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OpenStreetMap (OSM) data are geographical data that are easy and open to access and therefore used for a large set of applications including travel demand modeling. However, often there is a limited awareness about the shortcomings of volunteered geographic information data, such as OSM. One important issue for the application in travel demand modeling is the completeness of OSM elements, particularly points of interest (POI), since it directly influences the predictions of trip distributions. This might cause unreliable model sensitivities and end up in wrong predictions leading to expensive misinterpretations of the effects of policy measures. Because of a lack of large-scale real-world data, a detailed assessment of the quality of POI from OSM has not been done yet. Therefore, in this work, we assess the quality of POI from OSM for use within travel demand models using surveyed real-world data from 49 areas in Germany. We perform a descriptive and a model-based analysis using spatial, demographic, and intrinsic indicators for two common trip purpose categories used in travel demand modeling. We show that the completeness of POI data in OSM depends on the category of POI. We further show that intrinsic indicators and indicators calculated based on data from other sources (e.g., land use or census data) are able to detect quality deficiencies of OSM data.

This study uses a unique dataset on the cost of motoring in Germany to analyse cost competitiveness of emerging mobility-on-demand (MOD) services. Previous studies have focused on comparing current and projected MOD prices with the average cost of private motoring. This study quantifies which proportion of private car travel would actually turn out to be costlier than MOD given that MOD costs drop below certain levels relative to the cost of private motoring. In this context, not the average but the distribution of the costs of motoring are the key issue. These costs are strongly skewed across the cars in private households when including new and old vehicles: a large proportion of private car kilometres are driven at relatively low cost. The study uses simplified scenario settings with MOD price levels ranging from 0.1 €/km to 1.5 €/km to make predictions of hypothetical modal shifts under the assumption that car user switch to the most economic mode of travel. These modal shifts serve as an indicator of MOD cost competitiveness. The results indicate that MOD prices would have to drop to 0.5 €/km or lower to have a notable impact on use of the private car if cost was the key mode choice criterion. Only if MOD prices drop down to a level of about 0.3 €/km—quite possibly a lower boundary for automated MOD—MOD-enabled mobility packages would be the less costly alternative to the private car for a substantial proportion of mileage. However, even at that MOD price level, the private car would still be the most economic option for the majority of today’s car user kilometres. Our findings illustrate that the skewed distribution of the cost of owning and running private cars—where many of those who drive much drive inexpensively—substantially dampens the disruptive potential of MOD. While we use data from Germany to illustrate this, many of our findings are more widely applicable.

Fur die kommenden Jahrzehnte gehen nahezu alle Verkehrsprognosen, die keine deutliche Kehrtwende in den Rahmenbedingungen zugrunde legen, von einem weiteren Wachstum der Gesamtverkehrsnachfrage im Personen- und Guterverkehr aus. Diese Entwicklung wird auch den Stadtverkehr pragen, der zusatzlich durch eine zunehmende Konzentration der insgesamt alternden Bevolkerung in prosperierenden Metropolregionen gekennzeichnet sein durfte. Wichtige weitere ausere Einflusse sind auch Digitalisierung und Automatisierung. Sie lassen eine weitere Ausweitung der Angebotsformen im Verkehr erwarten, die voraussichtlich ebenfalls zu Verkehrswachstum beitragen. Damit bleiben Platzbedarf, etwa fur den ruhenden Verkehr, Energieversorgung und Emissionen des Stadtverkehrs drangende Herausforderungen. Mit zunehmender Multimodalitat und einer Renaissance des Fahrrads gibt es aufseiten der Nachfrage zwar auch entlastende Entwicklungen. Dennoch durfte vor dem Hintergrund des weiter wachsenden Verkehrs die langfristig groste Herausforderung fur den Verkehrssektor die Einhaltung der Klimaziele sein. Verkehrspolitik und -planung werden sich in den nachsten Jahren verstarkt an diesen Zielen orientieren mussen und hierzu alternative Verkehrstrager fordern und moglicherweise daruber hinausgehende Masnahmen, wie etwa differenzierte Bepreisung des Strasenverkehrs, ergreifen.

Vehicle kilometers travelled (VKT) directly reflect the extent of spatial interaction within society and economy. VKT is also a key figure to quantify the use of road infrastructure. Consequently, VKT is one of the most important statistical indicators in traffic and transport. For a country with substantial cross-border transport relations such as Germany, VKT must be differentiated in national and domestic VKT: national VKT is the mileage of vehicles registered in Germany while domestic VKT is the mileage on German territory by German and foreign vehicles. This paper presents the most current German VKT survey, Fahrleistungserhebung (FLE) 2014, which comprised two elements: a motor vehicle owner survey to measure national VKT and traffic counts to measure domestic VKT. Vehicle mileage figures with deep stratification of both national and domestic VKT can only be generated through such special empirical studies. The focus of this paper is on the vehicle owner survey and national VKT.

Adopting new methods in large longstanding surveys, such as National Travel Surveys, is associated with specific challenges. Aside from methodological issues, the continuation of time series and data that is usable for many, are important concerns. Multi-mode surveys are becoming common place and new methods are run in parallel to established methods. This improves survey representativeness but there are new challenges, for example mode effects. The introduction and spread of smartphone use in surveys and emerging methods for recruiting survey participants will add to this complexity. As survey methods evolve, data post-processing and statistical methods have to keep up as well.

Over the past few years, many studies have provided detailed descriptions of the potential benefits associated with the introductionof autonomous vehicles, such as improvements in traffic flows, local and global emissions, traffic safety, cost efficiency of public and private transport operations, etc. Additionally, the mobilization of mobility-impaired people and the independent car use of travelers without a driver’s license have been identified as potential benefits for users. However, merely estimatingthe benefits of these direct (or first-order) effects is unlikely to show the full picture of the consequences that will emerge once autonomous vehicles enter the roads. In this paper, wetherefore put emphasis on discussing systemic (or second-order) effects. The paper presents a conceptual exploration of these effects based on literature and research findings to date. We show that these systemic effects have the potential–especially in urban areas and without adequate policy intervention–to eliminate at least some of the benefits initially associated with autonomous vehicles. Following this systemic view on autonomous vehicles, we discuss policy aspects for responsible authorities and planners on how to prepare transportation systems for the challenges related to the introduction of autonomous vehicles, and conclude with areas of research that seem highly important in terms of further investigation in this context.

Walking and cycling—active travel—can help adults achieve the World Health Organization’s recommended 150+ min of moderate-intensity aerobic physical activity per week. Based on a nationally representative panel-survey of daily travel in Germany, this study assesses weekly minutes of active travel by adult respondents participating in a weeklong survey in two consecutive years. The paper first identifies person-level covariates for achieving 150+ min of active travel during a week in year 1 of panel participation. The analysis then compares the patterns of individuals falling into four groups of active travel over the two survey years: ‘high maintainers’ who achieved 150+ min in both year 1 and year 2; ‘low maintainers’ who did not achieve 150+ min in neither year 1 nor year 2; ‘adopters’ who did not achieve 150+ min in year 1, but did so in year 2; and ‘relapsers’ who achieved 150+ min in year 1, but not in year 2. About half (48%) of respondents achieved 150+ min of active travel per week in their first year of panel participation. Of those, about three-quarters were ‘high maintainers’ with 150+ min of active travel in both years. Logistic regressions showed that ‘high maintainers’ were more likely to be 30 years or older, not employed, have a monthly public transport pass, live within 2 km of a shopping destination, and less likely to own cars. Transport and land-use policies can help influence several of these factors. Compared to ‘low maintainers,’ policy interventions to increase population shares achieving health-enhancing levels of physical activity from active travel may be most promising when targeting ‘adopters’ and ‘relapsers.’ These groups are more similar to the ‘high maintainers,’ with at least one year reporting of health-enhancing physical activity from active travel—compared to the ‘low maintainers.’

This paper, for the first time, presents comparable projections of travel behaviour impacts of the introduction of autonomous vehicles (AVs) into the private car fleet for two countries, namely the USA and Germany. The focus is on fully autonomous vehicles (AVs) which allow drivers to engage in other activities enroute. Two 2035 scenarios – a trend scenario and an extreme scenario – are presented for both study countries. For these projections, we combine a vehicle technology diffusion model and an aspatial travel demand model. Factors that influence AV impact in the behavioural model are mainly new automobile user groups, e.g. travellers with mobility impairments, and altered generalized costs of travel, e.g. due to a lower value of travel time savings for car travel. The results indicate that AV penetrations rates might be higher in Germany (10% or 38% respectively) than in the USA (8% or 29% respectively) due to a higher share of luxury cars and quicker fleet turnover. On the contrary, the increase of vehicle mileage induced by AVs is not higher in Germany (+2.4% or +8.6% respectively) than in the USA (+3.4% or +8.6% respectively). This is mainly due to the lack of mode alternatives and lower fuel costs resulting in a higher share of travel times among the total generalized costs of travel in the USA. These results clearly indicate that context factors shaped by national policy will influence AV adoption and impact on travel demand changes. Based on these results the paper draws policy recommendations which will help to harness the advantages of AVs while avoiding their negative consequences.

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.

There are high expectations on autonomous vehicles promising a safer, more efficient and comfortable (auto)mobility experience. On the other hand it is important to discuss possible rebound effects going along with such a development. New user groups e.g. people who do not hold a driving license today, or are currently unable to drive because of physical and/or age-related constraints suddenly are enabled to “drive” a passenger car. In addition the past has shown that increasing efficiency and enhancing the comfort leads to a higher travel demand and subsequently more vehicle miles traveled. To support the research on the impact of autonomous vehicles on the transport system it is important to analyze the potential share of autonomous vehicles (AVs) on the passenger vehicle fleet in the future. The paper presents results from modelling private autonomous vehicle scenarios for the year 2035 for Germany and the US to estimate the number of vehicles within the fleet equipped with automation technologies Level 4 and higher (SAE in SAE International Standard J3016, 2014). A vehicle technology diffusion model has been developed to model an evolutionary and a rather revolutionary scenario which are distinguished by different market entry dates and AV technology take rates. Differentiating by passenger car segment, we introduce autonomous vehicles among new vehicles from 2022 resp. 2025 onward assuming an s-shaped market-take-up until 2035.

This paper introduces an innovative methodology to answer the question, Toward which levels of automobility are the BRIC countries (Brazil, Russia, India, and China) headed? The authors applied this methodology as an aid to understanding why long-term saturation levels for car travel differed across the countries of the Organisation for Economic Co-operation and Development study and what this difference meant for the saturation levels that the BRIC countries might attain. This approach factored out development of the gross domestic product (GDP) to focus on the ways in which other factors influenced specific paths of automobility in individual countries. The focus was on this question: Why were the long-term automobility saturation levels so much higher for some countries than for others, even at similar levels of GDP? The methodology drew on quantitative analysis of historical developments in four industrialized countries (the United States, Australia, Germany, and Japan) that served as case studies representing prototypical paths of automobility with extremely different levels of per capita automobility, in combination with qualitative data derived from an expert-based approach. The qualitative approach was used to transfer historical experiences about the ways in which (a) automobility evolution was shaped in industrialized countries and (b) these experiences might affect the future of automobility in the BRIC countries. On the basis of this analysis, Brazil proved the most car-oriented country of the BRICs, with a potential long-term level of automobility between those of Germany and Australia. Russia was the second most car-oriented country, also with a likely long-term level of automobility above that of Germany. China and India, in contrast, were heading toward lower levels of automobility, below that of Germany but higher than that of Japan.

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 case study focuses on the question which levels of automobility, i.e. car ownership and use, can be expected for Brazil within the next decades. To answer this question, we combine findings from three studies exploring future automobility: firstly, a study comparing context conditions for automobility in emerging and in advanced economies; secondly, as system dynamics model of the car purchase demand of first-time buyers in Brazil; thirdly, a cluster study of metropolitan areas worldwide. With a GDP per Capita of about 8,000 USD per year, car ownership is rapidly growing in Brazil. Based on analyses of historic paths of automobility development over economic growth, this rapid growth of car ownership in Brazil can be expected to level off in about 30 to 40 years. In light of various factors which are influential for car ownership, we expect that by then Brazil will have a level of automobility higher than Europe today, but lower than the USA today. The availability of domestic oil and bio-ethanol, an important car industry and policy factors conducive to car use contribute to this development. On their path towards low carbon mobility transitions, we suggest to focus on ‘improve’ strategies (e.g. increase efficiencies of cars).

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.

Since the turn of the millennium, car ownership and car travel among young German adults have decreased noticeably. This paper analyzes these changes in young Germans’ mobility behavior on the basis of a mobility diary survey and an income and expenditure survey. The decrease in car travel by young adults is linked to lower car ownership in this group. However, behavioral changes among car owners are far more important with regard to their overall decrease in car travel. Logistic regression was applied to identify the attributes of young households that are associated with low and altering car ownership. This model indicated that structural changes in the population concerning income, employment, household composition, and residential location account for the majority of the decrease in car ownership among young households. However, the model also showed that, all things being equal, the probability of car ownership has changed. Specifically, the gender gap for car ownership has almost disappeared because young men are less likely to own a car today than in the 1990s. The study also investigated changes in car use by car owners. The results showed that men have reduced their total travel and that both men and women have reduced their car mode share and exhibit increasingly multimodal behavior.

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.

This paper discusses available household survey data on long-distance travel (LDT) and presents harmonized figures on LDT in Europe. First, there is a comparison of the results of different household travel surveys about LDT. The findings of this comparison have important implications for the methodology of surveying LDT: conventional mobility diary surveys are better than LDT surveys in capturing journeys up to 200 km. LDT surveys perform better in capturing travel only beyond 400 km. Second, the paper presents the first internationally comparable figures on LDT demand for Europe. These figures have been compiled by using different sources of information, avoiding the drawbacks of the different surveys. The results indicate that in northern and central Europe there is higher demand for LDT than in the south. Moreover, the results illustrate how policies and public-transport supply affect the modal split in LDT: in countries with a high-quality railroad supply, such as Switzerland, the railroad share is significantly higher than in other countries. Countries with a liberalized, interurban bus market, in contrast, have a significantly higher bus mode share.

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.

Transport energy resources are largely finite, subject to constraints and a major cause of pollution. Transport-energy planning is not currently included in traditional transport and urban planning. However, transport energy is related to both land use and transport systems therefore transport-energy policy has the ability to positively influence urban design. A new tool has been created, the transport energy specification, which is intended for use within existing local government urban planning frameworks. In order to use this tool, a transport-energy limit is first defined by planning authorities that sets a quantifiable design boundary for urban and transport system development. The transport energy specification is then used to ensure development occurs within the defined design boundary. A case study was performed to demonstrate the required process to achieve a transport energy specification for an urban region. Karlsruhe, Germany was selected for the case study and the results showed that a minimal 0.97 MJ of transport energy per person per week was required, the equivalent energy a 60 W light bulb uses in four and a half hours. This was largely due to high residential density, many activities located within the residential area and the ease and safety of active transport (cycling and walking).

Mobility offerings have never been as abundant and varied as the present. While users welcome new and innovative mobility options, this current paradigm shift presents a challenge for authorities that plan, organize, and operate such services. In particular, integrating new mobility services into existing infrastructure systems can generate problems of acceptance, co-operability, and compatibility. This problem is especially relevant for electric vehicles. Limited range and battery capacity of battery electric vehicles make them dependent on charging infrastructure, which in turn hinders their acceptance. In light of the German government's goal of one million electric vehicles by 2020, establishing a demand-oriented charging infrastructure is of crucial importance. However, numerous questions remain unanswered regarding the quantity, type, and location of electric vehicle charging stations in Germany. This article presents the findings of the project “LADEN2020: Concept to build up a demand-oriented charging infrastructure in Germany between today and 2020.” The research project develops a systematically comprehensible and consistent strategy for electric vehicle charging infrastructure in Germany. The paper presents the methodological framework to estimate the charging demand for daily and long-distance travel, which is unique and innovative as similar comprehensive and consistent analytical tools do not exist to date.

Global gesehen entwickelt sich die Personenverkehrsnachfrage aktuell und in der mittelfristigen Zukunft sehr heterogen. Dabei muss zwischen Alltagsverkehr und Fernverkehr sowie zwischen Industrielandern und Schwellenlandern unterschieden werden. In den Industrielandern zeichnen sich seit einigen Jahren Sattigungstendenzen im Alltagsverkehr ab, die unter den Begriff „Peak Travel“ diskutiert werden. Diese Entwicklung ist besonders dadurch bestimmt, dass die Verkehrsleistung mit dem Pkw kaum noch zunimmt und in einigen Fallen sogar zuruckgeht („Peak Car“). Multimodalitat und abnehmende Automobilitat junger Menschen sind dabei entscheidende Treiber, wahrend Autonutzug und -besitz unter alteren Menschen jedoch weiter zunehmen. Der Fernverkehr, besonders der Flugverkehr, wachst zwar in den Industrielandern weiterhin, jedoch fallen auch hier die jahrlichen Zunahmen nicht mehr so deutlich aus wie in der Vergangenheit. In den Schwellenlandern zeigt sich ein deutlich anderes Bild: Hier ist die Situation im Alltags- und im Fernverkehr von massivem Wachstum gekennzeichnet. Haupttreiber hierfur ist die wirtschaftliche Entwicklung, die es immer groseren Bevolkerungsschichten in diesen Landern erlaubt, mobil zu sein. In der Summe ergibt sich global ein deutliches Wachstum des Personenverkehrs in den nachsten Jahrzehnten. Daraus leiten sich fur die Verkehrspolitik grose Herausforderungen in den Handlungsfeldern Klima, Luftschadstoffe, Larm und Erreichbarkeit ab.

Since 1994, the German Mobility Panel (MOP) has been one of the oldest multiday and multiperiod travel surveys. Along with the need to understand behavioral processes, the demand for such detailed and extensive data is increasing. However, for respondents to take part in a survey like the MOP is often time-consuming. Therefore, with generally declining response rates, it is even more difficult to recruit a suitable sample of test participants for a multiday or multiperiod survey. If a selective nonresponse problem exists, this calls into question the representativeness of such a survey. For the MOP, respondents were recruited in a multistage process that provided an opportunity to study selectivity. The findings indicate that sociodemographics dominate selective nonresponse. There is also some mobility-related selectivity because people for whom mobility is an everyday issue take a stronger interest in the survey topic and are therefore more likely to participate in the survey. It was also found that recruiting households instead of individuals is advantageous because it partly remedies selectivity problems. In addition, the study produced insight about the reliability and trustworthiness of computer-assisted telephone interview data and how they should be interpreted.

Results are presented from analysis of individual mode choice behavior in the longitudinal section in Germany. The findings show that about half of German drivers also use public transport. Because they use different modes, they can be characterized as multimodals. This group will constitute an increasing share of the public transport clientele in coming decades because the decline of captive public transport riders is foreseeable. Therefore it is necessary to understand multimodal behavior because in an environment where travelers have increasing options, it is important to know how they make use of their options. It was found that multimodals employ public transport for specific purposes, whereas the car is universal. Less than 20% of multimodals use public transport on a regular basis, for example, to commute. Most multimodals use it occasionally. Multimodals opt for public transport in specific situations because it is the better option and not because there is no car available. Although for families the car is often the better choice, single persons tend to be more multimodal. Commuting by public transport was found to be a gateway to the use of public transport for other purposes.

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.

Automobility — travel in personal vehicles — varies between countries. This brief summarizes a study of the factors besides economic development that affect automobility and how automobility might evolve in developing countries.

As other mobility innovations individual electric mobility will presumably have a significant market share only in decades from now. Scenario planning technique provides a framework for exploring the mobility market of the future with a long term perspective. Against this background the chapter at hand has a twofold objective: (a) It promotes scenario planning as an alternative approach to explore the distant future of mobility to establish market conditions. (b) The chapter presents results from a scenario planning study for Germany as an example. Three scenarios for the future of mobility emerged from an elaborate scenario planning process: (1) Matured Progress, (2) Global Take-Off, (3) Frantic Standstill. In all three scenarios, the German population ages significantly, concentrates in urban areas and is increasingly aware of environmental issues with consequences for consumer choice. The scenarios differ specifically regarding immigration to Germany, the global and national economies, and the farsightedness of political decision making. Conforming to expectation, these heterogeneous external developments lead to different projections for future travel. Hence, the presented study can assist in identifying future developments that are very likely while others are subject to specific conditional processes. This helps explore the future market for electric mobility among other mobility innovations.