Probabilistic road geometry estimation using a millilmetre-wave radar

Resultado de la investigación

Resumen

This paper presents a probabilistic framework for road geometry estimation using a millimetre wave radar. It aims at estimating the geometry of roads without assuming any particular infrastructure such as lane marks. It provides also the vehicle location with respect to the edges of the road. This system employs a radar sensor in view of its robustness to weather conditions such as fog, dust, rain and snow. The proposed approach is robust to noisy measurements since the radar target locations are modelled as Gaussian distributions. These observations are integrated into a Kalman Particle filter to estimate the posterior distribution of the parameters that best describe the geometry of the road. Experimental results using data acquired on a highway road are presented. The effectiveness of the proposed approach is demonstrated by a qualitative analysis of the results.
Idioma originalEnglish
Páginas4601
Número de páginas4607
DOI
EstadoPublished - 25 oct 2011
Evento2011 IEEE/RSJ International Conference on Intelligent Robots and Systems - San Francisco
Duración: 25 sep 2011 → …

Conference

Conference2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Título abreviadoIROS
PaísUnited States
CiudadSan Francisco
Período25/9/11 → …

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  • Citar esto

    Hernández Gutiérrez, A. (2011). Probabilistic road geometry estimation using a millilmetre-wave radar. 4601. Papel presentado en 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, . https://doi.org/10.1109/IROS.2011.6094848