Capacity Area B1 deals with increasing mobility energy efficiency from a systemic perspective. This approach takes all aspects of mobility into account, i.e. mobility technology, infrastructure and users, and relates them to mobility patterns, urban planning and environmental data. One focus lies on designing and optimizing the infrastructure for renewable energy carriers (supply of charging stations, hydrogen filling stations and logistics). On the user level, research deals with assessing new IT and information service technologies to foster energy-saving mobility choices. Capacity Area B1 interlinks mobility choices and patterns with environmental and spatial planning to develop a decision support tool for consumers, municipalities and policy makers leading to energy demand reduction.
Prof. Dr. Martin Raubal
Chair of Geoinformation Engineering at ETH Zürich
mraubal@ethz.ch / 044 633 30 26
ETH Zürich
Chair of Geoinformation Engineering, IKG
Prof. Dr. Martin Raubal, Coordinator
ETH Zürich
Institut für Umweltingenieurwissenschaften, IfU-ESD
Prof. Dr. Stefanie Hellweg, Deputy Coordinator
Berner Fachhochschule BFH
Architektur, Holz und Bau, AHB
Prof. Dr. Joachim Huber
ETH Zürich
Aerothermochemistry and Combustion Systems Laboratory, LAV
Dr. Gil Georges
ETH Zürich
Institut für Verkehrsplanung und Transportsysteme, IVT
Prof. Dr. Kay Axhausen
ETH Zürich
Institut für Verkehrsplanung und Transportsysteme, IVT
Prof. Dr. Francesco Corman
ETH Zürich
Power Systems Laboratory
Prof. Dr. Gabriela Hug
Hochschule Luzern HSLU (phase I)
Center of Competence IIEE, Efficient Energy Systems, IIEE/ES
Prof. Vinzenz Haerri
Multimodal Vehicle Integration and Charging Infrastructure (B1.1)
Spatio-temporal Data Acquisition & Analysis, Monitoring Devices and User Communication (B1.2)
Personalized energy mobility app prototype summary
Contact: M. Raubal
Urban Planning & Environmental Impact (B1.3)
Optimizing energy efficiency and infrastructure usage of railway operation
Optimal fleet composition and energy infrastructures for road-based mobility
Capacities of energy infrastructures with emphasis on the electric grid
Assessment of mobility choices in a geographic and socio-economic context
Information service for sustainable mobility choices
Prototype of transport need matching system
Household consumption modelling
Simulation of prospective household mobility behaviour
Impact of urban structures and planning activities on mobility
Erkenntnisse aus einem digitalen Modell (findings of a digital model)
Zwischenstand des laufenden Forschungsprojekts (intermediate results of the ongoing research project)
research conducted by SCCER Mobility CA B1 members Prof. Dr. Joachim Huber and Michael Walczak,
Berne University of Applied Sciences, Architecture, Wood and Civil Engineering
More information www.dencity.ch
Documents
Brochure (in german)
Analysis-diagram-spirit
Fact sheet
e-MIP - electro-Mobility-Information Planning
The innovative e-MIP project aims to optimize bus routes by using coherent, quantitative and spatial simulation and evaluation based on big-data. This collaborative effort between Dencity, ETHZ and HESS AG will promote improved land use in urban living spaces and reduced or neutral CO2 emissions in these areas.
Contact Joachim Huber
Documents
Fact sheet e-MIP (pdf)
Kick-off meeting e-MIP (pdf)
Ciari, F., & Becker, H. (2017). How Disruptive Can Shared Mobility Be? A Scenario-Based Evaluation of Shared Mobility Systems Implemented at Large Scale (pp. 51–63). Springer, Cham. https://doi.org/10.1007/978-3-319-51602-8_3
Froemelt, A., & Hellweg, S. (2017). Assessing Space Heating Demandon a Regional Level: Evaluation of a Bottom-Up Model in the Scope of a Case Study. Journal of Industrial Ecology, 21(2), 332–343. https://doi.org/10.1111/jiec.12438
Jonietz, D., Antonio, V., See, L., & Zipf, A. (2017). Highlighting Current Trends in Volunteered Geographic Information. ISPRS International Journal of Geo-Information, 6(7), 202. https://doi.org/10.3390/ijgi6070202
Zufferey, T., Ulbig, A., Koch, S., & Hug, G. (2017). Forecasting of Smart Meter Time Series Based on Neural Networks (pp. 10–21). Springer, Cham. https://doi.org/10.1007/978-3-319-50947-1_2
2016
Jonietz, D. (2016). Personalizing Walkability: A Concept for Pedestrian Needs Profiling Based on Movement Trajectories (pp. 279–295). Springer, Cham. https://doi.org/10.1007/978-3-319-33783-8_16
Weiser, P., Scheider, S., Bucher, D., Kiefer, P., & Raubal, M. (2016). Towards sustainable mobility behavior: research challenges for location-aware information and communication technology. GeoInformatica, 20(2), 213–239. https://doi.org/10.1007/s10707-015-0242-x
2015
Ahas, R., Aasa, A., Yuan, Y., Raubal, M., Smoreda, Z., Liu, Y., … Zook, M. (2015). Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn. International Journal of Geographical Information Science, 29(11), 2017–2039. https://doi.org/10.1080/13658816.2015.1063151
Allemann, D., & Raubal, M. (2015). Usage Differences Between Bikes and E-Bikes (pp. 201–217). Springer, Cham. https://doi.org/10.1007/978-3-319-16787-9_12
De Martinis, V., & Weidmann, U. A. (2015). Definition of energy-efficient speed profiles within rail traffic by means of supply design models. Research in Transportation Economics, 54, 41–50. https://doi.org/10.1016/J.RETREC.2015.10.024
Haerri, V. V., Lindegger, M., & Neumaier, M. (2015). A novel interior permanent synchronous motor for a high end ebike drive chain. In 2015 5th International Electric Drives Production Conference (EDPC) (pp. 1–6). IEEE. https://doi.org/10.1109/EDPC.2015.7323228
Toletti, A., De Martinis, V., & Weidmann, U. (2015). What about Train Length and Energy Efficiency of Freight Trains in Rescheduling Models? Transportation Research Procedia, 10, 584–594. https://doi.org/10.1016/J.TRPRO.2015.09.012
2014
De Martinis, V., Weidmann, U., & Gallo, M. (2014). Towards a simulation-based framework for evaluating energy-efficient solutions in train operation. In U. Weidmann & M. Gallo (Eds.), WIT Transactions on The Built Environment (Vol. 135, pp. 721–732). WIT Press. https://doi.org/10.2495/CR140601
Saner, D., Vadenbo, C., Steubing, B., & Hellweg, S. (2014). Regionalized LCA-Based Optimization of Building Energy Supply: Method and Case Study for a Swiss Municipality. Environmental Science & Technology, 48(13), 7651–7659. https://doi.org/10.1021/es500151q
Yuan, Y., & Raubal, M. (2014). Measuring similarity of mobile phone user trajectories– a Spatio-temporal Edit Distance method. International Journal of Geographical Information Science, 28(3), 496–520. https://doi.org/10.1080/13658816.2013.854369