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ListDB RepThree: Stationary camera videos and trajectories at a signalized 3-way intersection taken on different Wednesdays over a 3-year period (2019, 2020 with Covid-19 lockdown, 2022)![Open Access Icon](/xmlui/static/images/oa-logo.svg)
Subtitle: Dresden (Germany): Sidonienstrasse / St. Petersburger Strasse
Metadaten
Ergänzende Titel | Subtitle: Dresden (Germany): Sidonienstrasse / St. Petersburger Strasse | |
Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Bäumler, Maximilian - Technische Universität Dresden (ORCID: 0000-0003-4052-0572) | |
Verwendete Forschungsinstrumente | GoPro Hero Session 4 | |
Verwendete Forschungsinstrumente | DJI Action 2 | |
Zugrundeliegende Forschungsobjekte | Other: Traffic observation videos of an intersection | |
Kurzbeschreibung | The dataset can be used to study road traffic before, during, and after Covid-19. Moreover, the dataset can help to derive test scenarios for scenario-based testing, for example. The dataset includes seven days of drone videos and their corresponding trajectories recorded in Dresden, Germany, at a signalized 3-way intersection. Data collection in 2020 also took place on days with Covid-19 conditional lockdown, including curfew. The data collection followed a fixed sampling plan covering four different time slots daily (weekdays: 07.30-09.00 / 10.00-11.30 / 13.00-14.30 / 15.30-17.00) within 2019-2022. Moreover, extensive metadata is provided following the ListDB specification (w3id.org/listdb). Source trajectory data was extracted from video using DataFromSky TrafficSurvey (https://ai.datafromsky.com/aerial) - an AI video analytics-based service for gathering advanced traffic data for researchers and traffic engineers. Main facts: 1056 minutes of video (2019: 160 minutes / 2020: 560 minutes / 2022: 336 minutes). The analysed trajectories are available for each video. We sincerely thank DataFromSky for supporting the analysis. The video-based traffic observation was conducted within the MOTUS project (19FS2015A; motus-project.com) and supported by the mFUND grant by Germany’s Federal Ministry for Digital and Transport. | |
Angewendete Methoden oder Verfahren | The videos were collected using consumer cameras (GoPro Hero Session 4; DJI Action 2). The metadata was collected using the ListDBApp (see .apk). The source trajectory data was extracted from video using DataFromSky TrafficSurvey (https://ai.datafromsky.com/aerial) - an AI video analytics-based service for gathering advanced traffic data for researchers and traffic engineers. | |
Inhaltsverzeichnis | - Sample video data - Sample trajectory data - Video data - Trajectory data - ListDBApp to collect metadata - ListDB codebook to specify the metadata | |
Länder, auf die sich die Daten beziehen | GERMANY | de |
Koordinaten von Orten, auf die sich die Daten beziehen | 51.041777, 13.735755 | |
Region(en) auf die sich die Daten beziehen | Saxony | |
Region(en) auf die sich die Daten beziehen | Dresden | |
Weitere Schlagwörter | camera | |
Weitere Schlagwörter | traffic observation | |
Weitere Schlagwörter | trajectories | |
Weitere Schlagwörter | Data From Sky | |
Weitere Schlagwörter | video analysis | |
Weitere Schlagwörter | object detection | |
Weitere Schlagwörter | traffic scenario | |
Weitere Schlagwörter | autonomous driving | |
Weitere Schlagwörter | covid-19 | |
Weitere Schlagwörter | corona | |
Weitere Schlagwörter | lockdown | |
Weitere Schlagwörter | curfew | |
Sprache | eng | |
Entstehungsjahr oder Entstehungszeitraum | 2019-2022 | |
Veröffentlichungsjahr | 2023 | |
Herausgeber | Technische Universität Dresden | |
Referenzen auf ergänzende Materialien | IsPartOf: 123456789/5882 (Handle) | |
Referenzen auf ergänzende Materialien | IsPartOf: https://w3id.org/listdb/onto (URL) | |
Referenzen auf ergänzende Materialien | IsPartOf: https://doi.org/10.26128/2023.40 (URL) | |
Inhalt der Forschungsdaten | Text, Audiovisual, Dataset, Software: Video: Videos containing traffic observation (.mp4) Dataset: Mined trajectories (.csv; .tlgx) Software: ListDBApp to collect metadata (.apk) Text: Text files containing metadata (.txt; .csv) Text: Codebook specifying the metadata (.pdf) | |
Inhaber der Nutzungsrechte | Technische Universität Dresden | |
Nutzungsrechte des Datensatzes | CC-BY-NC-4.0 | |
Eingesetzte Software | Resource Production: ListDBApp (Android; self-developed) | |
Eingesetzte Software | Resource Processing: Data From Sky Traffic Survey | |
Angabe der Fachgebiete | Engineering | de |
Titel des Datensatzes | ListDB RepThree: Stationary camera videos and trajectories at a signalized 3-way intersection taken on different Wednesdays over a 3-year period (2019, 2020 with Covid-19 lockdown, 2022) |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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ListDB: Representative datasets of video-based traffic observations [3]
Representative datasets of video-based traffic observations according to the ListDB specification (w3id.org/listdb/). We collected the videos mainly at different intersections in Germany following a fixed sampling plan to ensure representativity. We describe the sampling plan and the collection procedure in the following paper: Maximilian Bäumler, Matthias Lehmann, Günther Prokop (2023). "Generating representative test scenarios: The "Fuse for Representativity" (FUSE4Rep) process model to collect and analyse traffic observation data". In: 27th ESV Conference. Yokohama. Paper NO.23-0122-O The paper is available here: https://index.mirasmart.com/27esv/PDFfiles/27ESV-000122.pdf