Machine learning based motion planning approach for intelligent vehicles


Abstract:

The complexity to handle complex situations in automated driving requires increasing computational resources. In this work, we propose a machine learning approach for motion planning aiming at optimizing the set of path candidates to be evaluated in accordance with the driving context. Thus, the computation cost of the whole motion planning strategy can be reduced while generating safe and comfortable trajectories when required. The proposed strategy has been implemented in a real experimental platform and validated in different operating environments, successfully providing high quality trajectories in a small time frame.

Año de publicación:

2020

Keywords:

    Fuente:

    scopusscopus
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    Tipo de documento:

    Conference Object

    Estado:

    Acceso restringido

    Áreas de conocimiento:

    • Inteligencia artificial
    • Software

    Áreas temáticas de Dewey:

    • Métodos informáticos especiales
    • Otras ramas de la ingeniería
    • Funcionamiento de bibliotecas y archivos
    Procesado con IAProcesado con IA

    Objetivos de Desarrollo Sostenible:

    • ODS 9: Industria, innovación e infraestructura
    • ODS 11: Ciudades y comunidades sostenibles
    • ODS 3: Salud y bienestar
    Procesado con IAProcesado con IA