Roadside Multi-LiDAR Data Fusion for Enhanced Traffic Safety

Roadside LiDAR (Light Detection and Ranging) sensors promise safer and faster traffic management and vehicular operations. However, occlusion and small view angles are significant challenges to widespread use of roadside LiDARs. We consider fusing data from multiple LiDARs at a traffic intersection to better estimate traffic parameters than one can estimate from a single LiDAR. The key challenge is to calibrate multiple LiDARs both in time and space. The problem is more complex when heterogeneous sensors differ in resolution and are positioned arbitrarily on a traffic intersection.

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Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1145/3690624.3709410
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.80
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Roadside Multi-LiDAR Data Fusion for Enhanced Traffic Safety

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Roadside Multi-LiDAR Data Fusion for Enhanced Traffic Safety

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article en
1 citations

Abstract

Roadside LiDAR (Light Detection and Ranging) sensors promise safer and faster traffic management and vehicular operations. However, occlusion and small view angles are significant challenges to widespread use of roadside LiDARs. We consider fusing data from multiple LiDARs at a traffic intersection to better estimate traffic parameters than one can estimate from a single LiDAR. The key challenge is to calibrate multiple LiDARs both in time and space. The problem is more complex when heterogeneous sensors differ in resolution and are positioned arbitrarily on a traffic intersection.

University of New Mexico (US)
Openalex Percentile: Top 31%
Remote Sensing and LiDAR Applications
0.80
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