Augmenting Car Surrounding Information by Inter-Vehicle Data Fusion

被引：0

作者：

Lee, Tzu-Kuang ^{[1
]}

Kuo, Yu-Chiao ^{[1
]}

Huang, Shih-Hsuan ^{[1
]}

Wang, Guan-Sheng ^{[1
]}

Lin, Chih-Yu ^{[1
]}

Tseng, Yu-Chee ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Dept Comp Sci, Hsinchu, Taiwan

来源：

2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2019年

关键词：

Autonomous Driving; Data Fusion; Sensing; V2V communication; COMMUNICATION;

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Collecting vehicle surrounding information is a key issue for accident prevention and autonomous driving applications. Although GPS and 4G/LTE are widely accepted. it is still a challenge for a vehicle to get complete information of its surrounding vehicles. In this work, we consider the integration of multi-sensory data through V2V communications to help a vehicle to understand its complex surroundings. We propose a fusion algorithm that can integrate four types of sensory inputs: V2V communications, GPS, camera, and inertial data. We show that through such fusion, it is possible for a vehicle to visually see the driving states of its surrounding vehicles.

引用

页数：6

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