Vehicle driving through a lidar point-cloud scene

Lidar Testing Product

From Point Clouds to Proven
Perception.

End-to-end LIDAR validation measures range, accuracy, and object-detection performance in real-world conditions. LIDAR is vital for ADAS and autonomy; its performance must be proven. SpeedEdge offers a repeatable validation framework.

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02 Product intro

Prove Sensor Performance.
Don't Assume It.

A validation programme measures sensor accuracy in distance and objects. SpeedEdge's LIDAR Testing offers a structured framework for characterizing performance and producing actionable results.

  • Range and accuracy measurement of a lidar sensor 01

    Range &
    Accuracy

    Measure detection distance, distance error and angular accuracy against calibrated ground truth.

  • Lidar point cloud of a road scene 02

    Point-Cloud
    Validation

    Analyse resolution, point density, noise and drop-out across the sensor's field of view.

  • Detected road users in a lidar scene 03

    Object
    Detection

    Evaluate detection, classification and tracking performance for relevant road users.

  • Lidar sensor tested in challenging weather 04

    Environmental
    Testing

    Evaluate sensor robustness under challenging environmental conditions.

  • Lidar sensor calibration and mounting alignment 05

    Calibration &
    Alignment

    Verify intrinsic/extrinsic calibration and mounting alignment.

  • Hardware-in-the-loop lidar bench test 06

    HIL /
    Bench Testing

    Run automated hardware-in-the-loop and bench sequences for repeatable regression testing.

03 The LIDAR testing workflow

From Sensing to
Traceable Validation.

  1. 01. Configure

    Define the sensor setup, test environment and acceptance criteria.

  2. 02. Calibrate

    Establish the reference configuration and verify sensor alignment.

  3. 03. Capture

    Collect LIDAR data across defined test scenarios.

  4. 04. Measure

    Calculate the relevant sensor performance metrics.

  5. 05. Validate

    Compare results against defined requirements and targets.

  6. 06. Report

    Turn test results into traceable engineering evidence.

04 What we measure

One Sensor. Multiple
Performance Dimensions.

LIDAR performance needs to be evaluated across multiple measurable characteristics.

  • Vehicle range measured by lidar

    Range

    Measure maximum detection distance against target reflectivity.

  • Lidar accuracy check against a known target

    Accuracy

    Measure distance and angular error against calibrated ground truth.

  • Dense lidar point cloud

    Density

    Evaluate point-cloud resolution and points-per-object.

  • Objects detected in a lidar scene

    Detection

    Measure object detection and classification performance.

05 Lean-aware control

Built Around the Dynamics
of a Leaning Vehicle.

LIDAR Testing transforms sensor output into quantified performance evidence through a structured validation process.

  • Range & Accuracy

    Measure detection distance, distance error and angular accuracy against calibrated ground truth.

  • Point-Cloud Quality

    Resolution • Point Density • Noise • Drop-Out

  • Object Perception

    Validate detection, classification and tracking performance for:
    Cars • Pedestrians • Cyclists

  • Environmental Robustness

    Test sensor behaviour under:
    Rain • Fog • Dust • Glare • Temperature Extremes

  • Calibration

    Verify sensor configuration and mounting alignment.

Lidar validation dashboard with range, detection and point-cloud results
Earth from orbit

Let’s Build Mission-Critical
Engineering Together.

Partner with SpeedEdge for mission-critical engineering, compliance and validation.

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