Erstellung von Wochenaktivitätenplänen für Verkehrsnachfragemodelle

Die Arbeit präsentiert actiTopp, ein Modell zur Erstellung von Aktivitätenplänen. Diese werden für Verkehrsnachfragemodellierungen benötigt und bilden, basierend auf Daten des Deutschen Mobilitätspanels, alle Aktivitäten einer Woche ab. Durch die Integration dieser, in vielen Modellen bisher nicht vorhandenen, Längsschnittperspektive ermöglicht actiTopp die Abbildung von Auswirkungen aktueller und zukünftiger Fragestellungen der Verkehrsplanung sowie Verbesserungen der gesamten Prozesskette

Erstellung von Wochenaktivitätenplänen für Verkehrsnachfragemodelle

Die Arbeit präsentiert actiTopp, ein Modell zur Erstellung von Aktivitätenplänen. Diese werden für Verkehrsnachfragemodellierungen benötigt und bilden, basierend auf Daten des Deutschen Mobilitätspanels, alle Aktivitäten einer Woche ab. Durch die Integration dieser, in vielen Modellen bisher nicht vorhandenen, Längsschnittperspektive ermöglicht actiTopp die Abbildung von Auswirkungen aktueller und zukünftiger Fragestellungen der Verkehrsplanung sowie Verbesserungen der gesamten Prozesskette

Influences of Norm and Excitement on Bike Use Behavior of High-Income People in China

In China, the bicycle had a high relevance in the past. Some decades ago, it was the major mode for most Chinese people. This situation changed with growing wealth and increasing car ownership. Today, as cities are traffic-crowded, the bicycle seems to be an alternative again. At the same time, the government as well as private equity, invest in public bike systems. Previous research indicates that especially people with high-income are less likely to use the bicycle as a mode of transport. The question arises whether the bike is used by high-income people that usually have a car as an alternative. What are the influencing factors to use bicycles? To investigate these aspects, we present results of a study conducted in 8 Chinese cities. The data is analyzed using a structural equation model to investigate influences on bike use behavior of high-income people. This study provides no contribution in the research of psychological characteristics of users or the routes used. Rather, it is intended to provide understanding to ecological norm and excitement regarding usage. The results provides insights into the complex interrelationships of sociodemographic and psychological aspects as well as the modernity of the cities in the context of bike usage. Mainly car ownership and the place of residence show significant effects on the attitudes and norms of people and thus influence the use of bicycles. Our results help to understand the interrelationships between sociodemographic characteristics, spatial characteristics and the attitudes of people while making mobility decisions

What do people think about autonomous minibuses in Germany?

Autonomous minibuses gain increasing importance as a mobility option for public transport. In order to realize advantages like increased safety and productivity as well as reduced emissions and congestion user’s needs have to be considered when further developing this technology. So far, there is only a little knowledge about use intentions for autonomous minibuses in public transport and the general perception. This paper presents the results of a Germany-wide online survey and answers the questions: What do people think about autonomous minibuses? When and how would people use them? What are the perceived advantages and disadvantages? Firstly, we analyzed the data descriptively. Secondly, we performed a principal component analysis to reduce data complexity and to identify attitude-based influences on people’s perception. Over 60% liked the minibuses and could imagine to use them in the future. We found one component representing a general attitude towards the minibuses that correlates strongly with the intention to use

Checking Data Quality of Longitudinal Household Travel Survey Data

Ensuring data quality of household travel survey data is often tedious and, thus, time-consuming. To speed up the process of data-checking and to gain an in-depth understanding of the data, data visualization is a practical, fundamental tool. Since 1994, data visualization has been used in the German Mobility Panel (MOP) data-checking process. This paper presents two graphical visualization tools developed for the MOP. Both tools speed up the data checks and ensure high consistency in identifying erroneous data. This paper describes and discusses how the tools provide a continuous data quality assessment

Identification of Non-Routine Tours in Everyday Travel Behavior

This paper deals with the distinction between everyday and tourism related travel. As no objective definition exists to differentiate between these two, surveys usually focus only on one aspect. In particular, this does not provide an overall picture of tourism related travel as some tourism activities are also embedded in everyday life, such as day excursions. However, it is of high relevance to distinguish these types of travel as policy measures may influence these aspects of travel differently and motivations and backgrounds to perform such travel are different. According to the World Tourism Organization (UNWTO), tourism activities take place outside the usual environment of people. In this paper, we approach this subjective definition of a personal environment using data of the German mobility panel. Analyzing the data of three reported weeks of everyday travel behavior per person, we calculate personal thresholds to approach an individual usual environment to decide which part of everyday travel behavior is outside of this environment and thus called non-routine. For this decision, we present a stepwise heuristic that finally distinguishes between routine and non-routine behavior for each tour of a person. Using one heuristic version for analysis, we identify 8.56% of all tours as non-routine. This corresponds to 9.57% of all reported trips but accounts for 33.44% of distances travelled in our dataset. Young people and students have the lowest share of non-routine tours. The opposite was found among pensioners and older age groups who have the highest shares of non-routine behavior

Image-based activity pattern segmentation using longitudinal data of the German Mobility Panel

In this paper, we present an approach to segment people based on a visualization of the longitudinal week activity data from the German Mobility Panel. In order to perform segmentations, different clustering methods are commonly used. Most of the approaches require comprehensive prior knowledge about the input data, e.g., condensing information to cluster-forming variables. As this may influence the method itself, we used images with a high degree of freedom. These images show week activity schedules of people, including all trips and activities with their purposes, modes as well as their duration or their temporal position within the week. Thus, we answer the question whether using only this type of image data as input will produce reasonable clustering results as well. For the clustering, we extracted the images from an existing tool, processed them for the method and finally used them again to select the final cluster solution based on the visual impression of cluster assignments. Our results are meaningful as we identified seven activity patterns (clusters) using this visual validation. The approach is confirmed by the data-based analysis of the cluster solution showing also interpretable key figures for all patterns. Thus, we show an approach taking into account many aspects of travel behavior as an input to clustering, while ensuring the interpretability of solutions. Usually, key figures from the data are used for validation, but this practice may obscure some aspects of the longitudinal data, which are visible when looking on the images as validation

Determining service provider and transport system related effects of ridesourcing services by simulation within the travel demand model mobiTopp

Purpose Ridesourcing services have become popular recently and play a crucial role in Mobility as a Service (MaaS) offers. With their increasing importance, the need arises to integrate them into travel demand models to investigate transport system-related effects. As strong interdependencies between different people’s choices exist, microscopic and agent-based model approaches are especially suitable for their simulation. Method This paper presents the integration of shared and non-shared ridesourcing services (i.e., ride-hailing and ride-pooling) into the agent-based travel demand model mobiTopp. We include a simple vehicle allocation and fleet control component and extend the mode choice by the ridesourcing service. Thus, ridesourcing is integrated into the decision-making processes on an agent’s level, based on the system’s specific current performance, considering current waiting times and detours, among other data. Results and Discussion In this paper, we analyze the results concerning provider-related figures such as the number of bookings, trip times, and occupation rates, as well as effects on other travel modes. We performed simulation runs in an exemplary scenario with several variations with up to 1600 vehicles for the city of Stuttgart, Germany. This extension for mobiTopp provides insights into interdependencies between ridesourcing services and other travel modes and may help design and regulate ridesourcing services