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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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Published on: February 25, 2013

A Three-Dimensional LiDAR Observability Framework for Pedestrian Representation: Sensor Placement and Multi-View

Juan Diego Valladolid¹, Juan P Ortiz², Franklin Castillo¹

¹Department of Automotive Engineering, Universidad Politécnica Salesiana, Cuenca 010107, Ecuador.

Sensors (Basel, Switzerland)

|May 13, 2026

Summary

Multi-LiDAR fusion enhances pedestrian 3D geometry representation for autonomous driving. Fused LiDAR configurations offer superior observability and robustness compared to single sensors, improving safety.

Keywords:

3D perception LiDAR sensing ROS 2 autonomous vehicles experimental evaluation pedestrian observability point cloud sensor fusion sensor placement

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Area of Science:

Robotics
Computer Vision
Autonomous Systems

Background:

Accurate 3D pedestrian geometry is crucial for autonomous driving safety.
Sensor viewpoint and data completeness significantly impact pedestrian representation.

Purpose of the Study:

To develop and evaluate a LiDAR-based observability framework for pedestrian 3D geometry.
To compare the performance of single vs. fused LiDAR configurations on the ANTA platform.

Main Methods:

Utilized geometric extent ratios, projected surface occupancy, and voxel-based volumetric occupancy.
Developed a global observability score (S3D) and a Distance-Robustness Index (DRI).
Analyzed data from Top LiDAR (TL), Front-Right LiDAR (FRL), and their fused configuration.

Main Results:

The fused LiDAR configuration achieved the highest mean global score (0.563) and robustness (DRI=0.5628).
Optimal pedestrian observability varied with distance: 1m for density, 2-3m for completeness, and 7m for balanced observability.
Complementary multi-LiDAR fusion provided superior geometry-aware pedestrian representation.

Conclusions:

Multi-LiDAR fusion significantly enhances pedestrian 3D geometric representation for autonomous driving.
The proposed framework effectively evaluates pedestrian observability across different sensor configurations and distances.
Fused LiDAR systems are essential for robust and complete pedestrian perception in autonomous vehicles.