Multi-Sensor Fusion for Obstacle Detection and Recognition: A Belief-based Approach

被引：0

作者：

Bouain, Mokhtar ^{[1
,2
]}

Berdjag, Denis ^{[1
]}

Fakhfakh, Nizar ^{[2
]}

Ben Atitallah, Rabie ^{[1
]}

机构：

[1] Univ Valenciennes, CNRS, UMR 8201, LAMIH, F-59313 Valenciennes, France

[2] Navya Co, Villeurbanne, France

来源：

2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) | 2018年

关键词：

Transferable Belief Model; Multi-Sensor Data Fusion; Obstacle Detection and Recognition; Intelligent Vehicles;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an obstacle detection and classification method for intelligent vehicles. We use both a camera and radar in a multi-sensor perception framework. Our main goal is to improve the reliability of pedestrian and vehicle recognition of the system, avoiding false alarms and reducing miss detections in an uncertain environment with imprecise models. To deal with this issue, an evidential sensor fusion is developed and implemented. Simulation results and preliminary experimental test are presented and confirm the reliability improvement.

引用

页码：1217 / 1224

页数：8

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