Traffic Vehicle Counter
AI-Based Traffic Monitoring and Vehicle Analytics System
Manual traffic counting is slow and costly
Traditional traffic studies rely on manual counting or expensive hardware sensors. The results are limited in duration, prone to human error, and difficult to repeat. Cities and engineers need richer, continuous, and more affordable traffic intelligence.
AI vision turns any camera into a sensor
The Traffic Vehicle Counter uses computer vision to detect, classify, and track vehicles from standard camera footage. It produces validated counts and analytics that integrate directly into transport studies and smart-city dashboards — without specialized roadside hardware.
What the system can measure
A single video feed becomes a rich, multi-metric traffic dataset.
Vehicle Counting
Accurate directional vehicle counts across lanes and approaches.
Vehicle Classification
Cars, trucks, buses, motorcycles, and more by vehicle type.
Turning Movement Counts
Per-approach turning movements for intersection analysis.
Queue Length
Lane queue estimation to understand delay and saturation.
Congestion Monitoring
Flow, density, and speed indicators for congestion insight.
Pedestrian & Cyclist Detection
Vulnerable road user detection for safety-focused studies.
Built on modern vision tooling
Where it delivers value
- Traffic impact studies and transport planning
- Smart city intersection and corridor monitoring
- Construction-zone and temporary traffic management
- Before/after evaluation of road interventions
From counts to continuous intelligence
- Now
Counting & Classification
Reliable vehicle counting, classification, and turning movement counts from recorded or live video.
- Next
Real-Time Dashboard
Live congestion and queue monitoring with a smart-city dashboard and alerting.
- Future
Multi-Camera & Edge
Multi-camera corridor coverage with on-device edge inference and centralized analytics.
Run a smarter traffic study with Autonomax.
Share your footage or study goals and we'll show what the system can measure.