Vehicle Detection & Tracking

Tech Stack

The Problem

• Traffic management relied on inaccurate manual counting and ageing sensor infrastructure.
• Existing loop detectors and radar systems required costly installation, calibration, and ongoing maintenance.
• No unified system could track individual vehicles or classify types across multiple camera zones.
• Late and inaccurate data delayed emergency response routing and real-time traffic management decisions.
• No method existed to generate granular, lane-level, time-stamped vehicle count data at scale.

Our Solution

• Developed a YOLO-based detection pipeline with multi-object tracking for real-time vehicle analysis across lanes.
• Implemented vehicle classification identifying cars, motorcycles, trucks, and buses with high accuracy.
• Built multi-lane counting logic capable of handling complex intersections and overlapping trajectories.
• Designed plug-and-play deployment using existing road camera infrastructure with no hardware changes.
• Created exportable traffic density reports with time-stamped per-lane counts for traffic planning teams.

Impact

Automated traffic data collection across multiple lanes with 96% accuracy, replacing manual counting operations.