AI4CCAM
Trustworthy Artificial Intelligence for Connected Cooperative & Automated Mobility
Fostering the adoption of Trustworthy AI in CCAM.
Vision.
To provide automated driving scenarios involving ethical, social, and cultural choices, introducing advanced AI models for predicting vulnerable road users’ (VRU) behaviour and considering factors for enhancing user acceptance of self-driving vehicles.
The challenge.
Artificial intelligence (AI) has the potential to revolutionise the future of automotive mobility services by using massive amounts of sensor data and supporting all parts of the sense-plan-act paradigm. However, the benefits of AI in CAVs are constrained by ethical concerns that may limit its adoption by vulnerable road users (VRUs) such as pedestrians, cyclists, and people with impairments.
The Trustworthy AI ethical guidelines advocate the development of transparent, responsible, and human-centric AI systems, while the ethics recommendations for CAVs suggest reducing opacity in algorithmic decisions by developing "explainability-enhancing technologies in relation to data collection and algorithms used for CAV decision-making."
Ethical Concerns
Limited Adoption
Guideline Conflict
Approach & solutions.
To address this challenge, AI4CCAM will develop new techniques and models for integrating transparent and explainable AI solutions in connected and automated vehicles for improved road safety, whilst accounting for user acceptance. The work focuses on pedestrian, cyclist and road-users recognition, users behaviour prediction and action triggering in urban traffic conditions.
The project will :
- develop an interoperable digital framework for managing and generating AI-based urban-traffic scenarios
- test trustworthy-by-design AI models
- foster acceptance of AI in automated driving
- determine AI risks
- identify biases in datasets and cyber-threats
Τhe project will provide automated driving scenarios involving ethical, social, and cultural choices, introducing advanced AI models for predicting vulnerable road users’ (VRUs) behaviour and considering factors for enhancing user acceptance of self-driving vehicles.
USE CASES
Novel AI services tested in real-life industrial settings.
Simulation scenarios of road users interacting with automated vehicles will be developed and evaluated in three complementary use cases covering the whole sense-plan-act paradigm and user acceptance.
In alignment with the European principles of “Trustworthy AI”, AI4CCAM will focus on the development of Trustworthy AI for automated driving assistance pursuing 4-5 driving automation level meaning high and full automation.
Our role.
INLECOM will develop a validation methodology of the use cases to guide the simulation-based trials and measure the efficiency of the new techniques. INLECOM is also responsible for conducting a detailed Market Analysis around the AI4CCAM ambitions, urban-traffic scenarios, and reusable hybrid AI models and will develop the project’s exploitation roadmap and elicit the project innovations in AI4CCAM registry leading to the filing of two patents.
This project has received funding from the Horizon Europe research and innovation programme under GA 101076911. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the granting authority can be held responsible for them.
