Using Real-Time Dynamic Prediction to Implement IoV-Based Collision Avoidance
Source abstract
Abstract
For some IoV-based collision-avoidance architectures, it is not necessary that all vehicles have communication abilities. Hence, they need some particular designs and extra components. In the literature, one of them uses a camera mounted onto the infrastructure at an intersection to realize collision detection. Consequently, technologies for real-time object detection and dynamic prediction are required for the purposes of collision avoidance. In this paper, we propose an interesting method to predict the future position of a vehicle based on a well-known, real-time object detection project, YOLOv3. Our algorithm utilizes the concept of vehicle dynamics and the confidence region to predict the future position on vehicles. This will help us to realize real-time dynamic prediction and Internet of Vehicles (IoV)-based collision detection. Lastly, in accordance with the experimental results, our design shows the performance for predicting the future position of a vehicle.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Autonomous Vehicle Technology and Safety · Vehicular Ad Hoc Networks (VANETs) · Video Surveillance and Tracking Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan
References (20)
Show source-provided references
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