| Title |
Towards High Accuracy Low Latency Real-Time Road Information Collection: An Edge-Assisted Sensor Fusion Approach |
| ID_Doc |
43508 |
| Authors |
Luo, Y; Wang, F; Liu, JC |
| Title |
Towards High Accuracy Low Latency Real-Time Road Information Collection: An Edge-Assisted Sensor Fusion Approach |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/MSN53354.2021.00099 |
| Abstract |
In order to have low-latency real-time response to applications such as Vehicle-to-everything (V2X) communications in Intelligent Vehicle System, edge computing as a paradigm has been proposed to put computing resources near the data origin. The limited computing resources in edge devices results in degraded object recognition results. To resolve this problem, high-level sensor fusion is a promising solution, which make uses of object-level information from multiple sensors to increase the accuracy. However, general high-level camera-radar fusion method does not work well in street information collection scenario. In this paper, we identified the key challenges in low-latency street information collection scenario and developed a multipath-resistant camera-radar sensor fusion method to increase the performance of sensor fusion method in such a scenario. Extensive experiments have shown that our system can increase 45% of detection rate and reduce 13% of error on edge devices comparing with a state-of-the-art method. |
| Author Keywords |
sensor fusion; smart city; edge computing; radar; v2x |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000817822300083 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Theory & Methods; Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Computer Science; Engineering; Telecommunications |
| PDF |
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