Probabilistic road geometry estimation using a millilmetre-wave radar

Research output: Contribution to conferencePaper

Abstract

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.
Original languageEnglish
Pages4601
Number of pages4607
DOIs
Publication statusPublished - 25 Oct 2011
Event2011 IEEE/RSJ International Conference on Intelligent Robots and Systems - San Francisco, United States
Duration: 25 Sep 2011 → …

Conference

Conference2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS
CountryUnited States
CitySan Francisco
Period25/9/11 → …

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