« Public Transportation Datasets » : différence entre les versions

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(20 versions intermédiaires par le même utilisateur non affichées)
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See [[PolyDatasets|PolyIT Datasets]], generally not public for privacy reasons.
Another resource: https://sites.google.com/view/transport-research-network/shared-resources/datasets
==Traffic Data==
==Traffic Data==
* TJRD TS: http://tjrdts.linknova.cn (vehicle were tracking through millimeter wave radar sensors installed along the freeways in sequence, and trajectories were spliced)
* DLR Urban Traffic dataset (DLR-UT) https://elib.dlr.de/207287/
* pNEUMA https://open-traffic.epfl.ch/
* INTERnational, Adversarial and Cooperative moTION Dataset https://interaction-dataset.com/
* NeurIPS 2022 Traffic4cast competition https://github.com/iarai/NeurIPS2022-traffic4cast
* CitySim https://github.com/ozheng1993/UCF-SST-CitySim-Dataset
* PEMS-BAY / METR-LA liyaguang/DCRNN: Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow https://github.com/liyaguang/DCRNN
* NAVER-SEOUL, HyunWookL/PM-MemNet https://github.com/HyunWookL/PM-MemNet
* Uber movement data https://movement.uber.com/?lang=en-CA
* Uber movement data https://movement.uber.com/?lang=en-CA
* highD dataset: new dataset of naturalistic vehicle trajectories recorded on German highways, using a drone https://www.highd-dataset.com/
* Detector-based traffic data from many countries https://utd19.ethz.ch/index.html
* Trajectories
** BirdsEyeTrajectoryReconstructionSHRP2NDS https://doi.org/10.15787/VTT1/EFYEJR https://github.com/Yiru-Jiao/BirdsEyeTrajectoryReconstructionSHRP2NDS
** TJRD TS: http://tjrdts.linknova.cn (vehicle were tracked through millimeter wave radar sensors installed along the freeways in sequence, and trajectories were spliced)
** Trajnet++ pedestrian trajectory detection benchmark https://www.aicrowd.com/challenges/trajnet-a-trajectory-forecasting-challenge
** pNEUMA https://open-traffic.epfl.ch/
** Vehicle-Crowd Intraction (VCI): DUT dataset https://github.com/dongfang-steven-yang/vci-dataset-dut, CITR dataset https://github.com/dongfang-steven-yang/vci-dataset-citr
** Toyota Woven Prediction Dataset https://woven.toyota/en/prediction-dataset/
** highD dataset (and more recent: inD, roundD, uniD, etc): new dataset of naturalistic vehicle trajectories recorded on German highways, using a drone https://www.highd-dataset.com/
** Trajectories from Shanghai intersections https://www.kaggle.com/datasets/zcyan2/mixed-traffic-trajectory-dataset-in-from-shanghai
** Zen traffic data (2-km Japanese highway) https://zen-traffic-data.net/english/
* Open Data portals
* Open Data portals
** Montreal: counts, [http://donnees.ville.montreal.qc.ca/dataset/temps-de-parcours-sur-des-segments-routiers-historique Bluetooth travel times (continuous, 2016-2017)], [http://donnees.ville.montreal.qc.ca/dataset/mtl-trajet MTL trajet travel survey with trajectories (2016, 2017)], [http://donnees.ville.montreal.qc.ca/dataset/trajets-individuels-velo-enregistre-mon-resovelo cyclist trajectories (2014)]
** Montreal: counts, [http://donnees.ville.montreal.qc.ca/dataset/temps-de-parcours-sur-des-segments-routiers-historique Bluetooth travel times (continuous, 2016-2017)], [http://donnees.ville.montreal.qc.ca/dataset/mtl-trajet MTL trajet travel survey with trajectories (2016, 2017)], [http://donnees.ville.montreal.qc.ca/dataset/trajets-individuels-velo-enregistre-mon-resovelo cyclist trajectories (2014)]
** Quebec: [https://www.donneesquebec.ca/recherche/fr/dataset/rapports-d-accident road accidents], [https://www.donneesquebec.ca/recherche/fr/dataset/debit-de-circulation AADT]
** Quebec: [https://www.donneesquebec.ca/recherche/fr/dataset/rapports-d-accident road accidents], [https://www.donneesquebec.ca/recherche/fr/dataset/debit-de-circulation AADT]
* Detector-based traffic data from many countries https://utd19.ethz.ch/index.html
* TRB Traffic flow theory and characteristics committee (AHB45) http://tft.eng.usf.edu/docs.htm (bottom of the page)
* TRB Traffic flow theory and characteristics committee (AHB45) http://tft.eng.usf.edu/docs.htm (bottom of the page)
** includes links to Portland ITS Portal, PeMS in California, etc.
** includes links to Portland ITS Portal, PeMS in California, etc.
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** Nevada http://challenger.nvfast.org/SPM/
** Nevada http://challenger.nvfast.org/SPM/
** Utah http://udottraffic.utah.gov/ATSPM/
** Utah http://udottraffic.utah.gov/ATSPM/
==PolyIT Datasets==
(not all public)
* Mohamed Gomaa Mohamed's: Guy / Rene Levesque, St Marc
* Marilyne Brosseau's: Sherbrooke / Amherst, Sherbrooke / Iberville
* Quebec's roundabouts (to validate) + NYC? (Paul, Stephen)
* Pedestrian data: Polytechnique and NYC (Dariush)
* Cyclistes et discontinuités (Matin)
* Cyclist overtaking (Catherine) (no ethics) to keep, not much happening
* Place Valois
* Worker safety, Montreal and Quebec (IRSST) (Cesar)
* Pedestrian - vehicle interactions (Catherine - INRS)
* Framework for the analysis of streets and public spaces: traffic calming in Outremont (Abbas), REV cycling facilities Montreal (Frederick)
* Automated Shuttles, Candiac and Montreal (Etienne) (MSC, INRS)
* COVID?
Share with https://hypercore-protocol.org/ or [https://ipfs.io/ IPFS] (test https://ipfs.io/ipfs/QmYzHmTmqZb3HoTfH5crc7YyuYyctNZkmjEgjAamSxKYv6?filename=nicolas.saunier.confins.net.md)


==Automated Vehicles==
==Automated Vehicles==
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* Infrared and visual comparison: CAMEL https://camel.ece.gatech.edu/
* Infrared and visual comparison: CAMEL https://camel.ece.gatech.edu/
* MOTSynth (pedestrian videos from GTA V): https://aimagelab.ing.unimore.it/imagelab/page.asp?IdPage=42
* MOTSynth (pedestrian videos from GTA V): https://aimagelab.ing.unimore.it/imagelab/page.asp?IdPage=42
* Mobility Aids http://mobility-aids.informatik.uni-freiburg.de/
* X world, EvalAI (CVPR2022 AVA Accessibility Vision and Autonomy Challenge) https://eval.ai/challenge/1690/overview https://openaccess.thecvf.com/content/ICCV2021/papers/Zhang_X-World_Accessibility_Vision_and_Autonomy_Meet_ICCV_2021_paper.pdf
* UCLA activity dataset https://vcla.stat.ucla.edu/Projects/Multiscale_Activity_Recognition/
* Multi-Object Multi-Actor, The first benchmark and dataset dedicated to activity parsing https://moma.stanford.edu
* LUMPI: The Leibniz University Multi-Perspective Intersection Dataset https://data.uni-hannover.de/dataset/lumpi
==Crash datasets==
* WTS: Woven Traffic Safety Dataset https://woven-visionai.github.io/wts-dataset-homepage/
* CADP: A Novel Dataset for CCTV Traffic Camera based Accident Analysis https://ankitshah009.github.io/accident_forecasting_traffic_camera
* TCP: Traffic Camera Pipeline https://github.com/BerkeleyAutomation/Traffic_Camera_Pipeline


==LIDAR datasets==
==LIDAR datasets==

Dernière version du 2 janvier 2026 à 13:22

See PolyIT Datasets, generally not public for privacy reasons.

Another resource: https://sites.google.com/view/transport-research-network/shared-resources/datasets

Traffic Data

Automated Vehicles

Video-related Datasets

Image datasets of known objects are useful to train and test object classifiers

Crash datasets

LIDAR datasets

Interesting applications https://scholar.google.com/scholar?&q=lidar%20urban%20environment%20parking

Driver Simulator/Naturalistic Driving