This dataset aims to provide high-quality nighttime traffic congestion recognition data to support the research and application of intelligent transportation systems.

Evaluate how well models reason about high-speed vessel motion responses, load variations, and seakeeping modeling assumptions through structured simulation scenarios and analysis tasks.

This dataset focuses on semantic segmentation of vehicle collision damage in tunnel environments, aiming to improve the efficiency and accuracy of traffic accident analysis.

This dataset provides classification images of various congested scenes at highway entrances, aiming to enhance the automatic recognition capabilities of intelligent traffic systems.

This dataset provides high-quality semantic segmentation images of accident vehicles and road debris, aiding the development of intelligent transportation and autonomous driving technologies.

The Rail Transit Accident Scene Dataset aids in accident detection and analysis for intelligent transportation systems.

Train and evaluate ship weight and center-of-gravity calculation checkers with JSON samples containing itemized weights, reference results, and correctness labels.

Evaluate specialized code verification and debugging with transmission diagnostic state machine code, transition constraints, and annotated defect causes.

Evaluate how well models understand cross-layer positions, alignment, and containment in HD maps featuring lane markings and road boundaries.

This dataset focuses on illegal parking detection on urban roads, providing abundant labeled images and detailed information.

Turn the spatial relationship between a vehicle and its lane centerline into clear, trainable lane-relative localization fields.

This dataset provides high-quality target detection data for subway entrance safety monitoring, aiding in traffic safety management.

This dataset focuses on complex traffic scenes of suburban roads, aiming to enhance the accuracy and reliability of target detection technology.

This is a dataset focused on in-car driving perspective target detection under rainy conditions.

This dataset monitors prolonged congestion or gathering of people in the underground garage due to queuing, payment, charging, and other reasons.

This dataset is dedicated to identifying abnormal states of traffic lights, providing reliable data support for traffic monitoring.

This dataset provides high-quality image data for tunnel and special scenarios traffic safety monitoring, aiming to support the training and application of object detection algorithms.

Target arithmetic defects in BMS firmware with examples annotated for failure behavior, code-level causes, and corrective guidance.

This dataset focuses on multi-target (vehicles, traffic police, environment) recognition at night, providing data support for traffic safety.

This dataset focuses on multi-target detection at traffic accident scenes and provides rich image data to support the research of intelligent transportation systems.