine learning techniques were used to analyze non-linear effects of built environment, travel-related, and individual attributes on regularity. Results indicate that the built environment, travel-related, and individual attributes account for 66.66%, 33.31%, and 0.03% of the total relative importance, respectively. Two most influential variables impacting regularity, namely entertainment POIs at the origin level (17.77%) and weekdays (17.51%), belong to the built environment and travel-related attributes, respectively. In terms of individual attributes, age exhibits a greater impact on regularity compared to gender and type of residence, manifested in the variation of regularity among different age groups. This finding can assist metro policymakers in understanding metro users' travel behavior, aiming to enhance operational efficiency and optimize the user experience.

Transport and gender are intrinsically intertwined. However, traditionally, transport planning has tended to favor the travel needs of adult men in home-work trajectories, thereby ignoring women's distinct experiences and needs. More recently, scholars have looked at the relationship between transport and gender, highlighting important discrepancies in travel behavior (e.g., mode, purpose, time of trip). Yet, thorough spatial analysis, especially for the Canadian context, remains scarce. This study examines the differences in spatial travel patterns between men and women in Montréal, Canada, using the 2018 Origin-Destination survey. First, the distance travelled by men and women is analyzed through descriptive statistics, and two distinct bootstrapped linear regression models are generated to identify key determinants of travel distance among women and men. Second, a ratio of the number of trips (women/men) ending in each census tract is generated to identify areas predominantly visited by women. A local spatial autocorrelation analysis is then performed. Findings show that women's trips tend to be more local than men's, possibly attributable to socio-cultural factors. Differences between gender are most visible among lower-income groups and in suburban areas, while the presence of children in the household reduces women's distances more substantially than men's. Significant spatial clusters were found for women and men, with distinct land use and transport characteristics. This research highlights the need for researchers and practitioners to consider gender differences in transport planning and can contribute to formulating and designing more equitable transport policy and systems for men and women.

The COVID-19 pandemic has significantly reshaped travel patterns globally, prompting shifts in mobility preferences and behaviors. After controling for temporal trends and weather, this paper investigates the impacts of the pandemic on station-based bike-sharing and ride-hailing services in New York City (NYC), spanning the periods before, during, and after the pandemic. Specifically, we examine how these transportation modes evolved across various land-use types and pandemic periods. To achieve this, we employ a spatial clustering method to group NYC traffic zones into distinct functional areas, i.e., Mixed Area, Commercial Area, Residential Area, and Educational Area, based on land use characteristics. Subsequently, we develop two time series models based on the seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model to analyze the impact of the pandemic on trip demand across different spatial areas and years. Our modeling analysis enables us to precisely quantify the average effects of pandemic phases on daily trip ridership, while also assessing shifts in daily trip demand trends across each COVID phase, accounting for variables such as land use and weather. Our findings uncover strikingly different recovery trajectories for bike-sharing and ride-hailing services. Bike-sharing rapidly rebounded, surpassing pre-pandemic trip levels by the end of the reopening phase. In contrast, ride-hailing has not yet fully recovered and continues to lag behind its pre-pandemic levels. Moreover, we observe disparities in cycling recovery across various land-use types, with Mixed and Residential Areas exhibiting faster recovery compared to Commercial and Educational zones. The varying recovery patterns can be attributed to evolving traveler sentiments and preferences, shifts in trip needs and purposes, and the implementation of local policies aimed at fostering sustainable transportation options.

Increasing accessibility and improving cycling safety are the primary objectives of cities and policymakers. In the literature, there are several studies examining cycling safety and few studies examining cycling accessibility. However, few studies conduct a joint examination of these two topics to understand the relationship between them. This paper aims to develop and apply a methodological framework to conduct a joint zone-based analysis of traffic safety and accessibility. The developed framework integrates route choice modelling and four-step modelling into traffic safety and accessibility analysis and the outcome is a novel zone-based crash risk estimation incorporating traffic crashes with trip characteristics (including, trip purpose, origin-destination, and alternative routes). The proposed framework was applied in a case study to examine the injury crash risk imposed on commuting cyclists and job accessibility in the city of Utrecht, the Netherlands.

The results illustrate the need to embed trip characteristics into zone-based traffic safety estimation to be able to compare the spatial distribution of traffic safety with other mobility and transport-related indicators. Moreover, the findings reflect on significance of taking route choice features into account in accessibility analysis to avoid overestimating accessibility levels. They show that safety and accessibility levels are not equally distributed in the city of Utrecht. For example, low-income areas generally have lower job accessibility levels and higher cycling crash risks which imply the spatial and social inequalities in the transport system's effects.