SWOT Analysis for Object Detection in Traffic Engineering Based on YOLO Implementation – Case Study

Abstract

Over decades, traffic engineers are focusing on different ways to increase the drivers and pedestrian safety during the daily traffic on the streets. The main reason for that is the growing number of cars, pedestrians, and road density across the whole world [1]. Also, the dramatic increase of computational power, decreasing price of technical equipment enable enrolling object detection topics also in the real time application withing traffic engineering topics. Special focus on mobility topics is not the only one application of this computer technology. It has a broad impact also to many different fields of interests starting from medicine, face-recognition, industry, or art. Three decades of algorithms development, increasing of the computational power led to wide spread of methods and usage. Many important milestones were reached and presented. One should have read the complete evolution, or even browse deeply dedicated pages and forums, but this all can lead to misleading conclusions of usage or performance. This paper should briefly demonstrate and illustrate the implementation of object detection algorithms at a specific, predefined location.