Bayesian Road Estimation Using Onboard Sensors

doi:10.1109/TITS.2014.2303811

2014-08-01

Ángel F. García‐Fernández *

Lars Hammarstrand

Maryam Fatemi

Lennart Svensson

DOI：10.1109/TITS.2014.2303811

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摘要

En 中文

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.

Keyword:

Camera

information fusion

radar

road geometry

unscented Kalman filter (UKF)

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期刊

IEEE Transactions on Intelligent Transportation Systems

IF:

8.4

论文数:

9.7K

被引数:

6.3W

机构

chalmers university of technology

学者数:

1.5W

论文数: 1.6W

被引数: 10

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