SISTEMA AVANZADO DE AYUDA A LA CONDUCCIÓN (ADAS) EN ROTONDAS /GLORIETAS USANDO IMÁGENES AÉREAS Y TÉCNICAS DE INTELIGENCIA ARTIFICIAL PARA LA MEJORA DE LA SEGURIDAD VIAL
Keywords:
Roundabouts, Machine Learning, Aerial Imagery, Object Detection, Deep Learning, Computer VisionAbstract
Roundabouts are a type of traffic construction in which several roads converge and communicate through a rotating circulation around a central island. Although, they have increased safety, driving around them properly is not an easy task for conventional and autonomous vehicles. There are publications about ADAS that considers roundabouts as objects to be transited, guiding these autonomous ones in the circulation. This work present takes roundabouts as a source of information that could be transmitted to these vehicles to improve their decision making. To this end, it details the creation of a prototype for monitoring Spanish roundabouts using aerial imagery and machine learning. This system requires an installation phase in which it is calibrated using image processing techniques to recognize the circumferences of the central island and the different lanes. Then, using a RetinaNET model based on a resnet50 backbone, each vehicle and its type is detected. Combining both subsystems, the prototype extract information about the position of vehicles (exact location and lane), entering/exiting ones and those that affect the entering (key aspect for capacity calculation). The aim is to improve security by using artificial intelligence techniques.
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