Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements

In our recently published 2021 GIScience paper “Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements“, we study the problem of how to quantify the spatial autocorrelation of samples that were recorded at different points in space and time. Such data is commonly produced by mobile sensors, e.g., the temperature sensors of cars, but also by social phenomena such as location checkins of people. As not only the sensors move, but also the phenomena (potentially) change over time, an autocorrelation value such as Moran’s I can either be inaccurate or impossible to compute due to a lack of data. Instead, we propose to weigh the contribution of different samples based on an empirically projected uncertainty. This weakening of the impact of uncertain samples leads to more stable estimations of spatial autocorrelation quantifications such as Moran’s I.

Doctoral Examination of Dominik Bucher

Dominik Bucher has successfully defended his doctoral thesis titled “Spatio-Temporal Information and Communication Technologies Supporting Sustainable Personal Mobility” on 21 September 2020.

His research revolved around the question of how smartphone-tracked individual mobility data can be analyzed and utilized to support people in transitioning towards sustainable mobility usage. To this purpose, analysis methods (that identify transport modes, extract preferences and context, and detect changes in behavior), routing algorithms (that put an emphasis on personalized inter-modal transport involving a large number of transport options) and communication strategies (based on research on motivation and persuasion and evaluated using the large-scale mobility study GoEco!) were presented. Overall, if individual mobility data is used to give people eco-feedback and alternative route options in a timely manner, it is successful in helping people think about and adopt more sustainable mobility styles.

We Welcome Yanan Xin to the MIE Lab Team

We welcome Dr. Yanan Xin as our newest team member. After successfully completing her PhD at the Pennsylvania State University, she joins the MIE lab in the role of lead researcher.

Exploring Choices between Internal Combustion Engine Cars and Electric Vehicles

In our recent publication “Exploring Factors that Influence Individuals’ Choice Between Internal Combustion Engine Cars and Electric Vehicles“, we use a large dataset of people owning both an Internal Combustion Engine (ICE) car as well as an Electric Vehicle (EV) to determine the impacts of various predictor variables on their choices between the two car types. The gained insights may give additional information to assess common uncertainties regarding EVs: “How far can I drive with a fully charged vehicle? How quickly does the battery wear out? Does the reduced range and/or lack of a substantial number of charging stations impact my mobility?”

We find that chocies between ICE cars and EVs are regular considering an individual user, but that it is almost impossible to guess how someone will choose for a given trip if nothing about the person is previously known. This is a strong indication that most trips can easily be performed with any of the two vehicle types, and only individual preferences and circumstances determine the choices.

MIE Lab involved in Future Resilient Systems II programme

The second phase of the FRS programme at the Singapore-ETH Centre officially started on April 1st with an online research kick-off meeting. It was launched in the midst of a global crisis – COVID-19, highlighting the need to better understand and foster resilience. Within FRS-II there is a particular emphasis on social resilience to enhance the understanding of how socio-technical systems perform before, during and after disruptions. MIE Lab researchers will contribute within a research cluster focusing on distributed cognition (led by Martin Raubal). More specifically, we will develop a methodology and prototype for detecting weak signals in mobility data to identify potential disruptions.

Interview with Former Lab Member David Jonietz

Our former lab member Dr. David Jonietz recently gave an interview regarding how geospatial data and a digital map of the world can help transform mobility. Currently a research group leader at HERE Technologies, David Jonietz points out how we can step beyond simple maps to create more comprehensive digital representations of reality, which in turn can be used for traffic prediction and management, optimization of mobility systems, and more.

Read the full interview on the SCCER Mobility homepage.

We are hiring!

We are exited to announce that we have an open position in our lab. We are looking for a new post-doc to take over the team lead at the MIE-Lab as soon as possible. If you are interested, please check the description at the ETH jobpage:
https://jobs.ethz.ch/job/view/JOPG_ethz_7R9Rl0z6QH6GC0M9Cv