Work

Map-aided localization with lateral perception

Year: 2014

Type: conference-paper

Abstract: Accurate localization of a vehicle is a challenging task as GPS available on the market are not designed for lane-level accuracy application. Although dead reckoning helps, cumulative errors from inertial sensors result in a integration drift. This paper presents a new method of localization based on sensors data fusion. An accurate digital map of the lane marking is used as a powerful additional sensor. Road markings are detected by processing two lateral cameras to estimate their distance to the vehicle. Coupled with the map data in a EKF filter it improves the ego-localization obtained with inertial and GPS measurements. The result is a vehicle localization at an ego-lane level of accuracy, with a lateral error of less than 10 centimeters.

Source: IEEE Intelligent Vehicles Symposium

DOI: 10.1109/ivs.2014.6856528

Authors: Dominique Gruyer, Rachid Belaroussi, Marc Revilloud

Language: English

Topic: Robotics and Sensor-Based Localization

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: Agence Nationale de la Recherche, Else Kröner-Fresenius-Stiftung

OpenAlex ID: W2107059967

FWCI: 5.409

Cites: 17

Cited by: 71

Related to: 10