English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Reliable traffic data are essential for understanding urban mobility anddeveloping effective traffic management strategies. This study introduces theDRone-derived Intelligence For Traffic analysis (DRIFT) dataset, a large-scaleurban traffic dataset collected systematically from synchronized drone videosat approximately 250 meters altitude, covering nine interconnectedintersections in Daejeon, South Korea. DRIFT provides high-resolution vehicletrajectories that include directional information, processed through videosynchronization and orthomap alignment, resulting in a comprehensive dataset of81,699 vehicle trajectories. Through our DRIFT dataset, researchers cansimultaneously analyze traffic at multiple scales - from individual vehiclemaneuvers like lane-changes and safety metrics such as time-to-collision toaggregate network flow dynamics across interconnected urban intersections. TheDRIFT dataset is structured to enable immediate use without additionalpreprocessing, complemented by open-source models for object detection andtrajectory extraction, as well as associated analytical tools. DRIFT isexpected to significantly contribute to academic research and practicalapplications, such as traffic flow analysis and simulation studies. The datasetand related resources are publicly accessible athttps://github.com/AIxMobility/The-DRIFT.

DRIFT open dataset: A drone-derived intelligence for traffic analysis in urban environment