| Revista: | Journal of applied research and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000377617 |
| ISSN: | 1665-6423 |
| Autores: | Wu, C. F1 Lin, C. J2 Lin, H. Y2 Chung, H2 |
| Instituciones: | 1Wenzao Ursuline College of Languages, Department of Digital Content Application and Management, Kaohsiung. Taiwán 2National Chin-Yi University of Technology, Department of Computer Science and Information Engineering, Taichung. Taiwán |
| Año: | 2013 |
| Periodo: | Abr |
| Volumen: | 11 |
| Número: | 2 |
| Paginación: | 251-258 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | The aim of this article attempts to propose an advanced design of driver assistance system which can provide the driver advisable information about the adjacent lanes and approaching lateral vehicles. The experimental vehicle has a camera mounted at the left side rear view mirror which captures the images of adjacent lane. The detection of lane lines is implemented with methods based on image processing techniques. The candidates for lateral vehicle are explored with lane-based transformation, and each one is verified with the characteristics of its length, width, time duration, and height. Finally, the distances of lateral vehicles are estimated with the well-trained recurrent functional neuro-fuzzy network. The system is tested with nine video sequences captured when the vehicle is driving on Taiwan’s highway, and the experimental results show it works well for different road conditions and for multiple vehicles |
| Disciplinas: | Ingeniería |
| Palabras clave: | Ingeniería de control, Ingeniería de transportes, Detección de carriles, Medicion de distancia, Redes neurodifusas |
| Keyword: | Engineering, Control engineering, Transportation engineering, Lane detection, Distance measurement, Fuzzy neural networks |
| Texto completo: | Texto completo (Ver HTML) |
