AutoTRUST

AutoTRUST is a Horizon Europe research and innovation project focused on developing trustworthy, inclusive, and user-centric technologies for Connected, Cooperative and Automated Mobility (CCAM). The project brings together a multidisciplinary consortium of industrial, research, academic, and end-user partners to improve safety, comfort, accessibility, and trust in automated vehicles and future mobility services.

The main objective of AutoTRUST is to develop an AI-enabled self-adaptive framework that enhances the onboard experience of passengers and supports personalized, inclusive, and resilient automated mobility. The project combines advanced internal and external monitoring, multimodal sensing, cooperative situational awareness, in-cabin personalization, virtual assistant technologies, human–machine interfaces, and user-centered design methodologies. These technologies are validated through multiple pilots addressing public transport, autonomous mobility services, industrial vehicles, and vulnerable user groups.

What the AviSense's Simulator Demonstrates

The simulator presents a virtual urban-driving environment in which users can explore how connected and automated vehicle technologies interact with the driver and the surrounding road environment.

Virtual overlays can highlight nearby vehicles, pedestrians, road hazards and other relevant events in their correct spatial position. The AR interface is designed to help the driver:

• Identify potential hazards more quickly

• Understand where an alert is coming from

• Maintain awareness of road users that may be partially or fully occluded

The AR component highlights how information from vehicle sensors, infrastructure cameras and connected systems can be transformed into intuitive visual guidance. Its purpose is not to replace the driver’s attention, but to extend situational awareness and support faster, safer and better-informed decisions. The main objective is to highlight how:

• Information from vehicle and infrastructure sensors can improve situational awareness

• Drivers can remain informed and in control when automated assistance is active

• Human-centred interfaces can improve safety, usability and trust in connected and automated vehicles

The simulator is not intended as a conventional driving game. It is an interactive demonstration of how trustworthy AI and intuitive interfaces can support safer and more informed mobility.

How to Use the Simulator

• Wait for the simulator to load fully. Loading time may vary depending on your device and internet connection.

• Select Enter Full Screen for a more immersive experience. Press Esc to exit full-screen mode.

• Click inside the simulator window to activate the controls.

• Select one of the available scenarios and start the simulation. You can choose between different weather conditions and different visibility interfaces to explore how the system performs under varying environmental and visual conditions.

• Use the arrow keys or the W, A, S and D keys to navigate, where manual movement is available.

• Move the mouse to rotate the driver’s head and look freely in any direction within the simulated environment.

• Press M to release the mouse pointer from the simulator and move it outside the application window.

• Use the mouse pointer to select buttons, change available options and interact with the simulator interface.

For the best experience, use a desktop or laptop computer with an updated web browser.

⛶ Enter Full Screen

Ergonomic Analysis and Adaptive Vehicle Interior Design

The following video presents the work carried out within AutoTRUST Task "Ergonomic Analysis and Interior Adaptation", focusing on the development of a simulation framework for the systematic evaluation and optimisation of vehicle interiors.

The framework enables users to define and modify a wide range of parameters, including the anthropometric characteristics of a digital occupant and the configuration of the vehicle interior. Adjustable elements include the seat position and rails, steering wheel and steering column, head-up display, centre console and other controls that may influence occupant posture, reachability, comfort and fatigue.

For each interior parameter, users can specify minimum and maximum values, together with a step size. The system then automatically generates and evaluates multiple vehicle interior configurations. Digital avatars with different heights, body proportions and other occupant characteristics perform predefined in-cabin interaction tasks, such as reaching controls, using displays and monitoring the surrounding environment.

For every combination of avatar profile, interior configuration and interaction sequence, the resulting posture is assessed using the Rapid Upper Limb Assessment (RULA) methodology. The RULA score provides a quantitative indication of the ergonomic strain associated with the occupant’s posture.

By running multiple simulation iterations, the framework identifies the configuration of interior parameters that minimises the cumulative ergonomic strain for a specific occupant profile and interaction scenario.

This approach supports:

• The evaluation of different occupant sizes and body characteristics.

• The real-time assessment of changes to vehicle interior components.

• The identification of potentially uncomfortable or high-strain interactions.

• The optimisation of seat, steering, display and control positions.

• The development of inclusive, adaptable and user-centred vehicle interiors.

The overall objective is to enable data-driven interior adaptation strategies that improve comfort, accessibility and efficiency while reducing physical strain and fatigue, particularly during long journeys and future automated-driving scenarios.