Визначення математичної моделі транспортної рухливості населення

The European Union has set a goal of achieving net zero greenhouse gas emissions by 2050, while Finland has committed to reaching carbon neutrality by 2035. To meet these climate targets, it is essential to reduce emissions in the transport sector. While the electrification of vehicle fleets is an important part of this effort, a shift in travel behavior toward more sustainable modes, such as public transport and shared mobility, is also needed. This study investigates whether there is a correlation between public transport travel times and the level of private car ownership in the Helsinki Metropolitan Area. Linear regression is used to examine the correlation between travel times and car ownership, while cluster analysis identifies spatial patterns across the city. The results reveal three main findings: First, areas with higher levels of car ownership tend to have slightly longer public transport travel times, though the relationship is weak. Second, car ownership is marginally higher in areas where car travel itself takes longer - a somewhat counterintuitive result. Third, and most notably, there is a clear positive relationship between the time advantage of car travel over public transport and the likelihood of owning a car. These findings are further reinforced by the cluster analysis, which groups postal code areas into three distinct categories based on travel time differences. One cluster comprises areas with low public transport accessibility and high car ownership; another includes well connected areas with high public transport accessibility and lower car ownership. A third, mixed cluster consists of areas with more moderate values across both measures. These observations indicate that differences in travel time may influence car ownership levels, particularly where public transport is significantly slower than driving. However, the results also suggest that other factors are likely at play, given the relatively weak correlations and some counterintuitive outcomes. Improving public transport accessibility - especially in areas where it currently lags car travel - may be associated with lower car ownership, although this study does not confirm causality. Rather, the analysis provides a foundation for further investigation and offers practical insights for urban planners seeking to promote more sustainable mobility patterns.

The goals of the paper are to study the financing structure of Russian road construction and to identify the contribution share of the vehicles owners in road construction. The conclusion is drawn that most of the roads do not meet the standards, and the negative effects of using a poor-quality road network are analyzed. Besides that the paper analyzes regional imbalances in the level of car ownership and the development of roads. The development dynamics and structure of the road network are analyzed. The authors consider reasons for the slow pace of road network expansion in Russia and look at trends in transport tax revenues and road construction expenditures. It is concluded that there is a number of objective reasons that require far higher spending on road construction in this country in comparison with developed economies. Types of vehicle taxes and fees are studied. It is found that only some of the charges build a link between the amount paid and the intensity of road use by the taxpayer. Sources of government funding for road funds are explored. The research shows that the fiscal and regulatory role of transport tax should be enhanced in regions with medium, high, and very high levels of private car ownership. The authors analyze the possibility of increasing fiscal and regulatory significance of transport taxes and charges. The conclusion that improving the quality of the road network will lead to a reduction in specific fuel consumption and improve the energy efficiency of transportation is justified.

At the beginning of the 1980s, it seemed that a consensus was emerging among researchers that public transport service levels, fares or quality had a small but possibly important effect on car ownership, and that this should be taken into account for those purposes where car ownership forecasts are used for developing policy on public transport or roads. Somehow, the findings faded away, and had little effect on policy thinking or on analytical techniques. The results of six surveys carried out in South Yorkshire over the period 1972 to 1991, during which there were extreme changes in public transport policy, tend to support a prima facie case for reopening the question. At the household level, car ownership rates are shown to be more volatile than is often assumed, especially in multiple car households. This volatility provides a context within which the quality of public transport provision appears to influence both the level of car ownership and the relationship between changes in the level of car ownership and changes in public transport use.

This research aims at establishing a macro-type estimation method of CO2emission from passenger transport at city level, which can consider the difference in car ownership level and transport infrastructure level as a tool for investigating CO2reduction countermeasure in transport sector. At first, the basic formula that describes the mechanism of CO2emission amount is shown, and it is modeling in detail. Changes in fuel economy and CO2emission according to driving situations on roads are included. Estimation and sensitivity analysis are carried out by applying this method to Nagoya city. It enables us to estimate the changes in CO2emission by transport properties, namely frequency distribution of trip length, car ownership and transport infrastructure level.

This paper presents a study of spatio-temporal patterns and city-level determinants of private car ownership in urban China. Car ownership data from 1990 to 2009 were collected from 235 cities of the prefecture-level and above. Panel data models are developed to examine the effects of city's socioeconomic, spatial and transport variables on private car ownership development. We find that car ownership development in Chinese cities has experienced stages of steady and rapid growths in the years before and after 2005; cities of larger sizes as well as in the coastal region have a higher level of car ownership and have experienced much faster growth in the entire period; and the most important determinants of car ownership are economic development related, including gross domestic product per capita and disposable income per capita, which both have positive and significant effects on car ownership in different periods and for different sizes of cities. This study adds to the literature some empirical evidence on the spatio-temporal patterns of private car ownership in urban China and the importance of socioeconomic, spatial and transport-related factors in determining the level of car ownership of cities.

Since the high economic growth period in Japan private motorcars have proliferated in the local cities, where they have become necessities of life for most dwellers today. This paper considers the present state of proliferation by applying some statistical methods to a set of cross-sectional data, an array of transportation and socio-economic variables in 1990 for each of eighty-four medium-sized cities located outside major metropolitan areas (Table 1). In order to solve the problem, the author studies the systematic relationship among the variables or the transportation system. The results may be summarized as follows:First, the eighteen variables on attributes of household, proliferation rate of private vehicle, modal choice in commuting, urban form, road environment and public transit shown in Table 2 were defined as indicators of the transportation system. Using exploratory factor analysis, they were grouped and simplified into five common factors which can be used as sorts of latent variables. The results of the factor analysis are given in Table 3. Of five factors extracted, Factor 5 was not identified even after a promax oblique rotation. Factor 1 was identified as household car ownership, Factor 2 as private traffic generation and traffic restraint, Factor 3 as public traffic generation, Factor 4 as compact car (Kei-jidosha) ownership in suburbs. These four factors correspond to essential elements of the above-mentioned transportation system.Second, for the respective group of key variables comprising each factor, the causal sequence in their internal correlations was examined by means of path analysis to clarify a property of the element. The following became clear after the investigation of the four arrow diagrams in Figure 1 to Figure 4 that show the results of the analysis: (1) The level of household car ownership is influenced by the number of commuters in the household and the family income. In particular the income level has an effect on the proliferation rate of passenger cars. (2) The incidence of traffic accidents is influenced by the model choice of motorcycles in commuting and the level of traffic congestion. This causal relationship is consistent with empirical facts. (3) The level of proliferation of both bus and taxis is influenced by the D.I.D.'s population density. It was proved that the urban form affects the level of public transit service. (4) The level of household compact car ownership is influenced by the proportion of the D.I.D.'s area to the city area. That is, the larger the proportion is, the higher becomes the level.Third, the relationship among elements of the transportation system was illustrated by hypothesizing a causal model for latent variables derived from the factors and then testing it through the multiple indicator method. The results in Table 4 and Figure 5 were obtained empirically, and indicate that three latent variables derived from the first three factors have significant relationships causally. The model represents a link in the chain of the causal cycle in which proliferation of private motorcars causes loss of public transit passengers.Finally, the first latent variable scores for the eighty-four cities were estimated and examined. This latent variable, household car ownership, is a key exogenous one which precedes causally. Figure 6 shows the highest scores to be located in the northern Kanto, the Hokuriku, and the Tokai Districts, the lower ones generally in Northeastern and Western Japan. Furthermore, cities with higher scores are those in which the secondary activities in the economy are of great importance and the increase in population is remarkable (Table 5).

Car ownership level in cities affects the volume of car traffic. So an exact prediction concerning car ownership is important to transportation planning or city planning. The aim of this thesis is to clarify the quantitative relations between the conditions of facilities in cities and car ownership level. The results can be expected to be useful to evaluate city planning from the view point of traffic. Three aspects of the conditions of facilities have been chosen “Road Area per Capita”, “Suburbanization of Inhabitants”, “Population Growth”. Regression analyses have been made using data from 424 cities in Japan. It was found that “Road Area per Capita” effects the car ownership level only in the cities whose “Road Area per Capita” is lower than 50m2 per capita. The elasticities of car ownership level with respect to each three variables have also been clarified.

This article examines intergenerational changes in personal automobile ownership, made possible with the accumulation of sufficient longitudinal data sets. Economic conditions, cultural characteristics, and technological changes affect how each generation perceives and uses automobiles. Analyzing these factors helps to better understand the inequality of opportunity between car-owning and non-car-owning households of past and current generations. Currently, there are no longitudinal studies of intergenerational differences in household car ownership in the national literature. The authors set out to fill this knowledge gap. Cross-country comparative analysis of motorization rates by age cohorts (generations) showed that differences in motorization rates within cohorts between countries or regions within the same country can be explained by the historical aspect of motorization, the level of economic development, and income differences between generations. Given the dynamically growing motorization in Russia, the research question arises: how the provision of personal cars in Russian Federation households changes over time and across generations. The study aims to identify differences in the level of personal car ownership by age groups and between generations using Russian society as an example. In the course of the study, the authors analyzed data on personal car ownership among Russian households obtained from the Russian Monitoring of the Economic Situation and Health of the Population (RMES) of the National Research University Higher School of Economics and the All-Russian Survey of Households on Consumer Finances, organized by the Ministry of Finance of Russia in 2013-2020 and the Bank of Russia in 2022. Using a retrospective method that brings generations to a single age level, the authors investigated intergenerational differences in car ownership. The authors show the dynamics of changes in the share of households owning a car in different generations and at different stages of the life cycle, as well as depending on the place of residence. The tendency to abandon personal cars among young people is revealed. It was found that this is influenced by the practice of carsharing, as well as the quality and availability of municipal transportation in cities, especially large cities. At the same time, the level of private car ownership in rural areas has significantly increased after 2010 and currently exceeds that in urban areas.

What role does free-floating car sharing play for changes in car ownership? Evidence from longitudinal survey data and population segments in Copenhagen

Examining the changes in car ownership levels in the Greater Dublin Area between 2006 and 2011

Car and vehicle ownership levels in developing countries are gradually increasing, leading to traffic congestion, energy consumption, and air pollution. As a developing country, Turkey encounters many of the issues caused by this rapid increase in car ownership. This paper aims to examine potential determinants of household car and vehicle ownership behavior in urban areas of Turkey by concentrating on three cities (Ankara, Erzurum, and Bayburt) that are distinct in population, geographical region, and public transit services. For this purpose, a written survey was administered to 1389 households living in these cities. The data is analyzed using alternative ordered response models—the generalized ordered logit, partial proportional odds (PPO), and heteroskedastic ordered logit models. To the best of our knowledge, this study is the first attempt to compare alternative ordered response models to determine car and vehicle ownership behavior in Turkey. Consequently, the PPO model was found to be the most parsimonious model among the others. The results demonstrated that household car and vehicle ownership behavior in Turkey differs significantly with urban area size. The estimation results also revealed that several key drivers, including type of dwelling, parking availability, household monthly income, and public transit use, significantly influence Turkish households’ car and vehicle ownership levels. This study’s empirical findings may provide insight to policymakers and stakeholders for future transportation strategies and policies.

Commuters’ mobility plays significant roles in urban economic due to its reliance on the cheapest means and available transportation system from one location to another. Commuters’ income in Lagos State affects the number of traffic generated along waterways during travel behavior such as commuters’ occupation and commuters’ level of car ownership. This study aims to estimate the impact of commuters’ income on the ferry operations in Lagos state.
 The research was carried out in four selected waterways terminals in Lagos State. The authors used primary data with the aid of snow balling sampling technique to administered 836 questionnaires at the selected inland waterways terminals in Lagos State. The study used multiple regressions to analyze the obtained data in the study area.
 The result of the findings revealed that majority of the respondents representing 63.9% (523) of the sample size had no car. Furthermore, passenger’s income that was measured using passengers’ occupation and passengers’ car ownership had a significant impact on ferry operational costs in Lagos State having R value of .699 (69.9%) and p-value of 0.000. This shows that ferry operational costs can be determined by passengers’ daily or monthly income.
 The study concluded that increase in mobility demand along waterways can be experienced when traveling cost is minimal compared to other means of transportation. It was recommended that government should subsidize the freight price and come up with a policy that will enforce usage of ferry service.

This paper applies a novel adaptive approach consisting of Artificial Neural Network (ANN) and Fuzzy Linear Regression (FLR) to improve car ownership forecasting in complex, ambiguous, and uncertain environments. This integrated approach is applied to forecast car ownership in Iran from 1930 to 2007. In this study, the level of car ownership is viewed as the result of demographic, politico-social, and urban structure factors including average family size, total population density, urban population density, urbanization rate, gross national product per capita, gasoline price, and total road length. To capture the potential complexity, uncertainty, and linearity relation between the car ownership function and its determinants, ANN and FLR (including eight well-known FLR) approaches are applied to the collected data. Next, the preferred ANN is selected based on sensitivity analysis results for the test data while the preferred FLR is identified with regard to ANOVA and MAPE results. The results obtained from the performance comparison demonstrate the considerable superiority of the preferred ANN over the preferred FLR regarding the nonlinear and complex nature of the car ownership function in Iran. This is the first study that presents an ANN-FLR approach for car ownership forecasting capable of handling complexity and non-linearity, uncertainty, pre-processing, and post-processing.

The determinants of car ownership in England and Wales from anonymous 2001 census data

This literature review is the first to explore the predictors of the ownership, mode choice, and use of private motorcycles for utilitarian travel. Existing literature reviews on motorcycles only focused on the adverse impacts of motorcycle transport. A total of 45 articles in English published up to 2022 from quantitative and qualitative studies were reviewed to identify socioeconomic and built environment predictors of motorcycle travel which can be affected by planning or policy interventions. Motorcycle ownership level of a country is explained by average income, population density, and urbanisation level; that of a province or city by average income; and that of a household by the numbers of adults and workers, car ownership level, income as well as the population density and road density at the residential location. The choice of individuals to use a motorcycle rather than other modes is predicted by income and age as well as the advantages of time and cost savings of motorcycles over other modes. The amount of motorcycle use of households or individuals is associated with the number of household members, car ownership level, the age of the principal user, and income. Supply of public transport should focus on areas prone to widespread motorcycle ownership to both slow down the growth in motorcycle ownership and pre-empt that in car ownership as both types of motorised vehicles bring environmental and public health harms. More research is needed for further understanding of the relationships between motorcycle travel, the built environment, and public transport supply.