Private Car Use Research Articles

“Everyone Wants to Drive There”: Challenges to Transport Sustainability in Rural Tourism Destinations

ABSTRACTUnderstanding transport challenges is inevitable for transitioning to a low‐carbon rural tourism future. Using social representation theory, this study examines how tourism and transport practitioners perceive transport challenges in rural destinations and how they overcome these problems. The multi‐method qualitative approach adopted involves semi‐structured interviews with practitioners, participant observation, and document analysis in the Swedish destinations of Åre and Sälen. Findings reveal social representations of transport challenges at both destinations, namely, “a car‐dependent society”, a “non‐desirable transport future” and “wicked transport problems”. Practitioners in these places address these challenges in several ways. Surprisingly, one solution is to promote flying to the destinations. This particular solution, not to mention the destinations' overreliance on private automobile use illustrates that they have not yet begun transitioning to a low carbon transport future. This situation highlights the urgency to encourage sustainable mobility development to and within these destinations.

Enhancing last mile connectivity using shared mobility: A stated preference survey of business park commuters

An important step towards more sustainable transport is to reduce the use of private cars. There is a significant unrealized potential of replacing car-based commute with public transportation, especially to and from business parks where many people are co-located, and where the use of private cars are quite common. This study examines the potential of shared mobility solutions to enhance the appeal of public transportation by addressing the last mile challenge. Various types of shared mobility are evaluated and compared in a stated preference survey conducted at the Sluppen business park in Trondheim. Results show that more people may choose the bus if there is a shared mobility solution available to complete the last mile of the commute. The respondents prefer e-scooters if there is no extra cost, but to a lesser degree if they must pay 20NOK. Car commuters who are willing to shift to from car to public transport and shared mobility, are also more willing to both wait and pay extra for a shuttle.

EV charging load forecasting and optimal scheduling based on travel characteristics

Accurate prediction of EV charging load distribution is not only the basis of evaluating the capacity of distribution network to receive EV, but also the necessary premise to promote the research of charging station planning and vehicle-network interaction. Based on this, firstly, according to the travel characteristics of electric private car and taxi users, this paper constructs the models of speed-flow and EV power consumption per mileage, thus, the real-time changes of vehicle speed and power consumption per mileage are simulated. Secondly, consider factors such as charging price, time, and power consumption along the way, as well as multiple sources of information such as traffic networks, vehicles, public quick charging stations, and distribution networks, the OD matrix analysis method is introduced to simulate EV moving characteristics for EV trip assignment matrix, and the EV charging load forecasting system with real-time interaction of multi-source information is established. Finally, the second-order cone optimization method is used to optimize the space-time distribution of regional charging load. The model and method proposed in this paper are more consistent with the actual situation and can improve the accuracy of prediction.

Investigating work commuters mode choice behavior in Dalian city during pandemic: a hybrid choice model approach

ABSTRACT This study examined commuters' mode choice behavior during the COVID-19 pandemic, focusing on the impact of both tangibles and intangibles factors. To do so, the authors developed a Hybrid Choice Model (HCM) which investigated the effects of sociodemographic characteristics, travel attributes, and intangible factors such as satisfaction, safety, and discomfort, on travel behavior. The model was tested using Stated Preference data collected from commuters in Dalian City (China) via wenjuanxing, an online survey platform. The results indicate that individual characteristics played a significant role in shaping people's perceptions and mode choice behavior was influenced by sociodemographic factors, travel characteristics, and the aforementioned intangible factors. More specifically, individuals, who perceived a higher level of safety, measured in terms of worries about robbery, accidents, and pandemic concerns, were less likely to choose cars. People with a stronger perception of discomfort favored metro over bus. Private car users reported higher satisfaction. The findings will be useful to policymakers for establishing more resilient transport solutions.

An investigation of perceived risk dimensions in acceptability of shared autonomous vehicles, a mediation-moderation analysis

The integration of shared and autonomous mobility has led to the emergence of shared autonomous vehicles with ride-sharing services (SAVWRS), which have the potential to significantly reduce private car usage and promote sustainable transportation. Despite numerous studies on this topic, there is still no research examining the impact of all dimensions of perceived risk theory on usage intention. Therefore, we aim to investigate these relationships and gain deeper insights by examining the mediating effect of trust and the moderating effect of generation (Millennials vs. Baby Boomers) to address potential disparities across generations. To gather insights, we design an online survey that was completed by a random sample of 723 individuals in 2021. The estimation results of the structural equation model reveal that all perceived risk dimensions (social, performance, time, physical, security, and financial risks, in descending order) are negatively related to consumers’ intention. Additionally, trust fully mediates the relationships between performance, physical, financial, and security risks and usage intention, whereas it partially mediates the relationships between social and time risks and the intention to use. Furthermore, moderation analysis revealed that Millennials are less concerned about most dimensions of perceived risk theory, except for social and time risks. In conclusion, our study contributes to a deeper understanding of the complex relationships between perceived risk dimensions, trust, and usage intention in SAVWRS. Our findings suggest that policymakers and industry stakeholders should consider strategies to address these concerns to promote widespread acceptance of SAVWRS.

A dynamic discrete choice modelling approach for forward-looking travel mode choices

In this paper, we present a systematic approach based on dynamic discrete choice models (DDCM) to investigate individuals’ forward-looking mode choice behaviours in daily travel tours with multiple destinations. We propose a novel network transformation model that encompasses the entire decision space of all feasible mode combinations for every observed trip/tour in the dataset. By applying the well-established Recursive Logit model structure commonly used in path choice modelling, we address the tour mode choice problem effectively and quantify forward looking considerations in the mode choice process. The proposed model captures the complex considerations individuals take into account when making mode choices. The network transformation incorporates downstream mode limitations into the preceding mode choice options, enabling us to model individuals’ forward-looking behaviour and gain insights into how considerations of future trips such as a shopping in the evening, or school pick-up trip influence previous mode choice decisions earlier in the day. Uncovering and quantifying these hidden forward-looking factors can help modellers better explain the private car usage usually observed for the entire sequences of daily trips, even in presence of competitive alternative modes. The proposed network transformation also enables us to measure the effect of the requirement/preference to return private vehicles (car, motorcycle, and bicycle) home on mode choices in home-bound trips, and subsequently, on the entire daily mode choice decisions. To validate the proposed model, we utilise the VISTA household travel survey data from the Melbourne Metropolitan area in Australia. The model is compared against baseline models, demonstrating its statistical advantages. Additionally, intuitive illustrations using the data showcase the model’s efficacy. From transport planning and policy perspective, tour-based mode choice modelling provides a more comprehensive and precise understanding of travel behaviour by considering the sequence of trips made by an individual. This can help capture the interactions and dependencies between different trips, which trip-based models may overlook. The proposed model is more suitable for analysing the effects of policy interventions like congestion pricing, public transport investments, or new mobility initiatives, as they can better represent the cascading effects of such policies across multiple trips.

But can it drive to Lapland? A comparison of electric vehicle owners with the general population for identification of attitudes, concerns and barriers related to electric vehicle adoption in Finland

Transportation is a major source of greenhouse gas emissions with private car use accounting for a large proportion of those emissions. Battery powered electric vehicles (EV) are a currently available technology that has the potential to significantly reduce emissions from car use. Therefore, promoting a shift from internal combustion engine vehicles to EVs should be supported by policy makers aiming to curtail emissions from car use. To design policies and interventions to promote EV adoption, information is needed on how people perceive electric vehicles and what are the real and perceived barriers preventing their adoption. With this objective in mind, it was investigated what the current EV owners in Finland are like and how they compare with the general population. We also endeavored to identify real as well as potentially misperceived barriers to EV adoption and factors affecting EV purchasing intentions. The study utilizes a sample of 3857 participants, including 141 electric car owners, who answered a questionnaire investigating lifestyle, car use, environmental and political attitudes as well as household carbon footprint and attitudes towards EVs. EV owners in Finland have more financial security, own more cars, drive more, and have a larger average household carbon footprint than the general population. There are two distinct subgroups among electric car owners, one group being interested in environmental impact of their car use and the other focused on the performance of their cars. People without experience of EVs generally have negative attitudes towards electric cars and also maintain some misconceptions about EVs. Personal experience with electric vehicles is associated with a positive outlook on these types of vehicles and is the strongest predictor of EV purchasing intentions.

Influence factors on travel mode preference of working residents living far away from downtown area on workdays: A hybrid method integrating random parameter logit model and Apriori algorithm

This study presents a detailed analysis on the characteristics of travel mode preference of working residents living far away from downtown area on workdays, using GPS-based activity travel diary data from Shangdi area (Beijing). A hybrid method integrating random parameter logit model with systematic heterogeneity (RPL-SH) and Apriori algorithm is put forward to explore the influence factors and interaction effects affecting travel mode preference. First, the RPL-SH model is established to explore significant factors, and capture the unobserved random heterogeneity and systematic heterogeneity due to individual characteristics on the travel mode preference. Then, these significant factors are used to generate association rules by Apriori algorithm to investigate statistical associations between the specific travel mode preference and these significant factors. Ten significant factors are found in the RPL-SH model, in which annual household income is normally distributed. The results of the Apriori algorithm indicate that some factors combined with other factors could significantly influence working residents’ travel mode preference. For example, the combination of lower annual household income and shorter distance between workplace and the nearest bus stop is highly associated with green travel mode preference. Moreover, the results show that the proposed hybrid method not only demonstrates the consistency of the results of the two methods, but also plays a complementary role in exploring more information on travel mode preference. This research hopes to give regulators a better understanding on how working residents living far away from downtown area choose their travel mode, so as to develop more effective and targeted measures for reducing private car use and alleviating workday traffic congestion.

Decoding Jakarta Women’s Non-Working Travel-Mode Choice: Insights from Interpretable Machine-Learning Models

Using survey data from three dwelling types in Jakarta, we examine how dwelling type, socioeconomic identity, and commuting distance affect women’s travel-mode choices and motivations behind women’s choices for nearby and distant non-working trips. We compared the performance of the multinomial logit (MNL) model with two machine-learning classifiers, random forest (RF) and XGBoost, using Shapley additive explanations (SHAP) for interpretation. The models’ efficacy varies across different datasets, with XGBoost mostly outperforming other models. The women’s preferred commuting modes varied by dwelling type and trip purpose, but their motives for choosing the nearest activity were similar. Over half of the women rely on private motorized vehicles, with women living in the gated community heavily relying on private cars. For nearby shopping trips, low income and young age discourage women in urban villages (kampungs) and apartment complexes from walking. Women living in gated communities often choose private cars to fulfill household responsibilities, enabling them to access distant options. For nearby leisure, longer commutes discourage walking except for residents of apartment complexes. Car ownership and household responsibilities increase private car use for distant options. SHAP analysis offers practitioners insights into identifying key variables affecting travel-mode choice to design effective targeted interventions that address women’s mobility needs.

Who is ready to live a car-independent lifestyle? A latent class cluster analysis of attitudes towards car ownership and usage

An excessive use of private cars for transportation has multiple negative effects on our society. It is therefore paramount to identify the underlying factors driving car usage among different segments of travellers. In this study, we aim to identify and characterise traveller segments in terms of their car-related attitudes and how different sociodemographic attributes, travel behaviour characteristics (such as using cars as the primary mode of transportation), and the accessibility of their place of residence vary amongst different population segments. Through Confirmatory Factor Analysis and Latent Profile Analysis we identify five different classes, namely car-detractors, −hesitants, −positives, −friends, and −lovers. More favourable car attitudes are associated with higher car ownership and access but, interestingly, there are no significant differences in terms of travel frequency and trip length distribution. This suggests that attitudinal differences relate mostly to modal preference rather than to the underlying travel demand patterns and the associated activities. We also see that car-less individuals are more likely to be car detractors, suggesting that the experiencing barriers for owning a car may contribute to developing more negative attitudes towards cars. Our results shed light on the different influencing factors and characteristics of individuals that consider, or not, a car-centred mobility.

Evaluating private car users’ preference to congestion pricing: A study on trip cancellation behavior

People show different behaviors when facing congestion pricing policy. A literature review reveals that the variables affecting behaviors such as trip cancellation in the case of the implementation of transportation demand management (TDM) policies have received less attention. Therefore, the present study aimed to investigate the effects of travelers’ characteristics, citizens’ attitudes towards TDM policies, socioeconomic variables, and five TDM policies on trip cancellation behavior among private car users entering congestion charge zones. The statistical population contained 2256 participants; each participant answered six scenarios resulting in 13,536 observations. The use of Stated Preference method is employed to identify the preferences of citizens of Shiraz as a case study. The binary logit model indicated that travelers who had to make essential trips would be less likely to cancel their trips. Also, those who strongly agreed with the idea that congestion pricing could restrict their travel mode choice and those who strongly disagreed that congestion pricing could reduce traffic congestion would be most likely to cancel their trips compared to people with other attitudes. In addition, every minute increase in the time spent in congestion charge zones could decrease the travelers’ tendency to cancel their trips by 0.13%. Likewise, every 10,000 Rials ($0.09) increase in congestion charge could increase the probability of trip cancellation by 0.31%.

Determinants of spatiotemporal changes of land use carbon emissions for counties in Shaanxi Province, China.

In China, urban sprawl and developed land expansion challenge the country's "carbon peak" and "carbon neutrality" goals. Counties as the basic governance units arecrucial for effective carbon reduction policies. This study examines land use carbon emissions (LUCE) in Shaanxi Province at the county level, essential for China's low-carbon strategy. Analyzing data from 107 counties between 2000 and 2020, we found that developed land, though increasing, is the primary carbon source with a slowing growth rate. The Conversion of Cropland to Forests and Grasslands national policy mitigated the impact on carbon absorption. Carbon emissions displayed positive autocorrelation and spatial heterogeneity, varying across the region. Using the Spatial Durbin Error Model, we linked county-level emissions to GDP per capita, population, urbanization rate, and research and development expenditure for direct and indirect influence. These factors correlate with fossil fuel use and high-quality industrial development. Promoting public transits and reducing private car use are vital for achieving local and regional low-carbon goals.

Exploring parental decision-making in school commutes: A structural equation model of public transport utilization and child safety in Thailand

Concern is growing regarding the increasing use of private car in many developing countries, including Thailand. Car usage is rising in Thailand in part because the public transit system is inadequate and unreliable, especially in rural and suburban communities. Often, children’s route to school is unsafe due to the increasing number of cars around the school. This prompts parents to worry about their child’s safety when in transit. The model of travel by public transportation is an alternative for reducing road congestion and improving children’s safety. This study seeks to better understand the factors that influencing parents’ decisions regarding the use of public transportation for their children’s school commutes. Data were gathered through a questionnaire from a sample of 750 parents with children between the ages of 6 and 18 years in Nakhon Ratchasima Province, Thailand. The findings of the structural equation model analysis showed a relationship between service users’ loyalty and the components of satisfaction, trust, expectation, and perception of service quality. The outcomes derived in this study can serve as practical guidelines for public and private transportation system operators to improve service efficiency, meet consumer demand, and foster positive interactions between service users and operators. In this way, this study can lead to important internal and external benefits for the continued development of the public transportation system and motivate more service users to transition to the use of public transportation.

The impact of public transport priority policy on private car own and use: A study on the moderating effects of bus satisfaction

China started implementing a public transport priority policy in 2004 to encourage people to use public transit, especially buses, and reduce reliance on private cars. This paper used 334 questionnaire survey data from Changzhou City, China, and explored the moderating role of bus satisfaction based on the examination of the antecedents and consequences of affective motivation for private cars through two studies. Study 1 explored the antecedents of affective motivation for private cars and the moderating effect of bus satisfaction. The empirical results revealed that instrumental motivation is the most relevant predictor of affective motivation favoring private cars, followed by symbolic motivation. The moderating effect of bus satisfaction on the relationship between symbolic motivation and affective motivation was significantly negative. Study 2 explored the consequences of affective motivation for private cars and the moderating effect of bus satisfaction. Empirical results indicate that decisions regarding private car ownership and use are significantly negatively influenced by bus satisfaction. Bus satisfaction has a significantly positive moderating effect on the relationship between affective motivation and private car ownership and use. The marginal effect of bus satisfaction on the probability of simultaneously owning and using private cars is significantly negative, and it strengthens the influence of affective motivation in promoting both ownership and use of private cars. These results demonstrate that for individuals with experience using both buses and private cars, the public transport priority policy focused on improving bus service quality can effectively reduce private car ownership and use. These results can serve as evidence to support policymakers in continuing to enhance the public transport priority policy.

Assessing the spatial transferability of mode choice models: A case of shared electric mobility hubs (eHUBS) in Amsterdam and Manchester

Electric mobility hubs (eHUBS) represent an innovative approach to providing diverse shared electric transportation options, aimed at curbing private car use, and mitigating associated environmental impacts. Assessing the impact of eHUBS on travel choices across different cities requires significant resource and time investment due to the need for localized data collection and model development. This paper proposes a potential solution to this challenge by investigating the transferability of mode choice models originally developed for eHUBS in Amsterdam to predict behaviour towards eHUBS in Manchester.Multinomial Logit (MNL) and mixed logit models were transferred using four different procedures, and their effectiveness was evaluated using three assessment measures. The findings indicate that a scaled mixed logit model with an updated Alternative Specific Constant (ASC) outperforms other models in terms of its transfer effectiveness, both for disaggregate and aggregate assessment measures. The interplay between transfer procedures and assessment measures also was examined, with results indicating enhancements in disaggregate transferability measures with the 'scaling' transfer procedure, while 'updating the Alternative Specific Constants (ASCs)' improved predictions of aggregate mode shares. Following the analysis, the paper presents an in-depth discussion to provide a nuanced understanding of transferability and thus offers valuable insights for researchers planning future studies and practical considerations for policymakers.

Do we accurately measure what we consume?

Understanding how consumption patterns affect the environment and shape well-being hinges on the rationale that the data collected on what is consumed, who consumes it, and where it is consumed are indeed accurate. To identify these consumption patterns and recommend corresponding policies, researchers and policy makers often rely on national surveys. Studies have explored the accuracy of individual surveys and the level of agreement across surveys of the same type (e.g. household expenditures), but no studies have compared representative national surveys measuring consumption in different ways. This study compares household consumption measured as expenditures and as material consumption (i.e. physical units) to assess how well we currently measure what we consume. We use multiple rigorous, national surveys to estimate meat consumption, household energy use, and private automobile use in the United States, with consumption profiles parsed by affluence, race/ethnicity, and education. Our results indicate that commonly used surveys may not accurately track important aspects of household consumption. For meat consumption, which included 30 consumption profiles detailing the consumption patterns across different demographic characteristics and meat types (e.g. kilograms beef consumed/capita for Caucasians), there is considerable disagreement between data sources for 20 profiles. By contrast, national surveys accurately measure household energy and transport (disagreement for four profiles). Our findings indicate that national surveys more accurately measure consistently tracked, standardized consumables like electricity than irregularly tracked, variable goods such as food. These results cast doubt on studies that use national surveys to draw conclusions about the how the environmental impacts of food, and, potentially, other goods (e.g. manufactured goods) vary across demographic groups. Overcoming this challenge will necessitate new surveys, updating legacy databases, and harnessing breakthroughs in data science.

Exploring the role of Mobility-as-a-Service in morning commuting trips

Promising the seamless integration of multiple transportation modes, Mobility-as-a-Service (MaaS) has gained popularity over the years, yet its effectiveness in enticing private car users and improving travel efficiency remains uncertain. This study explores the competitiveness of MaaS-enabled multi-modal travel options versus private car usage through equilibrium analysis. In addition to pricing that affects the fixed cost for travel, we examine the often overlooked inconvenience cost associated with multi-modal trips. We establish our analysis for the commuting problem of a one-origin-one-destination network, where a highway and a mass transit line connect the residential area and the central business district (CBD) area. Travelers choose their departure time and travel mode among auto, Park-and-Ride (PnR), ride-hailing and transit (RnT) to minimize their total travel cost. Inconvenience costs associated with searching for parking and waiting for ride-hailing are explicitly modeled. We analytically provide the mode share and departure time windows under all possible equilibria. Our findings reveal the complex nature of mode choice, distinctly affected by fixed and inconvenience costs, with demand playing an even more significant role. Notably, fixed costs set an entry fee to adopt different modes, and the feature of inconvenience costs affects the utilization of available transportation resources. More importantly, to benefit the overall system, we encourage maintaining a balanced mode share by implementing pricing and capacity strategies rather than aiming for a completer transition of private car users to MaaS.

Modal shift, environmental benefits and population exposure assessment on contingent transport policies

Transport policies targeting emission reduction and air quality improvement typically discourage private car use and promote shifts to mass transit (bus, metro). However, possible increase of travelers’ exposure while adapting to those policies have often been overlooked, which is addressed in this work via a case study of Heavy Pollution Episodes (HPEs) in Chengdu, China, using city-scale traffic camera and transit ridership data. By investigating traffic fluctuation and modal shift under prolonged license plate rationing for private cars and free or discounted fare for mass transit, we show that the reduction of small car traffic was marginal (up to 2.3 % in 24-hour periods), which, environmental benefits wise, is negligible according to air quality modelling. Meanwhile, over 3.23 % of car users switched to mass transit during Orange-level alerts, with a higher degree (by 19 %–39 %) of exposure to PM2.5. Our findings highlight the importance of exposure-centric decision making during HPEs.

High-Profile Convoy Disruptions: Exploring Socioeconomic and Environmental Ramifications of Road Closures

Congestion persists despite various demand management techniques, particularly for handling recurrent congestion. However, non-recurrent congestion from events like VIP movements poses unique challenges, especially during peak hours. This study investigates the environmental and economic impacts of road blockages due to VIP movements in developing countries, focusing on Pakistan. Considering practiced standard operating procedures associated with VIP movements, this study finds significant delays and economic burdens in debt-ridden economies. It uses discrete choice modeling and microsimulation techniques to evaluate the value of travel time and quantifies road blockage effects on fuel consumption, travel time, and carbon emissions. Data from central blockage locations in Rawalpindi and Islamabad reveal a value of travel time estimated at 1.77 USD/h, with income and gender significantly influencing mode choices during VIP movements. Moreover, road blockages exceeding two minutes substantially negatively impact the environment and economy, particularly in developing nations. Urgent action is needed for effective mitigation strategies and sustainable transportation policies to address the detrimental effects and promote alternative transportation modes. Recommendations include limiting VIP blockages to a maximum of two minutes and implementing policies to discourage private car usage. Despite limitations, the study emphasizes the critical role of sustainable transportation policies in enhancing the well-being of road users in developing nations.

Assessing the Link between Maternal Transport Modes and Childhood Mortality in Nigeria

ObjectivesThe study explored the association between maternal transport modes and childhood mortalities in Nigeria.MethodUtilizing data and definitions from the 2018 Nigeria Demographic and Health Survey report, the ten-year early mortality rates of the five childhood mortalities and the percentage of live births in the 5 years before the survey, transported by eight identified means of transportation, were statistically correlated for each of Nigeria’s 36 states and the federal capital territory (FCT) in the R environment at a significance level of α < 0.05.ResultsIn the spatial distribution of the five childhood mortalities, a notable north-south dichotomy was observed, contrasting with the spatial spread of maternal transport modes. The five childhood mortalities exhibited a significant, moderately positive correlation with transportation by Private Car or Truck, while their associations with Public Transport or Bus and Walking were notably moderate but negative.Conclusion for PracticeWhile the use of private cars or trucks should be encouraged as a means of maternal transport, public transport should be better organized to provide efficient services to women who need such services for maternal and child healthcare. Additionally, steps should be taken to reduce travel distances to health facilities to manageable distances for mothers.