Design, Demonstration and Dissemination of Systems for Sustainable Mobility

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

SUPSI
Dalle Molle Institute for Artificial Intelligence
Prof. Dr. Luca Maria Gambardella

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)

  • Analysis of overall optimization potential for alternative transport systems. | Contact: V.Härri
  • Technical simulation for more efficient transport systems. summary deliverable
    Contact: U. Weidmann
  • Pilot Project for Interconnection of Electrical Charging Devices and substations. Efficiency improvement and dissemination.
    Contact:V. Härri


Spatio-temporal Data Acquisition & Analysis, Monitoring Devices and User Communication (B1.2)

  • System requirements and specifications for and ICT- and Sensor-Based Monitoring Framework | Contact: M. Raubal
  • Implementation and extension of a model for real-time automatic matching of complementary transport needs
    Contact: M. Raubal
  • Transport simulation implementation: Sharing and Autonomous Driving. | Contact: K. Axhausen
  • Personalized energy mobility app prototype summary
    Contact: M. Raubal


Urban Planning & Environmental Impact (B1.3)

  • Models and definitions: Decision-making process and spatial mobility model based on Building Information
    Modeling BIM [M6]; Stakeholders definition [M8].
  • Inventory of spatial planning data, regulations, law and standards, LCiA [M12].
  • Prototype of decision-making tool with limited function including home-work-leisure interaction and planning tool for e-mobility [M24]

Optimizing energy efficiency and infrastructure usage of railway operation

  • Data collection of on-board monitoring data (first phase) [3, 2018]
  • Calibration and validation models for railway simulation modelling [1, 2019]
  • Energy efficient strategies in railway operation: towards autonomous driving in mixed traffic national rail networks [12, 2020]


Optimal fleet composition and energy infrastructures for road-based mobility

  • Research proposal ready for submission [6, 2017]
  • Release and publication of the optimization framework [12, 2017]
  • Documentation or paper, proof of concept [1, 2018]
  • Complete first example application based on micro-census [6, 2018]
  • Documentation or paper, aggregated examples based on micro-census [12, 2018]
  • Integration strategies for study region: final report case study 1 [6, 2020], and publication of generalization for other regions


Capacities of energy infrastructures with emphasis on the electric grid

  • Modelling of the distribution grid of a benchmark distribution grid and, if possible of the concrete partnering region(s) including simulations of the respective grids typical usage patterns as given by load demand and local PV production time-series inside the grid platform DPG.sim [12, 2017]
  • Technical report on distribution grid modelling and base-case simulation results [1, 2018]
  • Development of techno-economic assessment concept for cost-effective distribution grid adaption due to electric mobility charging demands. Validation of the assessment concept based on simplified mobility-induced electric charging profiles inside the distribution grid simulation framework and development [12, 2018]
  • Technical report or paper on electric mobility’s charging impacts and cost-effective distribution grid adaptation [1, 2019]
  • Incorporation of detailed mobility-induced electric charging profiles into distribution grid simulation and adaptation framework [12, 2019]
  • Final report or paper on electric mobility’s charging impacts and cost-effective distribution grid adaptation incl. generalizable grid adaptation recommendations for distribution grid operators [12, 2020]


Assessment of mobility choices in a geographic and socio-economic context

  • Main reasons for and against choosing sustainable or non-sustainable mobility options in a particular geographic or socio-economic context identified [12, 2018]
  • Model-driven questionnaire [12, 2017]
  • Results of questionnaires and documentation [12, 2018]


Information service for sustainable mobility choices

  • Sustainable mobility choice recommender system [12, 2020]
  • Prototypical implementation of a mobility choice recommender system [12, 2020]


Prototype of transport need matching system

  • Software prototype of transport need matching system & transfer to SUPSI team (within the framework of the NFP Go Eco! project) [12, 2017]
  • Standards for web-based publication of transport needs [6, 2017]
  • Algorithm for multi-modal and energy-efficient transportation modes [9, 2017]


Household consumption modelling


Simulation of prospective household mobility behaviour

  • Updated MATSim model (including integration of models from B1.2.1) [6, 2019]
  • Documentation and open-source code for the updated MATSim model [6, 2019]
  • Calibration results of updated MATSim model [12, 2019]
  • Results of the simulation study integrating prospective household behaviour [11, 2020]
  • Archive of the data and code used [12, 2020]
  • Investigation of measures/incentive systems on the mobility impacts of individual households in future scenarios [4, 2020]


Impact of urban structures and planning activities on mobility

  • Cluster analysis of settlement typologies inducing varying mobility behaviour is identified [10, 2018]
  • Prototype for decision-making tool validated and implemented into external practice [10, 2020]

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)

2019

Bucher, D., Mangili, F., Cellina, F., Bonesana, C., Jonietz, D., & Raubal, M. (2019). From location tracking to personalized eco-feedback: A framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors. Travel Behaviour and Society, 14, 43–56. https://doi.org/10.1016/J.TBS.2018.09.005


2018

Bucher, D., Mangili, F., Bonesana, C., Jonietz, D., Cellina, F., & Raubal, M. (2018). Demo Abstract: Extracting eco-feedback information from automatic activity tracking to promote energy-efficient individual mobility behavior. Computer Science - Research and Development, 33(1–2), 267–268. https://doi.org/10.1007/s00450-017-0375-2

Bucher, D., Rudi, D., & Buffat, R. (2018). Captcha Your Location Proof—A Novel Method for Passive Location Proofs in Adversarial Environments. https://doi.org/10.1007/978-3-319-71470-7_14

Buffat, R., Bucher, D., & Raubal, M. (2018). Using locally produced photovoltaic energy to charge electric vehicles. Computer Science - Research and Development, 33(1–2), 37–47. https://doi.org/10.1007/s00450-017-0345-8

Çabukoglu, E., Georges, G., Küng, L., Pareschi, G., & Boulouchos, K. (2018). Battery electric propulsion: An option for heavy-duty vehicles? Results from a Swiss case-study. Transportation Research Part C: Emerging Technologies, 88, 107–123. https://doi.org/10.1016/J.TRC.2018.01.013

De Martinis, V., & Corman, F. (2018). Data-driven perspectives for energy efficient operations in railway systems: Current practices and future opportunities. Transportation Research Part C: Emerging Technologies, 95, 679–697. https://doi.org/10.1016/J.TRC.2018.08.008

De Martinis, V., Toletti, A., Corman, F., Weidmann, U. A., & Nash, A. (2018). Feedforward Tactical Optimization for Energy-Efficient Operation of Freight Trains: The Swiss Case. Transportation Research Record: Journal of the Transportation Research Board, 2672(10), 278–288. https://doi.org/10.1177/0361198118776508

Froemelt, A., Buffat, R., Heeren, N., & Hellweg, S. (2018). Assessing environmental impacts of individual households: A large-scale bottom-up LCA-model for Switzerland. SETAC Europe 28th Annual Meeting, Rome, Italy, May 13-17,2018, (147), 32–33. Retrieved from https://www.research-collection.ethz.ch/handle/20.500.11850/291071

Froemelt, A., Dürrenmatt, D. J., & Hellweg, S. (2018). Using Data Mining To Assess Environmental Impacts of Household Consumption Behaviors. Environmental Science & Technology, 52(15), 8467–8478. https://doi.org/10.1021/acs.est.8b01452

Jonietz, D., & Bucher, D. (2018). Continuous Trajectory Pattern Mining for Mobility Behaviour Change Detection. https://doi.org/10.1007/978-3-319-71470-7_11

Jonietz, D., Bucher, D., Martin, H., & Raubal, M. (2018). Identifying and Interpreting Clusters of Persons with Similar Mobility Behaviour Change Processes. https://doi.org/10.1007/978-3-319-78208-9_15

Küng, L., Bütler, T., Georges, G., & Boulouchos, K. (2018). Decarbonizing passenger cars using different powertrain technologies: Optimal fleet composition under evolving electricity supply. Transportation Research Part C: Emerging Technologies, 95, 785–801. https://doi.org/10.1016/J.TRC.2018.09.003

Urner, J., Bucher, D., Yang, J., Jonietz, D., Urner, J., Bucher, D., … Jonietz, D. (2018). Assessing the Influence of Spatio-Temporal Context for Next Place Prediction using Different Machine Learning Approaches. ISPRS International Journal of Geo-Information, 7(5), 166. https://doi.org/10.3390/ijgi7050166

Valverde, G., Zufferey, T., Karagiannopoulos, S., & Hug, G. (2018). Estimation of voltage sensitivities to power injections using smart meter data. 2018 IEEE International Energy Conference (ENERGYCON), 1–6. https://doi.org/10.1109/ENERGYCON.2018.8398841

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

Zufferey, T., Toffanin, D., Toprak, D., Ulbig, A., & Hug, G. (2018). Generating Stochastic Residential Load Profiles from Smart Meter Data for an Optimal Power Matching at an Aggregate Level. 2018 Power Systems Computation Conference (PSCC), 1–7. https://doi.org/10.23919/PSCC.2018.8442470

Zufferey, T., Ulbig, A., Koch, S., & Hug, G. (2018). Unsupervised Learning Methods for Power System Data Analysis. Big Data Application in Power Systems, 107–124. https://doi.org/10.1016/B978-0-12-811968-6.00006-1


2017

Bucher, D., Scheider, S., & Raubal, M. (2017). A Model and Framework for Matching Complementary Spatio-Temporal Needs. Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - SIGSPATIAL’17, 1–4. https://doi.org/10.1145/3139958.3140038

Buffat, R., Froemelt, A., Heeren, N., Raubal, M., & Hellweg, S. (2017). Big data GIS analysis for novel approaches in building stock modelling. Applied Energy, 208, 277–290. https://doi.org/10.1016/J.APENERGY.2017.10.041

Buffat, R., Schmid, L., Heeren, N., Froemelt, A., Raubal, M., & Hellweg, S. (2017). GIS-based Decision Support System for Building Retrofit. Energy Procedia, 122, 403–408. https://doi.org/10.1016/J.EGYPRO.2017.07.433

Ciari, F., & Becker, H. (2017). How Disruptive Can Shared Mobility Be? A Scenario-Based Evaluation of Shared Mobility Systems Implemented at Large Scale. https://doi.org/10.1007/978-3-319-51602-8_3

Frischknecht, R., Bauer, C., Froemelt, A., Hellweg, S., Biemann, K., Buetler, T., … Wettstein, S. (2018). LCA of mobility solutions: approaches and findings—66th LCA forum, Swiss Federal Institute of Technology, Zurich, 30 August, 2017. The International Journal of Life Cycle Assessment, 23(2), 381–386. https://doi.org/10.1007/s11367-017-1429-1

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

Toletti, A., De Martinis, V., & Weidmann, U. A. (2017). Enhancing energy efficiency in railway operation through RCG-based rescheduling. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 1–6. https://doi.org/10.1109/EEEIC.2017.7977624

Zufferey, T., Ulbig, A., Koch, S., & Hug, G. (2017). Forecasting of Smart Meter Time Series Based on Neural Networks. 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