CyberMAP

Cyber-physical Multi-factor Authentication-based Positioning for Autonomous Vehicles

Autonomous vehicles (AVs) have rapidly become a major focus of the automotive industry in recent years. The promise of autonomous vehicles is that they have the potential to revolutionize transportation, providing greater safety, sustainability, efficiency, and accessibility. However, AVs cannot operate at full performance without enhancing modern roads, and as vehicles evolve in technology levels, so too must the infrastructure advance and evolve. Infrastructure such as roads and highways that exist today were primarily designed for human-driven vehicles with signage, markings, and signals designed almost exclusively for human perception and response. This presents a challenge for the integration of autonomous vehicles into the existing transportation system, as they operate differently from traditional vehicles and may have different infrastructure needs.

This project introduces the shapetag, a concept similar to “hyperlinks” on a webpage, which creates an easily located yet specific information-rich cue that allows an AV to access and/or verify its location and obtain geo-specific data.

Shapetag, using geometric patterns, can generate a vast array of unique 2D and 3D marks. These marks serve as secure, serialized, hard-to clone identifiers, both for physical and digital entities. Their uniqueness ensures rapid authentication via conventional mobile devices and guarantees security against unauthorized decoding. Because the geo-tags can encode information that is geo-referenced, the AV’s localization process is externally verified, allowing the AV to determine the precise location of the vehicle within its environment.

Project Goals

The primary objective of CyberMAP is to validate the shapetag concept as a cyber-physical infrastructure component that can support reliable and precise AV localization. The project aimed to demonstrate a working proof of concept through testing at the AstaZero proving ground in Sweden and at Penn State University's AV test facilities in the United States.

Project Activities

The project involved:

Designing shapetags capable of maintaining detection and authentication across a range of environmental conditions, including varied lighting, weather, and distance.
Conducting both simulation-based and real-world tests at AstaZero and Penn State to assess detection performance, positioning trace consistency, and robustness of localization.
Submitting the paper “Markers for Automated Vehicles: Technologies, Applications, and Future Directions” to IAVVC 2025, summarizing the research findings and outlining future development paths.

Results

CyberMAP successfully demonstrated the potential of geo-referenced infrastructure markers to enhance positioning reliability in autonomous vehicles—especially in environments where satellite signals are unreliable.
Key outcomes include:

Prototype validation of the shapetag system under diverse real-world and simulated conditions.
High detection consistency and trace reliability across multiple test runs at AstaZero and Penn State.
Submission of scientific findings to the IAVVC 2025 conference, contributing to the ongoing research community in trusted AV localization.

Future Development and Impact

As a next step, the CyberMAP prototype will undergo further evaluation in live driving environments to assess its scalability, robustness, and readiness for integration into future autonomous transport infrastructure. The project demonstrates a promising path toward safer and more reliable AV operation and showcases how physical and digital systems can work together to build trusted mobility solutions.