Dominik Bucher

Last Name

Bucher

First Name

Dominik

ORCID

0000-0001-9824-5388

Show all metadata

Search Results

Publications 1 - 8 of 8

A Taxonomy of Motivational Affordances for Meaningful Gamified and Persuasive Technologies
Weiser, Paul; Bucher, Dominik; Cellina, Francesca; et al. (2015)
Advances in Computer Science Research ~ Proceedings of the 3rd International Conference on ICT for Sustainability (ICT4S)
Sustainable human-computer interaction is investigating the role of persuasive and gamified technologies in encouraging people to engage in a more sustainable lifestyle. Motivation is a key requirement for behavior change, yet many persuasive systems do not sufficiently account for motivational aspects. In this paper we investigate under which circumstances components such as feedback and game elements (e.g., rewards) afford user motivation. The result is a taxonomy of design components that is grounded in well-established psychological theories on motivation. We illustrate how the taxonomy can contribute to the design of meaningful persuasive technologies by discussing a case study from the domain of sustainable mobility behavior (the project GoEco!).
Trackintel: An open-source Python library for human mobility analysis
Martin, Henry; Hong, Ye; Wiedemann, Nina; et al. (2023)
Computers, Environment and Urban Systems
Over the past decade, scientific studies have used the growing availability of large tracking datasets to enhance our understanding of human mobility behavior. However, so far data processing pipelines for the varying data collection methods are not standardized and consequently limit the reproducibility, comparability, and transferability of methods and results in quantitative human mobility analysis. This paper presents Trackintel, an open-source Python library for human mobility analysis. Trackintel is built on a standard data model for human mobility used in transport planning that is compatible with different types of tracking data. We introduce the main functionalities of the library that covers the full life-cycle of human mobility analysis, including processing steps according to the conceptual data model, read and write interfaces, as well as analysis functions (e.g., data quality assessment, travel mode prediction, and location labeling). We showcase the effectiveness of the Trackintel library through a case study with four different tracking datasets. Trackintel can serve as an essential tool to standardize mobility data analysis and increase the transparency and comparability of novel research on human mobility. The library is available open-source at https://github.com/mie-lab/trackintel.
Conserved quantities in human mobility
Hong, Ye; Martin, Henry; Xin, Yanan; et al. (2022)
Arbeitsberichte Verkehrs- und Raumplanung
Quantifying intra-person variability in travel choices is essential for the comprehension of activity-travel behaviour. Due to a lack of appropriate datasets and methods, there is limited understanding of how an individual’s travel pattern evolves over months and years. We use two high-resolution user-labelled datasets consisting of billions of GPS track points from ∼ 3800 individuals to analyze individuals’ activity-travel behaviour over the long term. The general movement patterns of the considered population are characterised using mobility indicators. Despite the differences in the mobility patterns, we find that individuals from both datasets maintain a conserved quantity in the number of essential travel mode and activity location combinations over time, resulting from a balance between exploring new choice combinations and exploiting existing options. A typical individual maintains ∼ 15 mode-location combinations, of which ∼ 7 are travelled with a private vehicle every 5 weeks. The dynamics of this stability reveal that the exploration speed of locations is faster than the one for travel modes, and they can both be well modelled using a power-law fit that slows down over time. Our findings enrich the understanding of the long-term intra-person variability in activity-travel behaviour and open new possibilities for designing mobility simulation models.
Using rooftop photovoltaic generation to cover individual electric vehicle demand—A detailed case study
Martin, Henry; Buffat, René; Bucher, Dominik; et al. (2022)
Renewable and Sustainable Energy Reviews
The introduction of battery electric vehicles (BEV) and the expansion of rooftop photovoltaic (PV) power generation are both progressing at a fast pace to decarbonize the transport and the energy sector in Switzerland. These parallel developments have an enormous synergy potential as the actual decarbonization impact of BEVs depends heavily on the carbon footprint of the power source and the PV expansion requires local storage as a buffer to reduce negative impacts on the distribution grid. We present an empirical analysis based on a detailed 10-month data set of the charging and mobility behavior of 78 BEV users in Switzerland. It is combined with a fine-grained digital surface model of Switzerland to extract the detailed roof geometry and the corresponding rooftop PV generation capacity of each of the BEV owner’s houses. We test four different smart charging strategies with a varying degree of complexity and find that when charging uncontrolled (the strategy used during the study), BEV owners can only cover 15 % of their BEV’s demand using PV generated from the roofs of their own houses. A simple controlled charging approach greatly increases the average coverage to 56 % and up to 90 % or 99 % when using an optimized charging strategy without or with a home battery storage. All charging strategies ensure that the individual mobility behavior of the BEV owners is not affected. We further show that using rooftop PV power generation for BEV charging has a large potential to further decrease the climate impact of BEVs and propose simple adjustments to consider in charging strategies that help to increase the owners’ PV consumption.
Begleitstudie SBB Green Class - Abschlussbericht
Martin, Henry; Becker, Henrik; Bucher, Dominik; et al. (2019)
Arbeitsberichte Verkehrs- und Raumplanung
Mit der Green Class haben die SBB eines der weltweit ersten grossen Pilotprojekte zu einer multimodalen Mobilitäts-Flatrate durchgeführt. In einer wissenschaftlichen Begleitstudie untersuchen das IKG und das IVT der ETH Zürich die verkehrlichen und ökologischen Wirkungen dieses Angebots. Im ersten Teil des Berichts wurden dafür die Befragungs- und Bewegungsdaten der Teilnehmenden im Detail analysiert und mit Informationen aus dem Mikrozensus Mobilität und Verkehr 2015 verglichen. Im zweiten Teil des Berichts, wurde dann das Mobilitätsverhalten der Nutzer über die Zeit analysiert. Die Ergebnisse zeigen, dass die Nutzer die neuen Mobilitätsoptionen langfristig in ihren Mobilitätsmix integrieren und sie in Kombination mit dem öffentlichen Verkehr verwenden. Vor allem der Ersatz des konventionellen Autos mit einem Elektroauto führte im Schnitt zu deutlich niedrigeren CO2-Emissionen.
A Clustering-Based Framework for Individual Travel Behaviour Change Detection
Hong, Ye; Xin, Yanan; Martin, Henry; et al. (2021)
Leibniz International Proceedings in Informatics (LIPIcs) ~ 11th International Conference on Geographic Information Science (GIScience 2021) - Part II
The emergence of passively and continuously recorded movement data offers new opportunities to study the long-term change of individual travel behaviour from data-driven perspectives. This study proposes a clustering-based framework to identify travel behaviour patterns and detect potential change periods on the individual level. First, we extract important trips that depict individual characteristic movement. Then, considering trip mode, trip distance, and trip duration as travel behaviour dimensions, we measure the similarities of trips and group them into clusters using hierarchical clustering. The trip clusters represent dimensions of travel behaviours, and the change of their relative proportions over time reflect the development of travel preferences. We use two different methods to detect changes in travel behaviour patterns: the Herfindahl-Hirschman index-based method and the sliding window-based method. The framework is tested using data from a large-scale longitudinal GPS tracking data study in which participants had access to a Mobility-as-a-Service (MaaS) offer. The methods successfully identify significant travel behaviour changes for users. Moreover, we analyse the impact of the MaaS offer on individual travel behaviours with the obtained change information. The proposed framework for behaviour change detection provides valuable insights for travel demand management and evaluating people’s reactions to sustainable mobility options.
Estimation of Moran's I in the Context of Uncertain Mobile Sensor Measurements
Bucher, Dominik; Martin, Henry; Jonietz, David; et al. (2020)
Leibniz International Proceedings in Informatics (LIPIcs) ~ 11th International Conference on Geographic Information Science (GIScience 2021). Part I
Measures of spatial autocorrelation like Moran’s I do not take into account information about the reliability of observations. In a context of mobile sensors, however, this is an important aspect to consider. Mobile sensors record data asynchronously and capture different contexts, which leads to considerable heterogeneity. In this paper we propose two different ways to integrate the reliability of observations with Moran’s I. These proposals are tested in the light of two case studies, one based on real temperatures and movement data and the other using synthetic data. The results show that the way reliability information is incorporated into the Moran’s I estimates has a strong impact on how the measure responds to volatile available information. It is shown that absolute reliability information is much less powerful in addressing the problem of differing contexts than relative concepts that give more weight to more reliable observations, regardless of the general degree of uncertainty. The results presented are seen as an important stimulus for the discourse on spatial autocorrelation measures in the light of uncertainties.
Conserved quantities in human mobility
Hong, Ye; Martin, Henry; Xin, Yanan; et al. (2023)
Transportation Research Part C: Emerging Technologies
Quantifying intra-person variability in travel choices is essential for the comprehension of activity-travel behaviour. Due to a lack of empirical studies, there is limited understanding of how an individual’s travel pattern evolves over months and years. We use two high-resolution user-labelled datasets consisting of billions of GPS track points from ∼3800 individuals to analyze individuals’ activity-travel behaviour over the long term. The general movement patterns of the considered population are characterised using mobility indicators. Despite the differences in the mobility patterns, we find that individuals from both datasets maintain a conserved quantity in the number of essential travel mode and activity location combinations over time, resulting from a balance between exploring new choice combinations and exploiting existing options. A typical individual maintains ∼15 mode-location combinations, of which ∼7 are travelled with a private vehicle every 5 weeks. The dynamics of this stability reveal that the exploration speed of locations is faster than the one for travel modes, and they can both be well modelled using a power-law fit that slows down over time. Our findings enrich the understanding of the long-term intra-person variability in activity-travel behaviour and open new possibilities for designing mobility simulation models.

Publications 1 - 8 of 8

Dominik Bucher

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results