Urban Transport Policy Research Articles

Analysing the Relationship between Proximity to Transit Stations and Local Living Patterns: A Study of Human Mobility within a 15 Min Walking Distance through Mobile Location Data

Urban planning and transportation policies are vital to creating sustainable and liveable cities. Transit-orientated development (TOD) has emerged as a prominent approach that emphasises the establishment of neighbourhoods with convenient access to public transportation, thereby promoting car-free lifestyles. This research investigates the connection between proximity to transit stations and local living habits in Auckland, New Zealand, which is a car-dependent city aiming to transition to a sustainable TOD model. We use geolocational data from mobile phones to measure the daily mobility patterns of residents living within a 15 min walking distance of various transit stations. Employing ordinary least squares (OLS) regression, we analyse the correlation between residents’ average travel distances and individual mobility, considering different station contexts. We aim to determine whether individuals living near transit stations are more inclined to participate in local activities and make a higher proportion of short-distance trips. The results illustrate that approximately 54% of the residents show dominant localised mobility patterns. Living near a station is significantly associated with shorter annual travel distances, although this trend varies by area. Notably, only about 16 of the 34 stations studied indicate that their local residents predominantly engage in ‘local’ travel patterns. Rural stations show less correlation, likely due to poor infrastructure and limited walkability. This study underscores the vital role of proximity to transit stations in promoting sustainable mobility. It serves as a foundational guide for urban planners and designers to make informed decisions that improve the built environment and optimise land use.

Inclusive and Safe Mobility Needs of Senior Citizens: Implications for Age-Friendly Cities and Communities

Municipalities are concerned with addressing social issues such as mobility inclusion and safety by increasing access to transport facilities and services for all groups in society to create equitable and equal access for all citizens. Moreover, the public transportation systems provided in cities have to be inclusive and safe, driven by emerging technologies such as Artificial Intelligence (AI)-based services that provide personalized recommendation to improve mobility inclusion and safety for all citizens in society, especially vulnerable road users such as senior citizens or older people. But at the moment, there are few studies that have investigated how municipalities can provide inclusive and safe public transportation in general and for senior citizens, particularly those aged 65 and above. Therefore, this study aimed to examine how to provide inclusive and safe mobility for senior citizens to improve out-of-home mobility services for senior citizens towards age-friendly cities and communities. Accordingly, a systematic literature review grounded on secondary data was adopted to investigate inclusive and safe mobility needs for senior citizens. The data were collected from previous research and existing documents, and a descriptive data analysis was carried out to provide insights on urban transportation policies related to senior citizens. Furthermore, case studies were adopted to present polices and strategies employed in Norway, Canada, the United States of America, the United Kingdom, Sweden, and Northern Ireland to identify measures employed to address the public transportation needs of an aging society, focusing on the provision of inclusive and safe mobility to senior citizens. Further findings from this study included the possible use of emerging technologies such as AI-based machine learning for inclusive and safe mobility.

Model for the Evaluation of Urban Transport Policies and Their Interaction with the Housing Market

We analyze several scenarios of transport reforms for the city of Bordeaux (France) using a model that takes into account the interaction between transport and the housing market. We find that road pricing schemes are significantly more effective when they are accompanied by an increase in housing supply in locations where demand increases. This allows households to consider their options for relocation in the medium and long term. Our analysis is based on an aggregate model with a nested decision structure that includes both transport and housing. We provide a full description of the model structure and the calibration steps and make the source code available for those who wish to analyze other cases.

O.1.3-7 Hungarian Active Lifestyle (HEPA) Strategy 2033

Abstract Inactivity and obesity crisis is getting serious in Hungary in the last decade. According to the latest Eurobarometer studies (2022) 59% of the population are inactive and do not meet the WHO minimum physical activity recommendations. Besides, research shows that nearly 60% of Hungarian adults are overweight or obese, and every fifth child as well. As a respond to these challenges in 2023 the first ever Hungarian Active Leisure (HEPA) strategy has been prepared. As a first step we have created a sectoral map and interviewed potential action partners, including all the most recognized stakeholders from the recreation, sport, health and education sector. After a deep overview of the relevant literature, international guidelines and best practices the team of experts chose the OECD/WHO ‘Policy options to increase PA intervention’ model to follow (2023) as theoretical framework for future interventions. The major focus areas of interventions such as School-based interventions, Workplace-based interventions, Interventions of the Healthcare settings, Interventions in the sports sector and Information and communication policies must have been extended with three more areas: Urban design and transport policies, Natural environment and at last Seniors and Socially and economically disadvantaged citizens. A number of programs have already been piloted (just like Active School Program, Sport Clubs for Health, Workplace interventions or Senior - Pre-school children’s recreational-sport activities together) with great results. Indicators are not only the growing numbers of participants but also successful pilot programs are spreading and more and more work-places, local communities and sport clubs open up to follow these examples all over the country. Hopefully, in the medium and long term both physical activity rates will increase and health and well-being benefits are going to be significant too. Sources: https://sport.ec.europa.eu/news/new-eurobarometer-on-sport-and-physical-activity https://read.oecd-ilibrary.org/social-issues-migration-health/step-up-tackling-the-burden-of-insufficient-physical-activity-in-europe_540a3e56-en#page1

Towards an equity-centred model of sustainable mobility: Integrating inequality and segregation challenges in the green mobility transition

Urban planners and transportation policy makers around the world are proposing initiatives for greener mobility, particularly by promoting higher urban development densities, active transport modes, and non-auto access to destinations. This Special Issue engages critically with the sustainable mobility and 15-Minute City concepts by outlining an Equitable Sustainable Mobility Model that integrates non-auto accessibility improvements with key daily activity destinations to establish a wider discussion on urban structure, segregation, equity and mobility. The papers collected in this Special Issue reveal that sustainable mobility solutions are only partial when detached from the underlying mechanisms of residential sorting and spatial patterns of daily activity spaces. An equitable shift towards greener mobility needs to (1) address rising levels of residential segregation by promoting neighbourhood-level mixed-income housing, (2) radically shift urban space from automobility to different greener forms of mobility, (3) address not only neighbourhood specific, but also metropolitan-level access challenges to key activity places, (4) focus on integrating broadly accessible and affordable travel modes, particularly active travel (walking and cycling) and public transit, and (5) develop e-mobility solutions that are accessible to diverse user needs and offer flexible inter-neighbourhood coverage.

Integrated Urban Transportation Policy: A Study of Kochi Metro and Vyttila Mobility Hub in Kerala, India

Integrated infrastructure has been considered the key to the development of the urban transport system. Studies have rarely focused on the benefits and issues related to the urban integrated transport system, including mobility hubs. The present study attempts to analyze different aspects concerning the urban integrated infrastructure with a special focus on the Kochi Rail Metro and the Vyttila Mobility Hub in Kerala. The study reveals that 41 percent of commuters rely on Hub and Metro for occupation-induced traveling, followed by education (28 percent) and health (20 percent). It is revealed that the existing fare of Kochi Metro does not appear to be attractive to passengers. Almost 90 percent of passengers consider fares as not reasonable. Most of the commuters of Metro Train services and Mobility Hub share the view that these are ‘inclusive.’ The most noteworthy aspect of Metro and Hub is that they are eco-friendlier and sustainable. However, as an integrated infrastructure mode, it has to travel a long way yet. The study shows that the metro rail services must be accessible and affordable to the people. The study suggests that metro authorities need to make policy decisions to rationalize the fare rates in accordance with different parameters to attract more passengers to the Metro services. As the commuters from the city area are averse to using the metro services, steps need to be taken to encourage the urban passengers to use the metro services.

How do the affective and symbolic factors of private car driving influence car users’ travel behavior in a car restriction policy scenario?

The number of private car trips a person makes is usually linked to external factors such as economic incentives or disincentives, legislation, infrastructure, and the quality of transport systems, among others. The impact of these options are typically analyzed to evaluate urban transport policies and projects. However, internal factors related to an individuals' attitudes and perceptions also play an essential role in the amount of private car driving they do and on urban mobility as well. Therefore, insight into private car driving's affective and symbolic aspects is important in order to formulate appropriate transport policies and strategies to reduce car-use dependency and encourage private car drivers to use public transport. Congestion charging schemes make drivers pay the full social cost of driving, they achieve congestion reduction, pollution reduction, they make cities more attractive for pedestrians and cyclists, and help improve quality of life. Congestion charging schemes are often difficult to implement and expensive to administer. As a result of these reasons, several cities worldwide have adopted a variety of car restriction schemes that try to reduce air pollution and congestion as well, instead of establishing congestion charges. The effects of driving restrictions in the short term are positive, but in the medium and long term, there are unwanted consequences. However, by giving private car drivers the option to pay a toll so that their cars are exempted from the restriction, these perverse incentives could be eliminated. This paper analyzes the impacts of internal factors related to individuals' attitudes and perceptions about the travel behavior of car users affected by car restriction policies in urban areas. We designed a stated preference survey conducted among car owners in Cali, Colombia, where a License Plate Restriction Charging (LPRC) policy has been in place since January 2017. Through hybrid discrete choice modeling, we demonstrated that latent variables, such as the feelings of being in control, independence, and higher social status, positively influence the decision to use cars for daily trips, thus impacting the urban modal split. The heterogeneity captured through these latent variables allowed us to understand more deeply how individuals deal with the LPRC policy in order to travel to their destination.

Barriers to bike and e-scooter sharing usage: An analysis of non-users from five European capital cities

In recent years, shared micro-mobility, particularly bike sharing systems (BSS) and e-scooter sharing systems (ESS), has emerged in many countries with the premise of fostering a more sustainable and healthier urban living. However, available research predominantly focuses on the users of these systems, while non-users and their opinions are often neglected although they may be also perceived as potential users.This study focuses on a less researched aspect of bike and e-scooter sharing systems: what are the reasons for not using these systems. Through the use of a comparative and survey-based research carried out in 2021 in five European capital cities (Budapest, Lisbon, Rome, Vilnius, and Warsaw), this research discloses the main drivers and behavioral attitudes towards the non-use of BSS and ESS during the coronavirus pandemic, when these means increased in importance as an alternative to public transport due to health and safety concerns.The analysis revealed that the main barriers to non-users are mainly external and infrastructural, such as other modes of transport being more convenient; safety concerns about riding in traffic; poor road conditions; lack of dedicated cycle networks, and destinations being too distant to be reachable by bike or e-scooter. These findings indicate that the further development and deployment of BSS and ESS in European cities primarily depends on local administrations, and urban transportation policies, and not so much on the users’ attitudes and adaptability.

Low Emission Areas vs. Urban Congestion Taxes

In most European cities, urban transport is responsible for the majority of energy consumption, the emission of pollutants into the air, traffic congestion and noise, and in the last century we have faced an increase in urban mobility and a growing tendency to use private, as opposed to public transport, and an increase in the number of vehicles. The strictly private economic rationality of citizens explains this trend and the market will regulate it, albeit with largely avoidable social costs of congestion. Supply policies, that is, more and more extensive routes, are those that have been carried out almost exclusively traditionally, but these have been insufficient and, paradoxically, have even caused effects contrary to those intended, in the light of the state of empirical experiences, not to mention the waste of public resources that may be destined for more socially profitable alternative uses. As a consequence, where there is the greatest room for manoeuvre for urban transport policy is found in demand, that is, in the use of available means of urban transport. In recent decades, a good number of partial demand measures have been tried in European cities, such as subsidies for buses and subways, ecological fuels, car-sharing, smart cards, road-pricing, park-pricing, one day without a car, distribution of departure times at the end of the working day, etc. This paper focuses on Road Pricing, pointing out the experiences of the cities in which it has been put into practice but, mainly, examining its economic foundation and the design that should inspire collaboration in terms of achieving a more efficient and socially equitable urban mobility model. Keywords: Taxes; Automobiles; Highways; Payments; Urban congestion; Polluters.

Uncovering spatiotemporal micromobility patterns through the lens of space–time cubes and GIS tools

In the past ten years, cities have experienced a burst of micromobility services as they offer a flexible transport option that allows users to cover short trips or the first/last mile of longer trips. Despite their potential impacts on mobility and the fact that they offer a cleaner, more environmentally friendly alternative to private cars, few efforts have been devoted to studying patterns of use. In this paper we introduce new ways of visualizing and understanding spatiotemporal patterns of micromobility in Madrid based on the conceptual framework of Time-Geography. Hägerstrand’s perspectives are taken and adapted to analyze data regarding use of micromobility, considering each trip departure location (origins) obtained from GPS records. The datasets are collected by three of the most important micromobility operators in the city. Trip origins (points) are processed and visualized using space–time cubes and then spatially analyzed in a GIS environment. The results of this analysis help to identify the landscape of micromobility in the city, detecting hotspot areas and location clusters that share similar behavior throughout space and time in terms of micromobility departures. The methods presented can have application in other cities and could offer insights for transport planners and micromobility operators to better inform urban planning and transportation policy. Additionally, the information could help operators to optimize vehicle redistribution and maintenance/recharging tasks, reducing congestion and increasing efficiency.

A Probabilistic Simulation Framework to Assess the Impacts of Ridesharing and Congestion Charging in New York City

Understanding the holistic city-wide impact of planned transportation solutions and interventions is critical for decision making, but challenged by the complexity of the urban systems, as well as the quality of the available urban data. The cornerstone for such impact assessments is estimating the transportation mode-shift resulting from the intervention. Although transportation planning has well-established models for the mode-choice assessment such as a nested multinomial logit model, an individual choice simulation could be better suited for addressing the mode-shift allowing us to consistently account for individual preferences. Moreover, the available ground-truth data on the actual transportation choices is often incomplete or inconsistent. The present paper addresses those challenges by offering an individual mode-choice and mode-shift simulation model and the Bayesian inference framework, and demonstrates how impact assessments can be performed in the events of incomplete mobility data. It accounts for uncertainties in the data as well as the model estimate and translates them into uncertainties of the resulting mode-shift and the impacts. The framework is evaluated on the two intervention cases: introducing ride-sharing for-hire-vehicles in NYC as well the recent introduction of the Manhattan Congestion surcharge. It can be used to assess mode-shift and quantify the resulting economic, social and environmental implications for any urban transportation solutions and policies considered by decision-makers or transportation companies.

Environmental and welfare gains via urban transport policy portfolios across 120 cities

Environmental and welfare gains via urban transport policy portfolios across 120 cities

Climate targets as more than rhetoric: Accounting for Norway's Zero Growth Objective

Climate-related targets for cities abound, but it is unclear how important they are in driving actual transformations. Scholars have often taken a skeptical view of official climate discourses, including their ambitious targets, and instead turned their attention to experimentation, innovation and civic action – colloquially termed 'real action.' In this article we try on the opposite view. Contributing to 'speculative political ecology', we argue that climate-related targets, even those without hard policies directly attached to them, can render climate change more governable and actionable. In a fragmented, polycentric and dispersed governance landscape, the immutability of a 'hard' number can create coherence, direction and measurability to policy action. We examine a particular target, and its associated governance instruments, which has arguably had a transformative effect on urban policy. Our empirical focus is Norway's Zero Growth Objective in urban transport policy. We follow the target from its first formulation as a soft goal around 2006 and until 2019, by when it had materialized as a hard target shaping funding streams and concrete policy interventions, and most likely, emission levels. Arguably, it has been a highly effective frame for policy.

The Impacts of the Multiscale Built Environment on Commuting Mode Choice: Spatial Heterogeneity, Moderating Effects, and Implications for Demand Estimation

Promoting the usage of sustainable commuting modes requires in-depth understanding about residents’ commuting mode choice behavior. This study presents an empirical study to investigate the relationship between the built environment and commuting mode choice using CLDS 2016 cross-city questionnaire data. Several multilevel multinomial logit models including the null model, base model, and moderating effect model are developed to analyze the effects of built environments at both city and neighborhood levels on commuting mode choice. Estimation results of the null model reveal the significant spatial heterogeneities in commuting mode choice across different cities and different neighborhoods within a specific city. We then explore the potential built environment variables yielding the spatial heterogeneity via the base model. Results show that the built environment at the city level (including the urbanization rate, number of public transportation vehicles, metro operating mileage, GDP, city population density, and road area per capita) and neighborhood level (including neighborhood population density, air quality, neighborhood location, and land use diversity) could partially explain the spatial heterogeneities in commuting mode choice. In addition, the moderating effects of these built environments on the link between commuting time and commuting mode choice are examined. Results imply that the urbanization rate and neighborhood population density moderate the effect of commuting time on choosing nonmotorized modes, while neighborhood location moderates the effect of commuting time on choosing public transit. Also, the mode shares of nonmotorized mode and public transit under different levels of commuting time are estimated in different built environment contexts. The findings of this study are expected to provide serviceable support for urban planning and transportation policy making.

Greening the Urban Transportation. A Debate on the Solutions of the Flying Car

Facing climate change challenges, many local governments worldwide became active deploying Green Urban Transport Policies (GUTP). By doing so, their central objective is to curb CO2 emissions and manage the latent tension between accessibility, mobility and quality of life. However, in some cases, those policies indirectly foster the localized development of cleantech innovations. In this paper we analyze the urban Europe state on cities, towns and suburbs based on the available data from the Report of 2016. Then there will be presented a study for the introducing of the flying car as an innovative solution from the electric one to green the cities’ transportation.

The effect of sustainable mobility transition policies on cumulative urban transport emissions and energy demand

The growing urban transport sector presents towns and cities with an escalating challenge in the reduction of their greenhouse gas emissions. Here we assess the effectiveness of several widely considered policy options (electrification, light-weighting, retrofitting, scrapping, regulated manufacturing standards and modal shift) in achieving the transition to sustainable urban mobility in terms of their emissions and energy impact until 2050. Our analysis investigates the severity of actions needed to comply with Paris compliant regional sub-sectoral carbon budgets. We introduce the Urban Transport Policy Model (UTPM) for passenger car fleets and use London as an urban case study to show that current policies are insufficient to meet climate targets. We conclude that, as well as implementation of emission-reducing changes in vehicle design, a rapid and large-scale reduction in car use is necessary to meet stringent carbon budgets and avoid high energy demand. Yet, without increased consensus in sub-national and sectoral carbon budgets, the scale of reduction necessary stays uncertain. Nevertheless, it is certain we need to act urgently and intensively across all policy mechanisms available as well as developing new policy options.

Urban freight policy maturity and sustainable logistics: are they related?

Problems associated with urban freight are well known and documented in the academic literature, particularly with regards to the impact on air quality and general intrusion of public space. As a defining principle however, urban freight has generally been left solely to operate on free market principles, with policy interventions generally being solely ‘problem’ focused. Given the underlying economics of freight transport, and particularly the cost advantages of road-based transport, intervention by public bodies is clearly a critical issue, however to date has received limited attention in the urban freight research literature. The aim of the current research is to examine if there is any relationship between the extent of local authorities’ freight policy development and the success of a policy driven (green) urban freight pilot initiative. This is based on five city case studies located across Northern Europe and uses an adapted form of Kiba-Janiak (Res Transp Bus Manag 24:4–16, 2017, https://doi.org/10.1016/j.rtbm.2017.05.003) five stages of ‘city maturity’ with regards to urban freight policy development. Each city’s policy framework is mapped onto one of these states of maturity. The success of the pilots in each city is then matched against the maturity of the policy framework. Taken at face value, the results show little correlation between the two, and hence the success of any initiative would appear to be independent of the policy framework. The real issue however is found to be low urban freight transport policy maturities within the case study sample, specifically a lack of tactical and operational functions, i.e. the ability to actually do something. The concern at the more general level is that what this leads to is policy stagnation.

A social media Data-Driven analysis for transport policy response to the COVID-19 pandemic outbreak in Wuhan, China

Non-pharmacological interventions (NPI) such as social distancing and lockdown are essential in preventing and controlling emerging pandemic outbreaks. Many countries worldwide implemented lockdowns during the COVID-19 outbreaks. However, due to the lack of prior experience and knowledge about the pandemic, it is challenging to deal with short-term polices decision-making due to the highly stochastic and dynamic nature of the COVID-19. Thus, there is a need for the exploration of policy decision analysis to help agencies to adjust their current policies and adopt quickly. In this study, an analytical methodology is developed to analysis urban transport policy response for pandemic control based on social media data. Compared to traditional surveys or interviews, social media can provide timely data based on the feedback from public in terms of public demands, opinions, and acceptance of policy implementations. In particular, a sentiment-aware pre-trained language model is fine-tuned for sentiment analysis of policy. The Latent Dirichlet Allocation (LDA) model is used to classify documents, e.g., posts collected from social media, into specific topics in an unsupervised manner. Then, entropy weights method (EWM) is used to extract public policy demands based on the classified topics. Meanwhile, a Jaccard distance-based approach is proposed to conduct the response analysis of policy adjustments. A retrospective analysis of transport policies during the COVID-19 pandemic in Wuhan, China is presented using the developed methodology. The results show that the developed policymaking support methodology can be an effective tool to evaluate the acceptance of anti-pandemic policies from the public's perspective, to assess the balance between policies and people’s demands, and to further perform the response analysis of a series of policy adjustments based on online feedback.

Urban transport infrastructure and household welfare: evidence from Colombia

The effects of urban transport policies on household welfare are a broadly understudied topic in developing countries. This paper analyzed the distributional effects of a bus rapid transit (BRT) system in Barranquilla, Colombia. Using geocoded household survey data over 2008-15 and a difference in differences approach, it showed that, in proximity to newly opened stations, poor households were replaced by non-poor households. These results suggested that the designers of such systems, despite the generally positive assessment of the systems, may have overlooked distributional consequences. Moreover, it showed that results in studies that do not control for the observed changes will be biased.

Familiar Strangers and Crime at Transit Stations: Is Crime Lower at Train Stations Where Familiar Strangers are Present?

Familiar strangers—individuals related through regular and repeated visual encounter occurring without verbal interaction—may reduce the risk of crime at places by increasing guardianship and internal motivation for norm compliance. This study examines the association between familiar stranger presence and incidents of theft and disorder at train stations using transit smart card and crime data for 22 stations across a six-month period. Familiar strangers are operationally defined as individual transit cards that are co-present within a 30-min temporal window on more than two occasions across a one-month period at a given train station. We apply logistic regression to estimate the likelihood of disorder and theft crimes within a 400-m radius of train stations controlling for station environmental features, co-located facilities and neighbourhood socio-demographic characteristics. Our results show that the impact of familiar strangers on crime (disorder and theft) at train stations is moderated by the neighbourhood socio-demographic context. This may suggest that macro-level norms of informal social control are important for determining crime at micro-places such as transit stations. The findings also indicate that urban design and transport policies require greater flexibility to enable intra-network variability in station design and formal security to enhance ridership.