road_objects Object Detection Dataset and Pre-Trained Model by selfdrivingcar

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Explore Dataset

Here are a few use cases for this project:

Smart Traffic Management System: Use the "road_objects" model to detect and analyze vehicle types, traffic lights, and signs in real-time to optimize traffic signal timings and reduce congestion.
Autonomous Vehicle Assistance: Integrate the model with self-driving cars to enhance their object recognition capabilities for improved navigation, ensuring safer and smoother operation on the roads.
City Infrastructure Planning: Analyze road usage patterns, including vehicle and pedestrian footfall, to make informed decisions on infrastructure expansion or modifications, such as traffic signal locations, lane allocation, and speed limits.
Road Safety Monitoring: Use the model to develop a comprehensive road safety monitoring system that assesses risk factors like speeding, traffic light violations, and the presence of vulnerable road users like pedestrians and cyclists.
Traffic Law Enforcement: Automate the process of identifying and recording traffic law violations, such as speeding or running red lights, using real-time video feeds from traffic cameras to enhance enforcement effectiveness and reduce accidents.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            road_objects-4laze_dataset,
                            title = { road_objects Dataset },
                            type = { Open Source Dataset },
                            author = { selfdrivingcar },
                            howpublished = { \url{ https://universe.roboflow.com/selfdrivingcar-dcaqb/road_objects-4laze } },
                            url = { https://universe.roboflow.com/selfdrivingcar-dcaqb/road_objects-4laze },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-05-06 },
                            }