Data fusion for automated driving: An introduction

Author:

Schreier Matthias1

Affiliation:

1. Continental Teves AG & Co. oHG , Guerickestr. 7 , Frankfurt am Main , Germany

Abstract

Abstract Data fusion is one of the key ingredients of Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS). The article provides an introduction into the field by highlighting different possible data fusion categorizations and architectures alongside pros and cons. Benefits, limitations, and pitfalls of exemplary data fusion systems are presented, and the consequences of specific design choices discussed.

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Generic Dynamic Object Detection Based on Dynamic Grid Maps;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

2. A Multimodal Fusion System for Object Identification in Point Clouds with Density and Coverage Differences;Processes;2024-01-24

3. Data Fusion in Wireless Sensor Network: An Overview;2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON);2023-12-05

4. Deep RADAR Inverse Sensor Models for Dynamic Occupancy Grid Maps;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

5. Toward Collaborative Occlusion-free Perception in Connected Autonomous Vehicles;IEEE Transactions on Mobile Computing;2023

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