Core Infrastructure

• Runtime Environment: Node.js (JavaScript)
• Cloud Services: Google Cloud Platform (GCP)
• API: Google Maps Routes API (v2 computeRoutes)

Data Storage

• Format: JSON (traffic-log.json) - Flat-file storage for historical data logging.

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Working

The system is designed to act as an automated "Traffic Watchdog" for specific routes in cties, running entirely in the cloud via GitHub Actions.

1. Automated Scheduling (Time-Gated)

Instead of running 24/7, the system uses a Time Window Logic in the GitHub Action workflow. It converts UTC server time to IST and only executes the script during relevant traffic hours to optimize API usage:

• Morning Rush: ~09:00 AM – 11:00 AM IST
• Afternoon/School: ~01:00 PM – 04:00 PM IST
• Evening Peak: ~06:30 PM – 09:00 PM IST

2. Route Analysis

The script iterates through a pre-defined list of Origin-Destination pairs (LOCATIONS). For each route, it requests the "Traffic Aware Optimal" travel time from Google Maps.

3. Traffic Severity Algorithm

Unlike standard maps that just show colors, this system calculates a precise Delay Percentage by comparing the Current Travel Time against a pre-defined Free Flow Time (ideal condition time).

$$ \text{Delay %} = \left( \frac{\text{RealTime} - \text{FreeFlow}}{\text{FreeFlow}} \right) \times 100 $$

Classification Thresholds:

• Normal: Delay < 25%
• Moderate: 25% ≤ Delay ≤ 60%
• Heavy: Delay > 60%

4. Data Persistence

After every run, the system appends the traffic data (Timestamp, Duration, Distance, Traffic Status) to traffic-log.json. The GitHub Action then detects this file change and automatically commits and pushes the updated log back to the repository, creating a permanent historical record of traffic patterns.