Browsing by Author "Gerike, Regine"

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Open Access
Mobility and GNSS-route data from a smartphone app-based travel survey from Berlin and Dresden (Städte in Bewegung 2025)
(Technische Universität Dresden, 2026-06-02) Weber, Johannes; Hubrich, Stefan; Díaz Cordero, Manuel; Noroozi, Vahid; Wübbenhorst, Jonas; Krombach, Jonas; Gerike, Regine
These datasets are dedicated to non-commercial research purposes in the areas of mobility research, urban and transport planning, and geoinformation upon authorized request. Given the fact that the datasets contain personal data, only authorized research institutions in Germany can be granted full access. More information on data request can be found at https://dd-trust.zih.tu-dresden.de/msp-main/. Datasets can be provided as SAV or CSV files, collectively forming the StiB database of persons and their travel behavior, based in the cities of Berlin and Dresden, who have given their broad consent for scientific data reuse of pseudonymized data—referred to as the StiB Broad Consent Database. The database is hierarchical and consists of four interconnectable levels: 1) 1 dataset containing socio-demographic information about the participants as well as information about their participation in the survey (person level), 2) 1 dataset containing collected days per person with travel estimates, calendar details, participation duration and user validation status (day level), 3) 1+1 datasets with the collected trips per person and day with e.g. trip duration, distance, purpose and data quality criteria—extendable with a geo-referenced dataset containing start and end coordinates of the trips using WGS84 / EPSG:4326 (trip level) 4) 1+2 datasets with collected app items from the mobility diaries per person, day and trip with e.g., route/stay duration, distance, stay purpose and data quality criteria—extendable with two separate geo-referenced datasets containing information on route and stay geometry using WGS84 / EPSG:4326 (storyline level) The StiB Broad Consent Database is based on collected data from the StiB-app and related online questionnaires. These data have been post-processed by MSP and unified into one database, formatted according to the standardized structure above, from data collections in Berlin and Dresden.
Open Access
SivaS Project Results: Traffic Observation Data and Exemplary Subset of Master Database
(Technische Universität Dresden, 2025-06-30) Kannan, Rajagopalan; Prokop, Günther; Kollascheck, Armin; Gerike, Regine; Stoller, André; Böhme, Tobias
This dataset comprises JSON files and .mp4 video recordings that collectively form the foundation of a centralized database for traffic observations, referred to as the SivaS Master Database. Included in the dataset are: (i) a subset of the raw traffic observation data, (ii) JSON schemas defining the standardized data structure for traffic data storage, (iii) the hierarchical folder framework for organizing such data, and (iv) an exemplary implementation of the standardized database. Given the complexity of the raw data and the substantial effort involved in converting it into the standardized structure, only a limited sample dataset was manually curated and prepared. The SivaS Master Database was created by transforming a subset of the raw traffic data collected during the project into the established database, designed to support integration from various acquisition systems. The dataset includes traffic observations obtained through three different modalities: drones, stationary pole-mounted cameras, and sensor-equipped NDS (Naturalistic Driving Study) vehicles. Specifically, it features over 60 minutes of video recordings from a junction in the city of Dresden, captured simultaneously by three stationary cameras. Additionally, it contains more than 30 minutes of drone-based video footage from two separate junctions in the city of Hoyerswerda. It also includes vehicle positioning data collected by a sensor-equipped observation vehicle, formatted according to the standardized structure, from traffic observations conducted in Hoyerswerda.