A decision-making architecture for automated driving without detailed prior maps
Autonomous driving requires general methods to generalize unpredictable situations and reason in complex scenarios where safety is critical and the vehicle must react in a reliable manner. In this sense, digital maps are a crucial component for relating the location of the vehicle and identifying th...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Estado: | Versión enviada para evaluación y publicación |
| Data de publicação: | 2019 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositório: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/218371 |
| Acesso em linha: | https://autopia.car.upm-csic.es/wp-content/papercite-data/pdf/artunedo2019a.pdf http://hdl.handle.net/10261/218371 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Decision making Mobile robots Path planning Road vehicles Robot vision |
| Resumo: | Autonomous driving requires general methods to generalize unpredictable situations and reason in complex scenarios where safety is critical and the vehicle must react in a reliable manner. In this sense, digital maps are a crucial component for relating the location of the vehicle and identifying the different road features. In this work, we present a decision-making architecture which does not require detailed prior maps. Instead, OSM is used to plan a global route and an automatically generate driving corridors, which are adapted using a proposed vision-based algorithm. Moreover, a grid-based approach is also applied to consider the localization uncertainty. Those self-generated driving corridors are used by the local planner to plan the trajectories the vehicle will follow. Our approach integrates global, local and HMI components to provide the required functionalities for autonomous driving in a general manner. |
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