Automatic Electric Tricycles Trajectory Tracking and Multi-Violation Detection.

The escalating traffic violations associated with electric tricycles pose a critical challenge to urban traffic safety. It is important to automatically track the trajectories of electric tricycles and detect the multi-violations related to electric tricycles. This paper proposed an Electric Tricycle Object Detection (ETOD) model based on the custom-built dataset of electric tricycles. ETOD can successfully achieve real-time and accurate recognition and high-precision detection for electric tricycles. By integrating a multi-object tracking algorithm, an Electric Tricycle Violation Detection System (ETVDS) was developed. The ETVDS can detect and identify violations including speeding, passenger overloading, and illegal lane changes by plotting electric tricycle trajectories. The ETVDS can identify the conflicts related to electric tricycles in complex traffic scenarios. This work offers an effective technological solution for mitigating electric tricycle traffic violations in challenging urban environments.