Road geometry estimation using a precise clothoid road model and observations of moving vehicles

An important part of any advanced driver assistance system is road geometry estimation. In this paper, we develop a Bayesian estimation algorithm using lane marking measurements received from a camera and measurements of the leading vehicles received from a radar-camera fusion system, to estimate th...

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Main Authors: Fatemi, M., Hammarstrand, L., Svensson, L., Garcia Fernandez, Angel
Format: Conference Paper
Published: IEEE 2014
Online Access:http://hdl.handle.net/20.500.11937/49852
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author Fatemi, M.
Hammarstrand, L.
Svensson, L.
Garcia Fernandez, Angel
author_facet Fatemi, M.
Hammarstrand, L.
Svensson, L.
Garcia Fernandez, Angel
author_sort Fatemi, M.
building Curtin Institutional Repository
collection Online Access
description An important part of any advanced driver assistance system is road geometry estimation. In this paper, we develop a Bayesian estimation algorithm using lane marking measurements received from a camera and measurements of the leading vehicles received from a radar-camera fusion system, to estimate the road up to 200 meters ahead in highway scenarios. The filtering algorithm uses a segmented clothoid-based road model. In order to use the heading of leading vehicles we need to detect if each vehicle is keeping lane or changing lane. Hence, we propose to jointly detect the motion state of the leading vehicles and estimate the road geometry using a multiple model filter. Finally the proposed algorithm is compared to an existing method using real data collected from highways. The results indicate that it provides a more accurate road estimation in some scenarios.
first_indexed 2025-11-14T09:42:17Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:42:17Z
publishDate 2014
publisher IEEE
recordtype eprints
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spelling curtin-20.500.11937-498522017-09-13T16:00:09Z Road geometry estimation using a precise clothoid road model and observations of moving vehicles Fatemi, M. Hammarstrand, L. Svensson, L. Garcia Fernandez, Angel An important part of any advanced driver assistance system is road geometry estimation. In this paper, we develop a Bayesian estimation algorithm using lane marking measurements received from a camera and measurements of the leading vehicles received from a radar-camera fusion system, to estimate the road up to 200 meters ahead in highway scenarios. The filtering algorithm uses a segmented clothoid-based road model. In order to use the heading of leading vehicles we need to detect if each vehicle is keeping lane or changing lane. Hence, we propose to jointly detect the motion state of the leading vehicles and estimate the road geometry using a multiple model filter. Finally the proposed algorithm is compared to an existing method using real data collected from highways. The results indicate that it provides a more accurate road estimation in some scenarios. 2014 Conference Paper http://hdl.handle.net/20.500.11937/49852 10.1109/ITSC.2014.6957698 IEEE restricted
spellingShingle Fatemi, M.
Hammarstrand, L.
Svensson, L.
Garcia Fernandez, Angel
Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title_full Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title_fullStr Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title_full_unstemmed Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title_short Road geometry estimation using a precise clothoid road model and observations of moving vehicles
title_sort road geometry estimation using a precise clothoid road model and observations of moving vehicles
url http://hdl.handle.net/20.500.11937/49852