HIDDEN (Hybrid Intelligence for Advanced Collective Perception and Decision-Making in Complex Urban Environments) is a Horizon Europe research and innovation project that tackles a key challenge in urban mobility: occlusions—the inability of connected and automated vehicles (CAV) to detect road users or objects hidden from their line of sight.

HIDDEN is focused on advancing urban mobility through safer, smarter, and more ethical automation. At its core, HIDDEN develops collective awareness systems that enable connected and automated vehicles to detect occluded objects and vulnerable road users in real time. Using hybrid intelligence (HI), the project combines machine with human intelligence to support decision-making that aligns with human driving styles and ethical principles.

HIDDEN also addresses the legal, regulatory, and ethical challenges of AI in mobility, ensuring transparency and trust in how decisions are made.

Key innovations include:

  • Advanced behavioral models for predictive perception

  • Driver gaze tracking and status monitoring to inform ethical and explainable decisions

  • Simulation and real-world validations across Europe using 8 consortium-owned autonomous vehicles

  • A dedicated framework for ethical, legal, and regulatory alignment of AI systems in mobility

Field tests across Europe and virtual simulations will validate the technology in real-world scenarios.

Through close collaboration with type approval authorities, standardisation bodies, and key stakeholders, HIDDEN aims to set new benchmarks for safe and socially responsible autonomous mobility in complex urban settings.

OBJECTIVES

  • Design, develop and test failsafe AI-based collective awareness systems, focusing on detection of occluded objects, including VRUs, in complex urban settings.

  • Design, develop and test predictive decision-making agents that utilise collective awareness output and which are explainable and aligned with human driving styles and ethical principles.

  • Embed human intelligence in both perception and decision-making layers, while considering AI-related ethical and societal aspects, via the development of a dedicated toolset.

  • Reach out to CCAM stakeholders, in EU and beyond, concerning HIDDEN developments, engage in a continuous discussion with EU type approval authorities and UNECE working groups and promote mature results to standardisation.

USE CASES

Use Case 1

Protect darting out child hidden by parked vehicle in a school zone

Use Case 2

Protect worker hidden by vegetation in a road construction zone

Use Case 3

Protect cyclist or micro-mobility user hidden by vehicle in a vehicles-cyclists shared zone

Use Case 4

Protect vehicle hidden by buildings or a shuttle in an unsignalized intersection