Physics Maths Engineering
Radar-Based Pedestrian and Vehicle Detection and Identification for Driving Assistance
Fernando Viadero-Monasterio,
Luciano Alonso-Rentería,
Juan Pérez-Oria,
Fernando Viadero-Rueda
Peer Reviewed
Related Subjects
Abstract
Key Questions about Radar-Based Object Detection in Vehicles
The article "Radar-Based Pedestrian and Vehicle Detection and Identification for Driving Assistance" explores the development of a neural network model aimed at the automatic detection and classification of objects in front of a vehicle, including pedestrians and other vehicles, using radar technology. Radar sensors detect objects by measuring the distance to them and analyzing the power of the reflected signals to determine the type of object detected. Experimental tests were conducted to evaluate the performance of the radar-based system under various driving conditions, assessing its accuracy in detecting and classifying different objects. The proposed neural network model achieved a high accuracy rate, correctly identifying approximately 91% of objects in the test scenarios. The results demonstrate that this model can be used to inform drivers of potential hazards or to initiate autonomous braking and steering maneuvers to prevent collisions. This research contributes to the development of more effective safety features for vehicles, enhancing the overall effectiveness of driver assistance systems and paving the way for future advancements in autonomous driving technology.
1. How does the radar-based system detect and classify objects in front of a vehicle?
The system employs radar sensors to measure the distance to objects and analyze the power of the reflected signals. A neural network model processes this data to identify and classify objects, such as pedestrians and other vehicles, with high accuracy.
2. What is the accuracy of the neural network model in object detection and classification?
The neural network model demonstrated a high accuracy rate, correctly identifying approximately 91% of objects in the test scenarios, indicating its effectiveness in real-world applications.
3. How can this radar-based detection system enhance vehicle safety?
By accurately detecting and classifying objects in front of the vehicle, the system can inform drivers of potential hazards or initiate autonomous braking and steering maneuvers to prevent collisions, thereby enhancing overall vehicle safety.
