Automated Traffic Management System
Software Engineering — .NET Core, ClickHouse, WebSocket, Grafana
A pilot traffic management system for downtown business district, providing real-time data analytics and optimization recommendations to improve traffic flow during peak hours and incident response times.
Challenge
City traffic department lacked unified data analysis system for traffic pattern optimization in the central business district, leading to inefficient signal timing, congestion during peak hours, and limited ability to respond to incidents or optimize traffic flows based on real-time conditions.
Solution
Implemented pilot traffic data analytics platform for downtown district with real-time monitoring, pattern analysis, and optimization recommendations. The 28-week project included stakeholder coordination, regulatory approvals, and phased deployment across the central business district.
Technical Details
- Frontend: React dashboard with WebSocket connections, Grafana visualization
- Backend: .NET Core, RabbitMQ message queues, data processing pipelines
- Database: PostgreSQL, ClickHouse for time-series analytics
- Infrastructure: Docker deployment, Elasticsearch for search and logging
- Integrations: Municipal traffic sensor APIs, emergency services systems, GPS data feeds
Key Features
- Real-time data collection from traffic sensors and cameras in pilot zone
- WebSocket-powered live traffic monitoring dashboard
- ClickHouse analytics for traffic pattern analysis
- Traffic signal timing optimization recommendations
- Grafana dashboards for traffic pattern visualization
- Incident detection and emergency response coordination
Results
- 10% improvement in traffic flow during peak hours in pilot district
- 15% improvement in emergency response coordination times
- 25% better incident detection and response capability
- Successful pilot program approved for expansion to additional districts
- Positive stakeholder feedback leading to Phase 2 funding approval