PDD: Personalized Driving Dataset Dataset Description PDD (Personalized Driving Dataset) is a multi driver, multi scenario driving dataset collected in CARLA 0.9.15. It captures real human driving behavior from 30 individual drivers , each performing 21 challenging driving scenarios . The dataset is designed for research on personalized autonomous driving, where models learn to mimic individual driving styles. Each driver has a detailed profile capturing demographics, driving experience, habits, and self reported driving style. The driving data includes front camera RGB images, 3D bounding boxes for surrounding objects, and per frame vehicle telemetry (speed, acceleration, steering, throttle, brake, etc.). Dataset Statistics Metric Value Drivers 30 Scenarios per driver 21 Total scenario instances 630 Total image frames 70,087 Total bounding box files 70,087 Dataset size ~13 GB Simulator CARLA 0.9.15 Frame rate (saved) 4 FPS Dataset Structure Data Fields Images ( images/ .jpg ) Front forward RGB camera images captured at 4 FPS during driving. Bounding Boxes ( boxes/ .json.gz ) Gzip compressed JSON files, one per frame. Each contains a list of detected objects: class : Object type (…
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