AI Traffic Control System

Eastgate delivered an embedded traffic control system integration for an ITS client in Germany, connecting traffic signal logic to existing infrastructure through protocol-based TCP/IP communication. The solution includes a Linux-based edge application and a handheld configuration interface for field operators. The 12-month project achieved full legacy system compatibility and sub-100ms real-time traffic control.

Challenge

• Needed to integrate a traffic control system into existing infrastructure while maintaining compatibility with legacy protocols and hardware.
• Required protocol-based communication for centralized monitoring and control of traffic signals and detectors.
• Lacked a configurable handheld interface for field engineers to perform configuration and real-time control.
• System had to operate reliably on edge devices with Linux-based deployment in field environments.

Solution

• Integrated traffic control logic into an embedded controller system compatible with existing infrastructure.
• Implemented protocol-based TCP/IP communication for centralized monitoring and control.
• Delivered real-time data exchange for traffic signal control and detector data processing.
• Built a handheld interface for field configuration and real-time monitoring by operators.
• Deployed a Linux-based application on edge device for reliable field operation.

Architecture

Outcome

• Achieved 100% compatibility with existing legacy system infrastructure and protocols.
• Delivered real-time traffic monitoring and control with latency consistently under 100ms.
• Improved operational efficiency by 30-40% through centralized control and field tooling.

Tech Stack

• Backend: Python
• Protocols: TCP/IP
• Infrastructure: Linux
• CI/CD: SonarQube