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Dataset and Scenario-based Evaluation Framework

The evaluation is conducted using a large-scale synthetic dataset comprising approximately 700,000 synchronised multi-modal samples generated within the CARLA autonomous driving simulator. The dataset is designed to support comprehensive scenario-based evaluation across diverse driving conditions

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CreatorBhagwan, Das
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Published2026-04-14
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DOI10.5281/zenodo.19570111
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Downloads80
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Licensecc-by-4.0
File Size257.7 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views334
Total Downloads80

The evaluation is conducted using a large-scale synthetic dataset comprising approximately 700,000 synchronised multi-modal samples generated within the CARLA autonomous driving simulator. The dataset is designed to support comprehensive scenario-based evaluation across diverse driving conditions, including variations in traffic density, weather conditions, lighting, and road topology. Each sample includes temporally aligned sensor modalities such as RGB images, depth maps, semantic segmentation, LiDAR point clouds, and vehicle state information, enabling robust multi-modal learning and benchmarking.

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Dataset and Scenario-based Evaluation Framework (Full Dataset)257.7 MB
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ReadmeVia DOI record
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Files are hosted on the source repository. Click download to access the full dataset.

Bhagwan, Das (2026). Dataset and Scenario-based Evaluation Framework. https://doi.org/10.5281/zenodo.19570111