The requirements for regulatory vehicle identification are changing rapidly. With an increasing need for streamlined processes, enhanced security, and international collaboration, there’s a pressing demand for a universally compatible approach.
RAIN technology, which effectively links the digital world to the real world, provides a proven and effective solution. However, when RAIN systems rely heavily on centralized online databases—especially when these databases are interconnected to facilitate data sharing among authorities—they can introduce risks such as data going out of sync, potential compromises, inaccessibility without an internet connection, and data privacy concerns. By adopting strategies that mitigate these risks—such as minimizing reliance on interconnected databases—we can enhance the effectiveness and security of vehicle identification systems.
Challenge
The primary method of vehicle identification—the license plate—poses significant challenges when used as the sole identifier. License plates are susceptible to alteration and cloning, making it difficult to detect anomalies and prevent fraud through visual recognition alone. Reliance on online databases to retrieve vehicle information introduces additional risks, including data inconsistency, potential inaccessibility, and privacy concerns.
Moreover, the heterogeneity of vehicle identification systems across nations, coupled with the lack of a universally accepted data encoding standard, exacerbates inconsistencies and inefficiencies.
There is a pressing need for a standardized yet adaptable approach that enables autonomous, reliable vehicle identification, reduces dependence on online databases, enhances security, and facilitates effective international collaboration.
Modern Solutions
To address the challenges in vehicle identification, we can learn from existing approaches that tackle similar issues. Some of these solutions are designed for tolling purposes, while others focus on data encoding and interoperability on a broader scale. By examining these modern approaches—including both regulatory frameworks and tolling systems—we can identify effective strategies and technologies to adapt into a comprehensive approach for regulatory vehicle identification.
ISO/IEC 20248 provides a standardized framework for data encoding and digital signatures, enhancing security and interoperability in vehicle identification systems. By using unique Field IDs for each data element, it supports translatability and maintains global compatibility, allowing vehicle information to be accurately interpreted across different languages and regions. This standard is highly relevant for developing a universally compatible and secure regulatory vehicle identification system.
6C Coalition’s AVI Standard (Version 3.2): This standard is based on the ISO/IEC 18000-63 (6C) communication protocol tailored for tolling applications utilizing Automatic Vehicle Identification (AVI). It addresses key areas such as transponder memory mapping, interoperability requirements, and barcode format. Serving as a benchmark for integrators and agencies, the AVI Standard ensures interoperability across different tolling systems. While designed for tolling, its methodologies and data structures offer valuable insights for regulatory vehicle identification by demonstrating effective practices in data encoding and system integration.
National Highway Authority of India (NHAI), FASTag is an electronic toll collection system that utilizes RAIN technology to streamline toll payments across India’s extensive highway network. While primarily designed for tolling purposes, FASTag demonstrates the scalability of RAIN technology in managing large volumes of vehicles and transactions. However, its reliance on centralized databases for data retrieval and processing presents limitations concerning data privacy and cross-border interoperability. These factors highlight challenges that need to be addressed when developing a regulatory vehicle identification system that aims for global compatibility and enhanced security.
Automatic Number Plate Recognition (ANPR) and Online Databases: offers a modern approach to vehicle identification by capturing and digitizing license plate images for applications such as toll collection and traffic enforcement. However, this method presents significant challenges: license plates can be altered or cloned, complicating fraud detection through visual recognition alone.
Additionally, reliance on online databases introduces risks like data inconsistency, inaccessibility without internet connectivity, and privacy concerns related to sensitive information. The diverse license plate formats across nations further exacerbate inefficiencies and highlight the absence of a universally accepted data encoding standard. These limitations underscore the urgent need for more robust and secure identification methods that enable autonomous, reliable vehicle identification, reduce dependency on online databases, and support effective international collaboration in regulatory vehicle identification systems.
Proposed solution
To address the challenges of inconsistent vehicle identification systems and enhance global interoperability, we propose adopting a standardized RAIN data structure that integrates ISO/IEC 20248 with the 6C Tolling Coalition’s data model.
This universal framework implements core mandatory data fields—such as vehicle license plate, VIN, vehicle type, and manufacturer—while allowing countries the flexibility to include additional data tailored to their regulatory needs. Leveraging ISO/IEC 20248 ensures secure, self-sovereign data management on RAIN tags, supports multilingual data fields for global accessibility, and enhances security through Tag Identifier (TID) referencing to prevent cloning or counterfeiting.
This standardized approach fosters international collaboration, strengthens security measures, and facilitates the integration of vehicles into smart city infrastructures, establishing a unified and efficient global vehicle identification system.
This is an excerpt from a white paper created by the RAIN Alliance Smart Mobility Work Group Steyn Geldenhuys, Sieveo; Anurag Kulshrestha, Anantics; Bertus Pretorius, Tönnjes; Bud Courville, EM Microelectronic; James Goodland, NXP Semiconductors; and Ashesh Ranjan, ID Tech Solutions.
The white paper is available to RAIN Alliance members on Basecamp. Not a member? Learn more about the benefits of RAIN Alliance membership.
Here is the table of contents for the white paper:
- Current Landscape: Inconsistencies and Limitations
- Modern Solutions to Global Compatibility
- Key Features of ISO/IEC 20248: Broad Applications in Data Standardization
- Roadmap to Implementation: Harmonizing 6C Coalition and ISO/IEC 20248 Data Structures
- Core data structure and additional data .
- The Power of Translatability and Universality
- A future with an open access verifiable vehicle identity
- Conclusion and Path Forward
- Annex A: Proposed DDD Structure