Car Travel Research Articles

Optimizing Traveler Behavior Between MADINA and JEDDA Using UPPAAL Stratego: A Stochastic Priced Timed Games Approach

This study looks at how travelers move between MADINA and JEDDA, using the UPPAAL Stratego tool to tackle the complexities of urban mobility. As cities grow, effective transportation planning becomes more challenging. Travelers have three options: car, bus, and train. The choices for car and bus travel are impacted by traffic conditions, which can vary between heavy and light, affecting both travel time and cost. We propose a detailed mathematical model that captures all possible scenarios related to these travel options, incorporating the uncertainties of real life. This allows us to simulate different traffic situations. By using UPPAAL Stratego, we evaluate three strategies: the Safe Strategy, which minimizes risk; the Fast Strategy, which aims to reduce travel time; and the Fast and Safe Strategy, which seeks a balance between speed and safety. This paper starts with an introduction to the Stochastic Priced Timed Games approach, highlighting its relevance in modeling dynamic travel environments. We then provide an overview of UPPAAL Stratego, showcasing its abilities in generating, optimizing, and comparing strategies. Next, we outline our mathematical model, explaining the assumptions, parameters, and data sources we used. Our simulation results illustrate how each strategy performs under different conditions, shedding light on traveler preferences and behaviors. The findings underscore the significance of accounting for traffic variability in travel planning and offer important insights for urban transportation policies aimed at improving the traveler experience and optimizing resource use. Additionally, we emphasize the theoretical contributions of our model by demonstrating its applicability to real-world scenarios and its potential to inform future research in urban mobility optimization. Ultimately, this research adds to the growing knowledge of smart transportation systems, demonstrating how formal mathematical modeling can address complex real-world challenges and inform future urban mobility strategies.

Diminishing returns of additional active travel infrastructure: Evaluating Barcelona's decade of sustainable transportation progress

In the context of the urgent climate crisis in urban areas, transportation policymakers are actively working to shift from car travel to sustainable transportation options through strategic interventions in the built environment. These efforts often involve a dual approach: promoting higher activity density to increase proximity to destinations while enhancing the experience of active mobility. However, a notable gap exists in addressing densely populated areas with established built environments, where the focus remains primarily on improving active mobility infrastructure. This study represents a crucial initial step in tackling this challenge. It examines mode distribution trends and trip purposes in Barcelona, an urban area that has recently seen significant enhancements in active mobility spaces. Our study sheds light on evolving modal share trends by analyzing local travel surveys from 2010 to 2019. The findings reveal relatively unchanged patterns in travel behavior at the city level during the examined years. Nevertheless, a closer examination of mode distribution for specific trip purposes, age ranges, and gender exposes noticeable shifts. The newly implemented infrastructure may have helped prevent a shift from active mobility to car usage, particularly for trips traditionally associated with public transit or walking, such as accessing public or health services. Further research is needed to explore this hypothesis and determine the extent of its impact.

Exploring vehicle preference dynamics: Analyzing the influence of oil price volatility on consumer car purchase decisions - A comparative survey experiment

China's automobile market is continuously expanding, leading to ongoing growth in oil demand. Fluctuations in oil prices will inevitably impact the travel patterns and car purchasing behavior of automotive consumers. This paper analyzes the influence of gasoline price fluctuations on the travel patterns and car purchasing behaviors of auto consumers with varying incomes, employing a dynamic perspective. We conducted a questionnaire survey of auto consumers in four first-tier cities in China and performed a comparative analysis of questionnaire data from 2015 to 2022. The empirical findings are as follows: (1) Under conditions of elevated oil prices, fuel car consumers exhibit an increased susceptibility to oil price fluctuations, which may cause fuel car consumers to curtail their travel activities. (2) The 10 yuan/liter is the threshold for middle - and upper-income consumers to change their car buying or travel habits, which has not been affected by oil price fluctuations. (3) For the cohort considering electric vehicles, gasoline prices stand as the primary determinant influencing their car buying choices. The primary conclusions serve as significant references for the government to craft corresponding carbon emission reduction policies amidst fluctuating oil prices.

Spatial disparities in access to NHS dentistry: a neighbourhood-level analysis in England.

Over the past decade, access to National Health Service (NHS) dentistry in England has been problematic. There are increasing media reports of patients being unable to find treatment at a local NHS dentist. However, the extent of this issue varies by location and by the characteristics of the neighbourhood. The study uses official data sources on NHS dental provision and population. Travel accessibility is measured using car journey times. An advanced form of Floating Catchment Area accessibility is used, which accounts for supply competition, varying catchments, and distance decay. Spatial availability and accessibility indices are calculated. Ways in which the method can be used to explore various types of 'what-if' scenarios are outlined. Both availability and accessibility vary by the level of neighbourhood deprivation and the urban/rural nature of the neighbourhood. A case study, based on a real-world situation, shows the impact on the local neighbourhood of the closure of a dental practice. For all neighbourhoods, NHS dental provision is generally less than would be needed to provide basic dental care. The interpretation of outputs needs to take account of edge-effects near to Scotland and Wales. Possible improvements include the inclusion of other modes of travel and the exclusion of the population that does not want to access NHS care.

Designing a carbon-trading incentive scheme for mode shifts in multi-modal transport systems

The pressing need to reduce greenhouse gas emissions triggers the imperative for efficient travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which place a significant financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters shifting to using public transit. The incentive budget for PCTTI is sourced from the revenue generated through selling carbon emission reductions resulting from commuters’ travel mode shifts. To determine the optimal incentives, we developed an incentive scheme optimization model based on the Stackelberg game model. Numerical analysis reveals the significant potential of the PCTTI to reduce carbon emissions and travel costs across various scenarios within a multi-modal transportation system. This potential is evident amidst changes in the fixed costs of car travel, carbon trading prices, the use of different travel modes, the value of time, and the prevalence of electric vehicles. The advantages are most pronounced when the carbon trading price exceeds 40 CNY/ton, and when the usage of public transit, the value of time, and the proportion of electric vehicles each fall below 0.4, 50 CNY/hour, and 0.4, respectively.

Understanding the urban mobility challenge: Why shared mobility providers fail to attract car drivers

Reducing urban car traffic has become a global policy objective. A vital element in achieving this objective is the availability of shared mobility providers offering sustainable alternative travel modes such as micromobility, carsharing, and ridehailing. Despite policy and industry efforts, shared mobility options have failed to change the travel patterns of current car users. We explore this urban mobility challenge through an empirical study of 807 urban travelers. Our results show that car drivers estimate travel costs conceptually rather than rationally and consider both trip purpose and length. In particular, car users perceive longer and recreational trips as cheaper per distance driven than shorter and work-related trips. A segmentation analysis reveals that habitual and technology-averse car drivers are particularly susceptible to this skewed cost perception, unlike more frequent transit users. Embedding these results in a case study of current shared mobility options shows that these options are ill-adjusted to the preferences of car travelers but more attractive to current transit users, potentially leading to cannibalization. Based on these findings, we outline several strategies for mobility providers and policymakers to attract car drivers to shared mobility options, thereby contributing to solving the urban mobility challenge.

Green commuting within the x-minute city: Towards a systematic evaluation of its feasibility

In cities, carbon emissions associated with commuting transport is large and significant. This study integrates data about the jobs-housing relationship, road network configurations, public transport availability, and real-time traffic conditions during peak hours to evaluate the commuting feasibility and performance of green travel modes (walking, cycling and public transport) and explore the potential determining factors. In the context of the x-minute city, the green travel commuting feasibility (GTCF) indicator measures the percentage of the working population who can commute via green travel modes within specific x-minute thresholds. 15, 30, 45 and 60 min have been considered. In comparison, the car travel commuting feasibility (CTCF) indicator is developed to evaluate the corresponding commuting performance by car. Nanshan district of Shenzhen in China is taken as a case study. Results show that distinct gaps exist between GTCF and CTCF. Public transport performs well only for long-distance (> 8 km) commuting trips, and cycling does well for short (< 3 km) and medium-distance trips. Geographically, areas with large differences of GTCF and CTCF are identified for improving green travel modes with priority. Potential factors influencing GTCF are explored with a regression model and case-based analysis. Smaller street blocks, bus route realignment and better jobs-housing balance should be targeted. Designing cycling short-cuts and public transport routes that avoid traffic jams are also recommended to promote green commuting. The findings demonstrate that real-time trip-planning information is of great value in evaluating the commuting feasibility of multimodal travel and identifying influential factors for achieving the x-minute city.

Why do sustainable shared mobility practices not proliferate more widely? Insights from digital mobility diaries

Sharing instead of owning consumer goods should significantly reduce their production and the associated environmental damages. However, this ecological promise has yet to be fulfilled, even in mobility, where sharing practices have become mainstream. This is because the most widespread mobility-sharing practice (free-floating carsharing) has the lowest ecological benefit. This study asks why the adoption of more ecologically beneficial shared mobility practices remains lower, addressing this question through digital ethnography. Using digital mobility diaries for three weeks, 21 respondents documented their mobility practices (including various shared mobility practices and private car travel) by uploading pictures, videos and text notes on a dedicated smartphone application. The data show that free-floating carsharing has proliferated because it can leverage the ‘system of automobility’ as its users are relatively monomodal. Other shared mobility services function well; however, we found that they have not proliferated as widely because the overall multimodal mobility mix (e.g. walking, cycling, public transport, on-demand sharing) associated with this form of shared mobility is highly demanding. Better conditions for multimodal mobility, created through appropriate infrastructure, are crucial for sustainable shared mobility practices to spread. However, space limitations mean this will likely come at the expense of car-centred infrastructure and necessitate its exnovation.

Legal Perspectives on New Urban Quarters in Germany: Living the Dream of the Compact City?

The ‘leitmotif’ of the compact city has become a widely embraced template for sustainable urban development. Particularly infill and redevelopment areas, as well as many planned new settlements, have been built following the planning principles of urban compaction. Numerous positive effects are attributed to high-density settlements such as more efficient use of infrastructure and less reliance on automobile travel. Planning law and policies, in Germany as well as other countries around the world, regularly strive to advance high-density developments, but it is by no means clear whether the prescribed densities in planning policies actually lead to vibrant and healthy places which fulfill the expectations of their inhabitants with regards to their quality of life. The study aims to analyze the relation between binding land-use plans in Germany and individual perceptions of urban density through a case study-based survey. This paper contributes to providing new information on achieving compact urban form and quality of life in new urban quarters by analyzing the change of densities over the past three decades in ‘large’ urban developments across Germany, by an in-depth assessment of planned and built densities within an archetypal urban extension and finally by contrasting these ‘objective’ figures and findings with the ‘subjective’ feelings of inhabitants. For sources of information, this paper draws from literature, surveys and empirical analyses as well as desktop-studies.

Modelling Passengers’ Travel Behaviour for Shared Autonomous Vehicle and Bus Considering Heterogeneity

The popularisation of autonomous vehicles will give rise to a new business model called shared autonomous vehicle (SAV). SAVs may attract a large number of passengers and lead to a decline in the share of buses, which can be interpreted by exploring passengers’ travel behaviour when confronting the SAV and bus modes. Thus, this paper addresses the SAV and bus passengers’ travel behaviour, aiming to examine the factors influencing travel behaviour and revealing the characteristics of SAV passengers. We classified passengers using latent class cluster analysis and modelled passengers’ travel behaviour based on confirmatory factor analysis and mixed logit model. The findings indicate a variation in travel preferences among different classes of travellers. Short-distance travellers pay less attention to travel time. Non-short-distance PT travellers are most likely to be affected by service attributes (waiting time, travel time and travel costs). Non-short-distance private car travellers are more likely to become early SAV adopters. Passengers travelling for short distances may be more likely to choose SAV, which reveals the potential of SAVs to become a first and last mile connection for public transport. Passengers lack trust in SAVs, which will affect their promotion.

Too Far? Autonomous vehicles, travel demand, and carbon dioxide emissions in Sweden

This article envisions that by the middle of this century fully self-driving Autonomous Vehicles (AVs) are available for private use. By considering how AVs can affect the utility of being in the vehicle, and accounting for the utility of being able to transport oneself to and from various locations, we derive the consumer surplus of having an AV and evaluate that against the cost of adopting the technology. This break-even calculation is used to evaluate AV purchase and consequent impacts on increase in travel demand and lifecycle CO2 emissions for different income groups for different assumptions concerning the Value of Travel Time, transport demand elasticity, AV technology costs, interest rates, and the possibility to work in the car or not. The modelled results show that all income groups purchase AV given low technology cost, and the highest income groups purchase AV under most conditions. Changes in demand elasticity and the value of travel time have the largest effect on vehicle miles traveled, which could be as much as 50 additional kilometers daily per driver. Even in a scenario consistent with the Paris Agreement, this implies an annual carbon footprint of 0.42 – 0.86 metric tons of CO2 per driver from personal car travel in Sweden.

Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020

In this study, we evaluated and forecasted the cumulative opportunities for residents to access radiotherapy services in Cali, Colombia, while accounting for traffic congestion, using a new people-centred methodology with an equity focus. Furthermore, we identified 1–2 optimal locations where new services would maximise accessibility. We utilised open data and publicly available big data. Cali is one of South America's cities most impacted by traffic congestion.Methodology: Using a people-centred approach, we tested a web-based digital platform developed through an iterative participatory design. The platform integrates open data, including the location of radiotherapy services, the disaggregated sociodemographic microdata for the population and places of residence, and big data for travel times from Google Distance Matrix API. We used genetic algorithms to identify optimal locations for new services. We predicted accessibility cumulative opportunities (ACO) for traffic ranging from peak congestion to free-flow conditions with hourly assessments for 6–12 July 2020 and 23–29 November 2020. The interactive digital platform is openly available.Primary and secondary outcomes: We present descriptive statistics and population distribution heatmaps based on 20-min accessibility cumulative opportunities (ACO) isochrones for car journeys. There is no set national or international standard for these travel time thresholds. Most key informants found the 20-min threshold reasonable. These isochrones connect the population-weighted centroid of the traffic analysis zone at the place of residence to the corresponding zone of the radiotherapy service with the shortest travel time under varying traffic conditions ranging from free-flow to peak-traffic congestion levels. Additionally, we conducted a time-series bivariate analysis to assess geographical accessibility based on economic stratum. We identify 1–2 optimal locations where new services would maximize the 20-min ACO during peak-traffic congestion.Results: Traffic congestion significantly diminished accessibility to radiotherapy services, particularly affecting vulnerable populations. For instance, urban 20-min ACO by car dropped from 91% of Cali’s urban population within a 20-min journey to the service during free-flow traffic to 31% during peak traffic for the week of 6–12 July 2020. Percentages represent the population within a 20-min journey by car from their residence to a radiotherapy service. Specific ethnic groups, individuals with lower educational attainment, and residents on the outskirts of Cali experienced disproportionate effects, with accessibility decreasing to 11% during peak traffic compared to 81% during free-flow traffic for low-income households. We predict that strategically adding sufficient services in 1–2 locations in eastern Cali would notably enhance accessibility and reduce inequities. The recommended locations for new services remained consistent in both of our measurements.These findings underscore the significance of prioritising equity and comprehensive care in healthcare accessibility. They also offer a practical approach to optimising service locations to mitigate disparities. Expanding this approach to encompass other transportation modes, services, and cities, or updating measurements, is feasible and affordable. The new approach and data are particularly relevant for planning authorities and urban development actors.

Impact of acute stress on the canine gut microbiota

There is growing evidence that a relationship exists between mental and emotional wellbeing and the gut microbiota. Little is known regarding how the microbiota reacts to repeated acute stress events in dogs, and whether it is a predictor of stress response. In this study, we explored the impact on the gut microbiota and digestive health with two common events many pet dogs find stressful. Twenty healthy adult dogs, living within a colony, were exposed to either car travel or separation three times across eight-week intervals. Faecal samples were collected 24 h before, within 24 h, and 24–48 h after. Faecal quality and pH, and microbiota diversity and composition were analysed in context with wider published work on physiological stress measures. No significant changes were observed in faecal quality or pH with either stress event at any timepoint, indicating all pets remained in good digestive health. Microbiota analysis demonstrated no significant impact on alpha or beta diversity with either stressor. Microbial signatures previously linked to stress were not identified in these dogs and no changes were observed in the functional gut composition. Irrespective of whether the pet was considered “stressed” (i.e., exhibited an increase in serum cortisol), there was no effect on the microbiota and no taxa were predictive of stress response. Collectively, this work demonstrates, for this population, certain acute stress events have no meaningful impact on the canine gut microbiota, and it has no impact on the associated stress response.

Motion sickness whilst reading as a passenger in the car is highly predictive of vestibular migraine.

Vestibular Migraine (VM) is a prevalent vestibular disorder, affecting up to 2.7% of the general population. Despite the establishment of diagnostic criteria by the Bárány Society and its inclusion in the International Classification of Headache Disorders, the clinical diagnosis of VM remains challenging due to its complex pathophysiology and symptom overlap with other dizziness disorders. Motion sickness is a core feature of migraine and can be interrogated through simple questionnaires. This study aims to identify to what extent motion sensitivity can predict VM compared to other causes of dizziness. We conducted a cross-sectional study involving 113 patients from the vestibular neurology clinics at University College London Hospitals. Participants were categorized into VM, Persistent Postural Perceptual Dizziness (PPPD), combined VM and PPPD, and 'other' dizziness etiologies. Data on motion sickness history and dizziness during car travel were collected through structured interviews and analyzed using logistic regression to assess the predictive value of these symptoms for VM. A substantial portion of patients with VM (91.2%) reported nausea or dizziness when reading as a passenger, a symptom significantly more prevalent than in those with PPPD or other dizziness diagnoses. Logistic regression indicated that VM patients are significantly more likely to experience these symptoms compared to non-VM patients, with an odds ratio suggesting a strong predictive value for this symptom in diagnosing VM. The findings highlight increased motion sensitivity while reading in a moving vehicle as a promising diagnostic tool for VM, offering a practical aid in clinical settings to distinguish VM from other vestibular disorders.

Elite hostesses as disruptive forces: the country house in interwar Britain

ABSTRACT British high society in the interwar years was led by a small group of hostesses who were instrumental in heralding consistency after the upheaval of the Great War. Yet, they were also beacons of change, introducing the famous names of the day to each other. Likewise, the country house was entering a period of adjustment as many changed hands or were utilised more often due to the advent of the motor car and quicker travel. This article analyses the role of two hostesses who were at the centre of two of the greatest scandals of the 1930s and argues that the seclusion of the country house was significant to events. Wallis Simpsons role as de facto hostess at Fort Belvedere is explored through the writings of her contemporaries and analysed in the context of the Abdication Crisis. Nancy Astor's role as chatelaine of Cliveden House is explored in relation to her involvement with the Cliveden Set.

A travel time matrix data set for the Helsinki region 2023 that is sensitive to time, mode and interpersonal differences, and uses open data and novel open-source software

Travel times between different locations form the basis for most contemporary measures of spatial accessibility. Travel times allow to estimate the potential for interaction between people and places, and is therefore a vital measure for understanding the functioning, sustainability, and equity of cities. Here, we provide an open travel time matrix dataset that describes travel times between the centroids of all cells in a grid (N = 13,132) covering the metropolitan area of Helsinki, Finland. The travel times recorded in the dataset follow a door-to-door approach that provides comparable travel times for walking, cycling, public transport and car journeys, including all legs of each trip by each mode, such as the walk to a bus stop, or the search for a parking spot. We used the r5py Python package, that we developed specifically for this computation. The data are sensitive to diurnal variations and to variations between people (e.g. slow and fast walking speed). We validated the data against the Google Directions API and present use cases from a planning practice. The five key principles that guided the data set design and production – comparability, simplicity, reproducibility, transferability, and sensitivity to temporal and interpersonal variations – ensure that urban and transport planners, business and researchers alike can use the data in a wide range of applications.

High-speed railway in developing countries: mind the gap -lessons from Morocco-

ABSTRACT Conducted prior to the launch of the High-Speed Railway (HSR) in Morocco, this study aims to be the first research to assess the HSR project through the estimation of the value of travel time savings. We focused on inter-urban routes to assess the HSR project impact. We conducted a Discrete Choice Experiment in the cities impacted (directly or indirectly) by the HSR project, which are Tangier, Kenitra, Rabat, Casablanca and Marrakesh. Our results show that at the sample average points of each mode of transport, the values of travel time savings are approximately 94MAD/h for car users, 27MAD/h for train users and 25MAD/h for bus users. We performed a simulation for the Tangier-Casablanca route and obtained satisfactory results (93MAD/h, 26MAD/h and 24MAD/h, for private car, train, and bus journeys respectively). Finally, our results show that the pricing strategies of the national railway operator (Office National des Chemins de Fer) present a potential risk of eviction, which could counterbalance the positive impact of the time savings.

Pedestrian safety on the road to net zero: cross-sectional study of collisions with electric and hybrid-electric cars in Great Britain

BackgroundPlans to phase out fossil fuel-powered internal combustion engine (ICE) vehicles and to replace these with electric and hybrid-electric (E-HE) vehicles represent a historic step to reduce air pollution and...

Financial determinants of mode substitution in residents’ travel behaviour: a case study of public bike-sharing in Lodz, Poland

Bike-sharing networks have achieved considerable success in many cities worldwide, gaining a growing number of supporters for this mode of transportation. While the existing literature covers various aspects related to bike-sharing, the exploration of the relationship between these networks and the financial benefits for residents when transitioning to cycling has been somewhat limited. Therefore, the main objective of our article is to identify the factors influencing urban residents’ decisions to switch to cycling and to understand the significance of financial considerations in shaping changes in travel behaviour.We assessed the perceived affordability of bike-sharing services by measuring respondent satisfaction (via Computer Assisted Personal Interviews – CAPI) with the rental prices of city bicycles. To examine the relationships between variables, we employed statistical tests, including the Fisher test, the chi-square test of independence, and the Mann-Whitney test. Our research findings confirmed that replacing public transportation with bicycles has the most substantial impact, while substituting car trips has a relatively minor effect. Furthermore, our analysis revealed statistically significant associations between price satisfaction and the decision to abandon car travel in favour of cycling, as well as the motivation to save costs and substituting walking and public transport with bicycle travel.

Beyond the Company Carpool: Disadvantage and Informal Automobile Sharing Within and Between U.S. Households

Planners increasingly recognize connections between traveler constraints, automobile access, and travel behavior. The limited ability to travel via car—for economic or other reasons—greatly reduces mobility for many Americans, who overwhelmingly rely on automobiles for access. Yet public policy efforts to reduce excessive automobile travel often prioritize public transit, ignoring the high rates of private automobile sharing among U.S. travelers. Relatedly, few researchers have studied informal sharing and its relationship with traveler disadvantage, particularly for noncommute trips. To address this research gap, I analyze U.S. trip diary data from 2017. I use multinomial probit modeling to explore the relationship between disadvantage and informal automobile sharing. My definition of disadvantage includes people who have low incomes, travel-limiting physical conditions, and/or limited automobile access. I define several categories of informal automobile sharing to account for different dimensions of interhousehold and intrahousehold sharing. I find that transportation disadvantage is associated with most types of informal sharing, particularly borrowing cars and receiving rides from nonhousehold members. However, trip purpose—particularly noncommute trips—predicts the choice to share better than disadvantage does. Further, trip purpose has a stronger association with sharing among nondisadvantaged travelers. These findings suggest that informal sharing benefits disadvantaged travelers, but social and situational contexts also influence decisions to share transportation. I recommend policies to enhance automobile-based access for low-income travelers, including subsidies for carshare, ridehail, and private car ownership.