Citation

Jo K, Kim C, Sunwoo M. Sensors (Basel) 2018; 18(9): s18093145.

Affiliation

Department of Automotive Engineering, Hanyang University, Seoul 04763, Korea. msunwoo@hanyang.ac.kr.

Copyright

(Copyright © 2018, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s18093145

PMID

30231492

Abstract

High Definition (HD) maps are becoming key elements of the autonomous driving because they can provide information about the surrounding environment of the autonomous car without being affected by the real-time perception limit. To provide the most recent environmental information to the autonomous driving system, the HD map must maintain up-to-date data by updating changes in the real world. This paper presents a simultaneous localization and map change update (SLAMCU) algorithm to detect and update the HD map changes. A Dempster⁻Shafer evidence theory is applied to infer the HD map changes based on the evaluation of the HD map feature existence. A Rao⁻Blackwellized particle filter (RBPF) approach is used to concurrently estimate the vehicle position and update the new map state. The detected and updated map changes by the SLAMCU are reported to the HD map database in order to reflect the changes to the HD map and share the changing information with the other autonomous cars. The SLAMCU was evaluated through experiments using the HD map of traffic signs in the real traffic conditions.

Language: en

Keywords

autonomous cars; cloud map; high definition (HD) map; localization; map change detection