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Costs of cars are among the most relevant factors influencing travel behavior. However, there is a lack of data about the true costs of car ownership and specifically on how these costs are distributed across different vehicles and across the population. This paper presents a multistage method for imputing car costs by cost item in a German national travel survey data set. Based on vehicle information reported by survey participants, we assign costs to each of the three thousand cars in the data set using the most comprehensive German vehicle cost data base. In addition to combining different data sets, we use model based imputation methods. In order to validate the average costs for private vehicles we analyze the German income and expenditure survey EVS. The average total cost of ownership for a private car in Germany is about 310 Euros per month. This translates to about 30 Eurocents per auto-km. About one third of the costs are fuel, another third is depreciation, and the rest are other mainly fixed costs (insurance, tax, repair and maintenance). However, the cost distribution is strongly skewed with a long tail to the right. Hence, the majority of motorists pay less than average for their private vehicles while few pay more and evidently some pay a lot more. This imputation approach delivers unprecedented vehicle cost information in particular with regard to the distribution of vehicle costs. Such data is key for understanding the fundamentals of mobility choices.

This paper investigates the contribution of underlying trends to per-capita car travel development since the 1970s in France, Germany, Great Britain, and the USA. In these countries, after a long period of growth, car travel began to show signs of stagnation — or even decrease — after the 1990s. Our paper breaks down underlying demographic and travel trends for two study periods: first, a period of per-capita car travel growth (until the mid-1990s); second, a period of stagnation or decrease in car travel (beginning around the turn of the millennium). Two patterns of development emerge: (1) in France and the USA, the reversal in the trend in car travel per capita was due mainly to trend changes in total travel demand by drivers; (2) in Germany and Great Britain, the levelling off of motorisation, and shifts to other modes, played a much larger role. Ageing has in recent years gained weight in shaping per-capita car travel trends. In Europe, the continued increase of car availability for seniors has had a ...

This study investigates the contribution of the aging of the population and changes in travel behavior by age group to peak car use in France, Germany, Great Britain, Japan, Norway, and the United States. The terms “peak car use,” “peak car travel,” and “peak car hypothesis” have been coined for the recent trend reversal in car travel development observed in some industrialized countries. In the study countries, car travel was characterized by growth for a long time but started to show signs of stagnation or even decrease in the past decade. The authors analyze underlying travel trends since the mid-1990s and use a trend decomposition based on descriptive statistics from national travel surveys and Laspeyres indices. The results indicate that relevant developments have different weight in shaping peak car use in the study countries. In many places, the aging of the population has been an important contributor to peak car use. In Japan, aging was the most important factor limiting growth of car travel. In all study countries except the United States, where car ownership by seniors has not grown, increasing car ownership and car use by seniors have contributed to increasing car travel and thus have exerted a damping influence on peak car use. Another important development was new travel trends of young adults. In three countries, the contribution of young adults to peak car use is crucial: if young adults' car ownership and car mode share had not decreased, results would not have shown declining total car kilometers per capita in Germany and would have shown much stronger increases in Great Britain and Norway.

This paper investigates trends in the travel behaviour of young adults in Germany, France, Great Britain, Japan, Norway, and the USA over the past few decades with a focus on car availability and car travel. The trend analysis relies on micro-data from over 20 National Travel Surveys from the study countries dating back to the mid-1970s. The analysis of the survey data is supplemented by official statistics on licence holding. On this basis, this paper compiles a body of evidence for changes in mobility patterns among young adults in industrialized countries over the past few decades. The findings indicate that since the turn of the millennium, access to cars, measured in terms of drivers' licences and household car ownership, has decreased in most study countries—especially for men. Moreover, average daily car travel distance has decreased in most study countries, again especially for men. In France, Japan, and most significantly in the USA, the decrease in car travel has led to a reduction in total ever...

After decades of growth in motorization and car use, recent trends suggest stagnating travel demand in Germany. This paper focuses on travel trends of young German adults between 18 and 29. For decades these young adults represented one of the most car oriented age groups. Until the 1990s car use increased for all age groups in Germany, including young adults. Based on a range of primary and secondary data sources this paper finds that since the turn of the millennium car use among young adults has decreased. We identify two important underlying trends. First, an increasing share of young drivers also uses alternative modes of transport, thus indicating a rise in multimodal travel behavior. Second, gender differences in car travel have largely disappeared among young Germans—mainly because young men reduced car ownership and driving more than young women. These trends have led to an overall decrease of automobile travel by young adults and contributed to an increase of travel by other modes of transport. Decreasing automobile travel by young adults helps explain the stagnation of aggregate travel demand in Germany, since declining car use among young adults offsets increases in automobile travel of older individuals.

Like other industrialized countries, Germany and Great Britain have experienced increasing motorization over the past five decades. However, results from national travel surveys, vehicle registration statistics, and driver's licensing databases suggest that young Germans and Britons today are less automobile oriented than their parents' generation. The paper sheds light on this trend, with a focus on the group of 20- to 29-year-olds. The analysis finds decreasing car availability, a significant reduction of automobile mileage, increases in the use of other modes, and growing multimodal behavior of the young, with men reducing their automobile travel more than women. Even though the development is more pronounced in Germany, the similarity of the changes in young people's mobility patterns in the two countries is striking. This similarity suggests that the observed changes in travel behavior are not an idiosyncratic development in one country. Instead, the similarity may indicate a structural change in travel behavior that may be found in other Western countries. The paper substantiates findings of changes in trends in mobility patterns of young adults and identifies important storylines of this development on the basis of a harmonized international comparison. Finally, the paper intends to stimulate a discussion and research about reasons for these changes in mobility trends.

Cycling demand has been growing in recent years in Germany. Today, during an average week, about 30% of the German population, including all age classes and rural as well as urban populations, use the bicycle as a means of transportation. Cyclists use their bicycles on average 3 days per week for about 30% of their trips. The bicycle, however, is a mode used for specific segments of everyday travel, particularly short distances, unlike the car, which is almost universal. Hence, cyclists exhibit multimodal travel behavior (i.e., they combine the bicycle with other modes and switch to public transport or the car when the bicycle is not suitable). The domain of the bicycle as a means of transport is a radius around home that on average is about 3 to 5 km, dependent on the urban form. Within this radius, the car with its flexibility is the only serious competitor to nonmotorized modes. For the neighborhood-oriented travel of cyclists, public transport performs well only in specific niches, such as travel at night or commuting to school or university. Here, public transport and the bicycle are competitors. Nevertheless, from a system perspective they are allies: each provides important components for a multimodal mobility tool kit that enables travelers to cultivate mobility that is less automobile oriented.

A 7-day multiagent model of travel demand is presented. Multiday modeling has several strong points and expands the applicability of travel demand models. It allows for incorporating the interrelationship of individual budgets and travel behavior, and the model output provides high flexibility for the further use of the data. Multiday models allow simulation of individual mode use over time and identification of mode clienteles. The challenge of multiday modeling is the realistic representation of behavioral variability and stability and dealing with a large number of possible combinations when generating activity schedules. The presented activity generation approach has two steps: ( a) deriving agendas of intended activities from observed activity schedules and assigning the agendas to the agents in the model and ( b) transforming these agendas to feasible activity schedules with specific activity start times and activity destinations by using a greedy algorithm. This activity generation module was incorporated in a 7-day travel demand model. The model was applied for predicting changes in mode use in the German city of Erlangen caused by demographic development and growth in car ownership within the next decade.

Specific information about travelers’ activities is often vital for transportation planners. For example, in modeling destination choice should only those attractions where a desired activity can be pursued be included? Destination choice modeling may improve when more specific activity information is available, especially for leisure trips. Destinations for leisure trips can be places to visit people, cinemas, and restaurants. In surveys, however, respondents are often asked to categorize their trips into generic purposes such as work, shopping, or simply leisure, without specifying the leisure activity. Hence, there is often a gap between trip-purpose information elicited from respondents and specific activity information, which would enhance destination modeling. A model is presented that bridges this gap with respect to leisure activity engagement. Common experience provides an idea of who is likely to conduct a particular leisure activity and at what time. The approach taken here was to quantify this likelihood by evaluating a data set of more than 20,000 leisure trips that provided specific activity information. This provided the calibration for the model IRMA, which simulates a specific activity for each trip based on trip-context data. IRMA was applied to model activities for leisure trips in a data set from Tuebingen, Germany. The result of the application of IRMA was consistent with common experience and provided vital activity information that helped to improve destination choice modeling. The approach to infer activity information from available trip data has proven useful in bridging the gap between information that is needed and information that is available.