About the role
The project develops next‑generation urban road usage charging systems that rely on GNSS‑based vehicle detection. It aims to build resiliency against GNSS signal disruptions, create data‑driven tools for planning and managing charging points, design cost‑effective frameworks to detect malicious activities (jamming, blocking, spoofing), and improve vehicle positioning using existing sensors and AI techniques. The work also explores low‑cost beacons for V2X communication to enhance system resilience and accuracy.
ResearchOnsite
Key Responsibilities
- Develop system resiliency against GNSS signal disruptions to ensure robust vehicle positioning for charging
- Create data‑driven tools to support planning and management of new and existing charging points
- Design a cost‑effective framework to detect malicious GNSS activities such as jamming, blocking, and spoofing
- Leverage existing sensors and AI techniques to improve positioning in GNSS‑challenged urban environments
- Explore the use of cost‑effective beacons to enable V2X communication for enhanced system resilience and accuracy
- Design test cases and conduct field trials to validate algorithm performance for malicious activity detection and improved vehicle positioning
Requirements
- Strong software development skills in C++ and Python, with hands‑on experience in system design, modular architecture, and interfacing multiple components
- Familiarity with AI‑assisted development workflows and AI tools for SDLC automation
- Ability to engage stakeholders to define use cases and system requirements
- Expertise in data analytics and signal processing algorithms