| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560542 |
| ISSN: | 1405-5546 |
| Autores: | López Campos, Rafael1 Rojas Pérez, L. Oyuki1 Martínez Carranza, José2 |
| Instituciones: | 1Instituto Nacional de Astrofísica Óptica y Electrónica, Departamento de Ciencias Computacionales, Tonantzintla, Puebla. México 2University of Bristol, Bristol. Reino Unido |
| Año: | 2020 |
| Periodo: | Jul-Sep |
| Volumen: | 24 |
| Número: | 3 |
| Paginación: | 1149-1157 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | In this work, we proposed an approach for autonomous driving based on the concept of following and overtaking. This policy controls the vehicle to follow a car ahead of it, and when getting closer, it applies an overtaking step to pass the car and later on to get incorporated to the lane again. For this work, we exploit the robustness of Convolutional Neural Networks for object tracking, which is used to track the car ahead of our autonomous vehicle. We use the pixel position of the tracker in combination with measurements from a laser scanner sensor, as input signals in a PID controller, responsible for driving the vehicle autonomously. We have carried out evaluations of our proposed policy in the Gazebo simulator, whose results indicate the feasibility of our approach. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Autonomous car, Tracking, Overtaking, Deep learning, Autonomous navigation, Artificial intelligence |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
