Car Dependency Research Articles

Dissecting multidimensional morphology of urban sprawl: Framework for policy intervention

Urban sprawl is a major challenge to sustainability, yet it remains the prevalent form of urban growth globally. Traditional management strategies have been ineffective due to a siloed approach often neglecting the multidimensional complexity of urban sprawl morphology. This study bridges the gap by identifying the multidimensional features of urban sprawl morphology at city and neighbourhood levels and mapping these features to existing planning policies. The findings reveal strong linkages between city and neighbourhood morphological traits and highlight discrepancies in how current policies address urban sprawl, such as spatial development of greenfield, brownfield, infill development, pedestrian-friendly street design, adaptive reuse policy and chrono urbanism. The proposed framework advocates for coordinated multidimensional policy interventions promoting compact, polycentric cities with mixed land use and reduced car dependence. This integrated approach is crucial for developing targeted strategies to mitigate urban sprawl and foster sustainable urban development.

The Environmental and Biodiversity Impacts of a New Cableway System: A Comprehensive Life Cycle Assessment

Cars are still used as the primary mode of transportation for daily commuting, with their emissions significantly affecting urban air quality, contributing to overall greenhouse gas emissions. Efforts to reduce car dependency have led to exploration of alternative transportation options such as cableway systems in urban areas. However, limited information exists regarding the environmental impacts and biodiversity implications of such systems. This study conducted a comparative life cycle assessment between a proposed cableway system for the city of Trieste, Italy and its current car transportation mode. The analysis considered both daily operational profiles and passenger occupancy rates of the cableway system. Drawing from similar cableway systems worldwide, it was calculated that the proposed Trieste cableway would accommodate 2,007 daily passengers, on average. Results from the environmental assessment revealed that the cableway's operational phase had by far the greatest impact on all environmental categories, followed by its construction and by land clearance. Additionally, the use phase was found to be the major cause for most biodiversity loss, particularly towards terrestrial ecosystems. Comparisons of life cycle GHG emissions between the cableway and car transportation indicated that the cableway system would be a preferable option if the daily average passengers would reach at least 3,908, which is almost double than the expected ones. Furthermore, the cableway system exhibited larger environmental impacts across most categories compared to current car transportation. Thus, this study challenges the perception that the cableway system is a more sustainable option compared to conventional modes of transport, as additional factors need to be considered for a broader overview of the environmental performances.

Carbon emission reduction effects of heterogeneous car travelers under green travel incentive strategies

Encouraging car travelers to switch to public transport is an effective measure to alleviate urban traffic congestion and reduce traffic carbon emissions. This study integrates travel survey data with multi-dimensional individual travel data to focus on incentive strategies. The research identifies key target groups for green travel incentives and quantifies the carbon reduction potential and cost-benefit effectiveness of differentiated incentive strategies for heterogeneous car users. Using Nanjing as a case study, the results show that low-income groups, long-distance commuters, and those with lower car dependency are primary targets users for these incentives. The optimal periods for implementing these strategies are during morning and evening peak commuting times. There is a positive correlation between overall carbon reduction and incentive levels. With a green travel incentive of 0.5 yuan per trip, the target group’s carbon emissions from travel decreased by 27.3%. The highest cost-effectiveness was observed with a 0.1 yuan per trip incentive, resulting in a reduction of approximately 280 yuan per ton of carbon. This study provides crucial insights for designing effective green incentive strategies, enhancing both cost-efficiency and carbon reduction in urban transport.

Stuck in the driver’s seat: a conceptualisation for understanding car dependence and its determinants

ABSTRACT Car dependence brings along many negative social and environmental externalities that policymakers and stakeholders need to consider. Nonetheless, the concept is not well defined and lacks a clear framework regarding its determinants and mechanisms, which also leads to problems in terms of its operationalisation. Therefore, this paper proposes a conceptualisation and operationalisation of car dependence, which can serve as a basis for further research and policy. We define car dependence as the extent to which an individual is incapable to participate in location-based activities without a car in a satisfactory way. This definition is based on the theoretical background of the capabilities approach and the concept of motility and also linked to the concept of accessibility. Our conceptual model consists of seven components, most of which have been considered separately in previous conceptualisations, namely the land use system, transport system, natural environment, temporal component, social environment, and individual objective/subjective characteristics. These components range from being external to the individual (e.g. the land use system) to internal (e.g. individual features). Considering these components jointly emphasises the importance of looking at car dependence in a holistic, unifying way. This approach contributes to a better understanding of car dependence that goes beyond the explicit analysis of components in previous research. In addition, we provide a systematic approach to operationalising car dependence that contributes to a more comparable approach to measuring car dependence. Researchers have to decide whether they want to examine car dependence via its components or via self-report by individuals, whether they want to study the full set of components or only a subset, and whether they want to consider perceptions or factual information about external components. Therefore, our conceptualisation and operationalisation provide valuable new insights into car dependence regarding new research directions and policy approaches.

Does Car Dependence Make People Unsatisfied With Life? Evidence From a U.S. National Survey

In the United States (U.S.), cars play a key role in facilitating mobility. Americans heavily rely on their cars for daily travel due to the benefits of access, convenience, comfort, and autonomy that private vehicle travel offers. However, the potential negative implications of high rates of car ownership and use for wellbeing, sustainability, and social equity have sparked the interest of many scholars. We contribute to these lines of inquiry by examining whether and if so, how car dependence relates to people’s satisfaction with life. Our data come from a national survey with a representative sample (n = 2,155) of U.S. adults living in urban and suburban areas. Using descriptive statistics and multivariate regression models, we find that there is a threshold effect of car dependence on life satisfaction. Our results show that beyond a certain point, increases in car dependence yield a decrease in people’s satisfaction with life. For instance, we find that, in a typical week, relying on a car for more than 50 percent of the time for out-of-home activities is associated with a decrease in life satisfaction. These findings suggest that planners and decision-makers should promote multimodality and land use patterns that may help to reduce car dependence and its potential negative effect on subjective wellbeing (SWB).

Putting the Car Before the Horse: The Diffusion of the Automobile and the Rise of Technocratic Primacy

A key question in the literature of technology in society is the degree to which technology is a product of society and vice versa. A related question is how the differing cross-causal lines between the two change both technological and social forms. This paper considers these questions by conducting a review of the literature on technology and society, and then conducting a structured historical examination of the social, economic, and technical dimensions of the rolling-out and utilisation of the automobile in the United States since the early 20th century in light of that literature. This examination is broken into analytical “phases”, starting with the early days of the auto steeped largely (but not exclusively) in technological idealism, moving through an age of car-ascendancy that peaked in the 1950s and 1960s (with the birth of a literal “car culture”), and into the present day of automobile dependency and changes in auto technology that have varying societal implications that are still largely unexplored. This history is assessed according to three different broad approaches offered by the literature, including (1) an instrumental approach viewing technical change as largely socially “neutral” and technology as primarily driven by the need to solve specific material problems; (2) a values approach in which technology is viewed as having technical components but with technical change driven largely as an expression of social values, both of particular interest groups and societal idea-systems more broadly; and (3) a relational approach in which social and technical change arises from an interplay of different entities, human and non-human, relating to each other in dynamic ways. The American historical experience with the automobile suggests that all three models apply at different times, but that instrumental technological approaches have dominated there, often subordinating the human to the machine, rather than the other way around.

Assessing Non-linear Influences of Urban Layout on Driving Travel Distance: A Mumbai Case Study

Introduction This study investigates the impact of built environment factors on travel behavior in Mumbai, India, focusing on the non-linear effects on driving distances. The rapid urbanization and complex urban of Mumbai constitute present challenges for sustainable transportation, necessitating a deeper understanding of how urban planning influences travel behavior. While demographic factors have often been highlighted in travel studies, this research prioritizes the role of built environment factors. Materials and Methods The study utilized Gradient Boosting Decision Trees (GBDT) to analyze household travel survey data from Mumbai, capturing the non-linear relationships between built environment variables and driving distances. Partial dependence plots were used to visualize these effects, and the relative importance of each variable was assessed to identify key determinants of travel behavior. Results The analysis identified trip time as the most influential factor in determining driving distances, followed by built environment characteristics, such as proximity to commercial areas and intersection density. Socio-demographic factors were found to have a comparatively low impact. Non-linear relationships were observed, such as the stabilization of driving distances beyond certain thresholds of block density and proximity to bus stops. Discussion The findings challenge the traditional emphasis on demographic factors in explaining travel behavior, highlighting the significant role of urban form. The study reveals that specific built environment factors, such as accessibility and connectivity, play a crucial role in shaping driving behavior in a rapidly urbanizing city like Mumbai. These results suggest that urban planning strategies should prioritize these factors to reduce car dependency. Conclusion This study underscores the importance of the built environment in influencing travel behavior in Mumbai, particularly in reducing driving distances. The insights gained offer valuable guidance for urban planners and policymakers aiming to promote sustainable mobility in rapidly developing cities. Further research is recommended to validate and expand upon these findings in other urban contexts.

How to improve public environmental health by facilitating metro usage on weekend: exploring the non-linear and threshold impacts of the built environment.

The accelerated motorization has brought a series of environmental concerns and damaged public environmental health by causing severe air and noise pollution. The advocate of urban rail transit system such as metro is effective to reduce the private car dependence and alleviate associated environmental outcomes. Meanwhile, the increased metro usage can also benefit public and individual health by facilitating physical activities such as walking or cycling to the metro station. Therefore, promoting metro usage by discovering the nonlinear associations between the built environment and metro ridership is critical for the government to benefit public health, while most studies ignored the non-linear and threshold effects of built environment on weekend metro usage. Using multi-source datasets in Shanghai, this study applies Gradient Boosting Decision Trees (GBDT), a nonlinear machine learning approach to estimate the non-linear and threshold effects of the built environment on weekend metro ridership. Results show that land use mixture, distance to CBD, number of bus line, employment density and rooftop density are top five most important variables by both relative importance analysis and Shapley additive explanations (SHAP) values. Employment density and distance to city center are top five important variables by feature importance. According to the Partial Dependence Plots (PDPs), every built environment variable shows non-linear impacts on weekend metro ridership, while most of them have certain effective ranges to facilitate the metro usage. Maximum weekend ridership occurs when land use mixture entropy index is less than 0.7, number of bus lines reaches 35, rooftop density reaches 0.25, and number of bus stops reaches 10. Research findings can not only help government the non-linear and threshold effects of the built environment in planning practice, but also benefit public health by providing practical guidance for policymakers to increase weekend metro usage with station-level built environment optimization.

Interactive Effects of Built Environment and Parking Policy on Car Use: Examining Differences Between Work and Non-Work Trips

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence.

Impact of Areal Factors on Students’ Travel Mode Choices: A Bayesian Spatial Analysis

A preliminary analysis of the 2018/2019 Austin Travel Survey indicated that most off-campus students in Travis County, TX, tend to use cars rather than more sustainable transportation modes, significantly contributing to traffic congestion and environmental impact. This study aims to analyze the impacts of areal factors, including environmental and transportation factors, on students’ choices of travel mode in order to promote more sustainable transport behaviors. Additionally, we investigate the presence of spatial correlation and unobserved heterogeneity in travel data and their effects on students’ travel mode choices. We have proposed two Bayesian models—a basic model and a spatial model—with structured and unstructured random-effect terms to perform the analysis. The results indicate that the inclusion of spatial random effects considerably improves model performance, suggesting that students’ choices of mode are likely influenced by areal factors often ‘unobserved’ in many individual travel mode choice surveys. Furthermore, we found that the average slope, sidewalk density, and bus-stop density significantly affect students’ travel mode choices. These findings provide insights into promoting sustainable transport systems by addressing environmental and infrastructural factors in an effort to reduce car dependency among students, thereby supporting sustainable urban development.

Place and mobility in Wales: Challenges and opportunities for reducing car use in a car-dependent, low-density country

The related concepts of 15‐minute city and 20‐minute neighbourhood have gained increased attention, contributing to planning and transport strategies and policies in many cities with the objectives of reducing car use, boosting local economies, improving liveability of places and the health of those who live there. However, there has been relatively little consideration of whether and how the 15/20‐minute place concept can be applied beyond world cities to the towns and suburbs where many people live. Taking the example of Wales, the paper develops empirical analysis to explore the nature of and variation in car-dependence in a range of different places, from densely populated city centres to residential suburbs and small towns. This analysis shows that the potential for developing more liveable, less car-dependent places exists not only in central cities but in some smaller places where there is a resident live-work population and relatively short commuting distances. For places like Wales, which has already incorporated the 15/20‐minute place ideal into its planning framework and transport strategy, the aspiration to reduce car dependency will require policies that reflect the very different starting points in Welsh places.

Mapping Nutritional Inequality: A Primary Socio-Spatial Analysis of Food Deserts in Santiago de Chile

This study investigates the socio-spatial distribution of food deserts in Santiago de Chile, aiming to understand how urban planning and socioeconomic factors influence access to nutritious food. Employing geospatial analysis techniques with data from OpenStreetMap and the 2017 Census, the research identifies areas within Santiago where access to healthy food is limited. The novelty of this study lies in its application of spatial autocorrelation methods, specifically Local Indicators of Spatial Association (LISA), to reveal clusters of nutritional inequality. The findings indicate significant concentrations of food deserts in both lower socioeconomic peripheral areas and, surprisingly, in some high-income central areas. These results suggest that both poverty and urban infrastructure, including car dependency, play critical roles in shaping access to healthy food. By highlighting over two million residents affected by food deserts, the study underscores the urgent need for integrated urban planning and public health strategies. This research contributes to the understanding of urban nutritional inequality and provides a replicable methodological framework for other cities. The implications extend beyond Santiago, offering insights into how urban design can be leveraged to improve public health outcomes through better access to nutritious food.

Mobility as a Service (MaaS) for university communities: Modeling preferences for integrated public transport bundles

In order to investigate the role that Mobility as a Service (MaaS) could play in university communities to reduce car dependency and moderate car-oriented travel behavior, this paper examines individuals’ stated interest in adopting MaaS bundles in academic environments, where its potential is still largely underexplored. The study involves a large-scale survey campaign carried out within a university community in Milan (Italy), comprising 1873 answers from faculty members, technical-administrative staff, and students. The paper discusses the factors affecting behavioral intentions towards a potential MaaS adoption on the basis of aggregate statistics and discrete choice models estimates. This research highlights that there is a real opportunity to market MaaS in university communities, but an accurate user-centered design of the MaaS solutions is needed, based on individuals’ preferences and actual mobility needs. Results suggest that MaaS has a broader potential user base among individuals under 35 years old and Public Transport subscribers, and that MaaS bundles involving shared mobility services are attractive by residents in the city center, while reserved parking at interchange facilities is more attractive to commuters coming from suburban areas.

Proposing an ethics of care: Tracing Victoria's transport planning history

AbstractThis paper examines the question what kind of ethics prevail in contemporary urban transport planning and what potential does an ethics of care hold for practice? Researchers have given ample attention to the need for better governance and coordination, and despite acknowledging the need to reduce reliance on private cars, little has been said by them about what ethics can or should guide planning to bring about such frameworks for caring. This area of research merits urgent work given our collective need to address the socio‐spatial, climate, and health impacts of car dependence. Taking as our focus transport planning in Victoria, Australia, we consider how an ethics of care could open new ways to redress how transport planning has perpetuated injustices in metropolitan Melbourne. We draw on secondary research to consider both the conditions that cultivated the current transport planning landscape and pathways for possible change that lie ahead. The research highlights opportunities to consider care as an ethical framework for transport planning that could amplify justice and equity claims in urban transport planning for Australian cities and that has salience for other cities elsewhere.

Modelling mobility as a service: A literature review

MaaS (Mobility as a Service) is often presented as a means to solve some of the most pressing mobility issues such as car dependency and increasing vehicular greenhouse gas emissions. In this context, adequate models and simulations are key to estimating the impact of potential MaaS implementations and support decision-making to reap the benefits MaaS could bring. This article aims at reviewing MaaS representation in existing academic literature pertaining to transportation modelling, in order to assess its progress and identify trajectories for future improvements. We do so by considering mobility as an economic system in which MaaS interacts with both travel demand and supply. After identifying an adequate set of indicators to analyze MaaS models, we review 31 contributions and find out that most studies consist of demand-centered usage models while the integration of the system's supply side's operational and profitability factors is still lacking, especially in-MaaS financial flows.

The new frontier of urban mobility: a scenario-based analysis of autonomous vehicles adoption in urban transportation

ABSTRACT Urban mobility, as a critical component of urban development and sustainability, is on the brink of a major revolution with the advent and widespread adoption of autonomous vehicles (AVs). However, the ambitious vision of a transformative shared economic future and decreased car ownership conflicts with the notion that car dependency will be worsened, leading to significant uncertainties and potential challenges surrounding AVs, particularly in developing countries. In this context, this study contributes to the literature by addressing these uncertainties, through an empirical examination of preferences toward four distinct modes of transportation: “public transport”, “conventional private car”, “autonomous private car”, and “shared autonomous taxi”. To accomplish this, a scenario-based stated preference survey was administered in Istanbul, Turkey, as an example of a megacity in a developing country. The collected data were analyzed using discrete choice models (multinomial and random parameter (mixed) logit models) to reveal the preferences of the survey participants. The findings indicate that considering the social status and significance associated with private vehicle ownership, the challenges of popularizing shared and on-demand AV modes should not be underestimated.

Multi-group exploration of the built environment and metro ridership: Comparison of commuters, seniors and students

Understanding the associations between demographic groups’ metro travel behaviors and the built environment is crucial for addressing automobile dependence and promoting transportation equity and reasonable urban construction. This study examines the nonlinear relationships and threshold effects of the built environment on the metro travel patterns of three groups (i.e., commuters, seniors, and students) by applying smart card data in Kunming, China. We select the optimal machine learning model—gradient boosting decision trees (GBDTs)—and consider various built environment attributes. Our findings indicate that: 1) built environment attributes universally have nonlinear and threshold effects on metro travel for all groups; 2) the collective contributions of density and diversity differ greatly across groups compared to other attributes; and 3) only a few built environment attributes have similar effect directions and degrees across all three groups, while most have unique effects on each group. The findings suggest metro station area planning strategies to promote metro use and transportation equity for different groups.

How electric bikes reduce car use: A dual-mode ownership perspective

Electric bikes (e-bikes) can play a vital role in sustainable transportation and reducing car dependence. However, questions persist regarding the extent to which e-bikes contribute to replacing and complementing car use and other modes, especially from dual-mode ownership (households with both cars and e-bikes) perspective. Utilizing the Household Travel Survey dataset from Jiading, Shanghai, this study reveals that: (1) e-bikes can lead up to a 19% reduction in car mode share in dual-mode ownership households compared to car-only households; (2) e-bikes encourage a greater variety of non-commuting activities compared to car-only households; (3) e-bikes have a minor negative effect on public transport mode share, while e-bikes enhance mobility for older people. Overall, these findings underscore the importance of e-bikes in reducing car dependence and achieving development goals towards sustainable transportation and age-friendly cities.

Vulmob, a new multidimensional indicator of mobility vulnerability

Mobility enables to find jobs, go to school or meet people. However, long distances, high costs, car dependency and poor accessibility are sources of mobility vulnerabilities. The current rise in fuel prices may have a strong impact on mobility, especially for households that rely heavily on their cars. Moreover, the need to reduce air pollution and greenhouse gases emissions requires the implementation of ambitious environmental policies. It is therefore necessary to identify transport poor households, affected by financial issues, as well as vulnerable households whose mobility would be strongly impacted by changes in individual mobility conditions and would have difficulties to adapt to this situation. To this end, we construct VulMob, a multidimensional indicator made up of thirteen individual factors organized in four dimensions: financial resources and transport affordability, work constraints, heavy car use and accessibility and structural constraints. We apply this indicator to the Grenoble area, in France. Our results show that 9.6% are highly vulnerable, meaning that they face at least six vulnerability issues and 5.5% of the households face transport affordability issues. A typology of five profiles of highly vulnerable households shows that some are financially constrained; others are heavy car users, work at night or face public transport accessibility problems.

Spillover effects in transit networks: A parameterized weight matrix spatial lagged approach

Public Transit (PT) systems aim to provide social, economic, and environmental benefits to modern cities offering reliable transportation service to users and ultimately reducing the problems related to traffic externalities due to car dependency. With the growing trend of urbanization and the associated phenomenon of cities’ sprawl being increasingly evident, significant attention should be given to understanding PT systems’ performance and then improving their efficiency. Considering the spatial characteristics of the PT system's performance promotes the environmentally friendly transport “character” that every city endeavors. This paper aims to incorporate the spatial spillover effects of a realistic PT system by augmenting information about the service network along with socio-economic variables, in a spatial demand-supply econometric framework. In detail, geographically separated demand and supply information on bus stops and lines was analyzed by a spatial econometric model, namely, the Spatial Lagged X (SLX) model which may be formatted so that can soundly handle, spatial and –in particular- network data like those coming from the General Transit Feed Specification (GTFS) protocol widely used in PT systems. The novelty and the importance of the proposed model rely on the ability to introduce transit network structure within the framework of spatial econometric regression, fostering the explanatory statistical analysis over networked information. The developed modeling approach was applied to the urban and rural PT system of Nicosia (Cyprus), incorporating the spatial spillover effects of the system over more than 1,500 bus stops, 40 lines, and 252 different but spatially connected postcode areas. The results of the SLX model were compared with other demand models of this form typically used, namely the Ordinary Least Square model and standard Spatial Autoregressive models, providing solid evidence of the benefits of incorporating the network structure in spatial demand modeling, giving valuable input for further planning purposes.