Detection of road markings from LIDAR data
It is not rare to find LIDAR technology (Light Detection and Ranging) in the sensor setup of an autonomous car, since it can offer many features and compensate lackings of cameras. Since LIDAR sensors measure reflectivity, they can be useful in road markings detection methods. Many different techniq...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/376994 |
| Acceso en línea: | https://hdl.handle.net/2117/376994 |
| Access Level: | acceso abierto |
| Palabra clave: | Remote sensing Automated vehicles LIDAR road markings detection autonomous driving Teledetecció Vehicles autònoms Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció |
| Sumario: | It is not rare to find LIDAR technology (Light Detection and Ranging) in the sensor setup of an autonomous car, since it can offer many features and compensate lackings of cameras. Since LIDAR sensors measure reflectivity, they can be useful in road markings detection methods. Many different techniques have been explored to take advantage of their higher reflectivity in relation to other road elements. An algorithm for the detection of road markings from LIDAR pointclouds is proposed and tested on the KITTI raw dataset. An augmentation of the pointcloud size using the data from the navigation sensor and a filter to detect road points are applied to ensure a good detection thanks to a thresholding performed based on the reflectivity values. It is proven that indeed detection from LIDAR measurements is possible regardless of the external light conditions. For future work, a deep learning approach is encouraged to classify the detected road markings. |
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