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Bayesian Road Estimation Using Onboard Sensors

Angel Garcia-Fernandez (Institutionen för signaler och system, Signalbehandling) ; Lars Hammarstrand (Institutionen för signaler och system, Signalbehandling) ; Maryam Fatemi (Institutionen för signaler och system, Signalbehandling) ; Lennart Svensson (Institutionen för signaler och system, Signalbehandling)
IEEE transactions on intelligent transportation systems (1524-9050). Vol. PP (2014), 99, p. 1-14.
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: Camera, information fusion, radar, road geometry, unscented Kalman filter (UKF)



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Denna post skapades 2014-03-19. Senast ändrad 2017-01-27.
CPL Pubid: 195294

 

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Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling

Ämnesområden

Transport
Matematisk statistik
Signalbehandling

Chalmers infrastruktur