Project Description:

The PRISMA project proposes an innovative solution that goes beyond current Driver Monitoring Systems (DMS). The intelligent and adaptive virtual assistant being researched in this project represents a qualitative leap forward in driving safety. By combining advanced perception technologies, artificial intelligence, and adaptive learning, PRISMA aims to create a system capable of gaining an in-depth understanding of the driver’s condition and the cabin environment, anticipating risk situations, and responding in a personalised manner.

Main Objective:

The core objective of the PRISMA project is to research and conceptualise a next-generation driving assistance system based on artificial intelligence and advanced perception technologies. The system will be capable of monitoring, understanding, adapting to, and interacting in a personalised way with the driver and the vehicle cabin, with the aim of significantly improving road safety and contributing to the goal of zero road accidents.

General Project Objectives:

• GO1: Advance scientific and technological knowledge of communication systems for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) information exchange through the use of 5G communications, enabling the development of safer driving.
• GO2: Reduce road accidents through the advanced deployment of technologies that enable real-time information for safer driving.
• GO3: Conduct Proofs of Concept (PoCs) to validate the technologies under research, paving the way for future development and commercialisation.
• GO4: Develop an ecosystem involving companies and technology centres to foster effective collaboration in the provision of comprehensive V2X communication solutions for safer driving.
• GO5: Strengthen and position the Consortium and its member companies as leaders in their respective fields, facilitating their participation in international initiatives.

Specific Project Objectives:

The specific objectives of the project cover the different technologies to be researched:

• SO1: Research advanced perception algorithms based on computer vision and artificial intelligence.
• SO2: Advance the generation and use of synthetic data for training perception systems.
• SO3: Design adaptive communication algorithms for system-driver interaction.
• SO4: Research and conceptualise an innovative hardware system for PRISMA processing and integration.
• SO5: Design methods for secure integration with vehicle systems.

Project Duration:

October 2024 – December 2025

National collaborative project with:

ITCL will work together with Rovimática on: the development of a Human-Agent Interface based on Large Language Models (LLMs) to enable intuitive and effective interaction between the user and a driving assistant, as well as the development of a personalisation system for an AI Agent based on Large Language Models (LLMs), capable of adapting in real time to the user’s needs, preferences and context.

Funded by