Bastian Chlond

Who Made Peak Car, and How? A Breakdown of Trends over Four Decades in Four Countries

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 damping effect on peak car. Even though all age classes have contributed to peak car, young adults stand out in this regard and therefore deserve special attention.

Users of Transport Modes and Multimodal Travel Behavior Steps Toward Understanding Travelers' Options and Choices

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 ...

INFRASTRUCTURE DEVELOPMENT IN GERMANY UNDER STAGNATING DEMAND CONDITIONS: A NEW PARADIGM?

Findings from various sources of information, such as mobility panels, permanent road traffic recording devices, and model calculation methods, indicate that for the past few years passenger traffic demand in Germany has not been increasing but has shown notable evidence of stagnation. An analysis of various relevant factors clarifies that this has in fact been an emerging tendency. This is true especially with respect to the demographic changes in Germany and the increased probability of more scarce and definitely more expensive oil resources; further stagnation of traffic demand appears imminent. That leads to the conclusion that infrastructure development must not be based on the idea of everlasting growth with expansions in areas in which the symptoms of traffic growth have been most obvious. It will rather be necessary to identify accurately specific areas of growth or stagnation and to find a suitable scale for further development. Future planning should concentrate on modification rather than on expansion of infrastructure facilities.

Multimodal Travel Choices of Bicyclists: Multiday Data Analysis of Bicycle Use in Germany

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.

Nonresponse, Selectivity, and Data Quality in Travel Surveys: Experiences from Analyzing Recruitment for the German Mobility Panel

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 recr...

Hybrid Modeling Approach of Car Uses in Germany on Basis of Empirical Data with Different Granularities

The use of private cars in Germany has not yet been analyzed from a longitudinal perspective: most travel surveys consider only a single day. Daily car usage is not identical over a given period because car owners use their vehicles for daily routines (e.g., commuting) as well as for infrequent events, such as holiday trips. Another problem of short-period surveys is that they underestimate the share of cars used for long-distance travel. The current work may help to improve the reliability and realism of statements about the extent to which German cars could be replaced by electric vehicles. The authors developed a hybrid modeling approach that aims to obtain car mileage per day for a full year. This approach is based on empirical data with different granularities. Input data are derived from the annually conducted German Mobility Panel, including a survey of fuel consumption and odometer readings, and the long-distance travel survey INVERMO. The study showed that 13.1% of the modeled German private car fleet never exceeded 100 km/day during a full year. Furthermore, cars were driven more than 100 km on 13.3 days/year on average. Mainly used cars (first cars) of a household were used for longer distances rather than second cars. A comparison of average mobility figures from the model approach with the Mobility in Germany national travel survey showed the model results as reliable and realistic.

On New Measures for Detection of Data Quality Risks in Mobility Panel Surveys

Multiday and multiperiod panel surveys are state-of-the-art methods to assess changes in individual travel behavior. Though important for transport planners, these surveys are rather time-consuming for participants and therefore might lead to erroneous and biased mobility data. Variability in the data quality significantly affects statistical analyses of mobility figures as well as common microscopic travel demand models that use the mobility data as the basis for generating activity plans. Supplementary to the well-known approach of weighting biases in key figures of mobility, this paper focuses on methods for detecting data quality differences between individual travel diaries. These quality measures address aspects of motivation loss at different stages of the survey. A classification approach based on these new quality measures helps to detect erroneous data and possible dropouts. The results might help reduce dropouts in general by addressing the potential dropouts individually in advance and boosting their motivation. Quality measures are tested with recent data from the German Mobility Panel. For participants older than 60 years of age, the quality measures show good classification results in regard to accuracy, but for participants younger than 35 years of age the quality measures are not effectual in identifying dropouts. Such an individual approach combined with the partial inspection and correction of travel diaries may be useful for microscopic travel demand modeling based on external activity chains.

Making People Independent from the Car – Multimodality as a Strategic Concept to Reduce CO2-Emissions

Carbon dioxide emissions can be reduced not only by technical improvements but also by appropriate planning concepts aimed at individuals, with a view to changing their travel behavior, mainly through the use of other modes of transport. This article illustrates what should be understood as a change in travel behavior, why observed effects are still few, and the conclusions to be drawn from these. The article shows how politics and planning can create framework conditions that allow for decisions favoring multimodal behavior. The general concept of multimodality and a catalogue of measures are introduced, and illustrated by means of the example of the city of Karlsruhe in Germany, where such planning concepts have been successfully implemented and positive effects are becoming measurable.

Electric Vehicles with Range Extenders: Evaluating the Contribution to the Sustainable Development of Metropolitan Regions

AbstractElectric vehicles play a key role in strategic development plans of urban regions in Europe because they are seen as a promising technology to promote environmental quality, livability, and...

Data Quality and Completeness Issues in Multiday or Panel Surveys

Abstract Purpose — The paper aims at an improvement of the understanding, how mobility is reported in longitudinal surveys and to develop ideas how to assess the completeness of the reported mobility. Methodology/approach — Analyses of data quality and completeness are performed on the multiday and multiperiod data of the German Mobility Panel. Distinctions are made between differing reporting behaviours of individuals who either reported three times, two times or only once. Findings — It can be shown that the reporting behaviours are different depending on the number of repetitions. The results illustrate that on the one hand individuals who repeat the survey in a consecutive wave tend to report with greater motivation, endurance and accuracy. On the other hand, participants who have not reported completely and accurately are more likely to drop out. These effects positively influence the quality and completeness and therefore the reliability of recorded mobility figures in multiperiod mobility surveys. Practical implications — The analytical possibilities of combined multiday and multiperiod data in terms of the assessment of data quality will be demonstrated. Hints to identify such types of survey artefacts are presented.