LiDAR point cloud vehicle model

LiDAR for MLFF vehicle separation, classification and lane footprint.

LiDAR adds geometric intelligence to free-flow tolling by turning live traffic into a three-dimensional point cloud.

What LiDAR contributes

LiDAR sees the vehicle body, not only the plate or tag.

MLFF cameras identify visual evidence and RFID identifies tags, but LiDAR measures the physical object. It helps determine where the vehicle begins and ends, how tall it is, whether it crosses a lane boundary, and whether two close targets should be separated.

LiDAR data fields

  • X/Y/Z point location
  • Point intensity/reflection
  • Object contour and footprint
  • Height envelope and separation gaps
  • Lane-zone occupancy
MLFF problem solved

From point cloud to toll-grade evidence.

Vehicle separation

Separates close-following cars, truck-trailer combinations, motorcycles and vehicles moving side-by-side near lane boundaries.

Classification support

Height, length, contour and envelope features support category validation when ANPR or RFID data is insufficient.

Lane footprint

Vehicle footprint is mapped against the gantry charging zone to resolve lane-change and straddling scenarios.

Audit confidence

LiDAR evidence is fused with RFID, ANPR and radar tracks to generate transaction confidence and exception flags.

Gantry with roadside tolling sensors
Sensor fusion

LiDAR is strongest when paired with 4D radar.

4D radar provides robust motion tracks - range, azimuth, elevation and velocity. LiDAR provides physical geometry. Together they help the system maintain vehicle identity during occlusion, lane shifts and dense traffic.

RadarMotion, velocity, elevation, continuity
LiDARShape, footprint, height, separation
FusionTrusted vehicle twin for transaction processing
Explore Sensor Fusion
Video placeholders

LiDAR demo video concepts

Point Cloud Under Gantry

Animate vehicles passing through a LiDAR scan plane, generating 3D object profiles.

Truck + Motorcycle Separation

Show LiDAR distinguishing smaller vehicles from larger occluding vehicles in dense traffic.

Lane Footprint Mapping

Visualize a vehicle straddling lanes and the system resolving the correct tolling zone.

Fusion With 4D Radar

Show radar motion tracks merged with LiDAR geometry to create a digital vehicle twin.