Bayesian Road Estimation Using Onboard Sensors

Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455, Hammarstrand, Lars, Fatemi, Maryam and Svensson, Lennart (2014) Bayesian Road Estimation Using Onboard Sensors IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 15 (4). pp. 1676-1689. ISSN 1524-9050, 1558-0016

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Abstract

This paper describes an algorithm for estimating the road ahead of a host vehicle based on the measurements from several onboard sensors: a camera, a radar, wheel speed sensors, and an inertial measurement unit. We propose a novel road model that is able to describe the road ahead with higher accuracy than the usual polynomial model. We also develop a Bayesian fusion system that uses the following information from the surroundings: lane marking measurements obtained by the camera and leading vehicle and stationary object measurements obtained by a radar-camera fusion system. The performance of our fusion algorithm is evaluated in several drive tests. As expected, the more information we use, the better the performance is. © 2014 IEEE.

Item Type:	Article
Uncontrolled Keywords:	Camera, information fusion, radar, road geometry, unscented Kalman filter (UKF)
Depositing User:	Symplectic Admin
Date Deposited:	22 Jan 2020 09:57
Last Modified:	22 May 2026 23:13
DOI:	10.1109/TITS.2014.2303811
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3071562
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