Long-range road geometry estimation using moving vehicles and road-side observations
Journal article, 2016

This paper presents an algorithm for estimating the shape of the road ahead of a host vehicle equipped with the following onboard sensors: a camera, a radar and vehicle internal sensors. The aim is to accurately describe the road geometry up to 200 m ahead in highway scenarios. This purpose is accomplished by deriving a precise clothoid-based road model for which we design a Bayesian fusion framework. Using this framework the road geometry is estimated using sensor observations on the shape of the lane markings, the heading of leading vehicles and the position of road side radar reflectors. The evaluation on sensor data shows that the proposed algorithm is capable of capturing the shape of the road well, even in challenging mountainous highways.

Advanced driver assistance systems

Road geometry

Bayesian Estimation

Author

Lars Hammarstrand

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Maryam Fatemi

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Angel Garcia

Curtin University

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

IEEE Transactions on Intelligent Transportation Systems

1524-9050 (ISSN)

Vol. 17 8 2144-2158

COPPLAR CampusShuttle cooperative perception & planning platform

VINNOVA, 2016-01-01 -- 2018-12-31.

Areas of Advance

Transport

Infrastructure

ReVeRe (Research Vehicle Resource)

Subject Categories

Signal Processing

DOI

10.1109/TITS.2016.2517701

More information

Latest update

4/11/2019