aware2all

Safety systems and human-machine interfaces oriented to diverse population towards future scenarios with increasing share of highly automated vehicles.

Safety systems for autonomous vehicles

Why are safety systems for autonomous vehicles necessary?

In 2020, someone died on European roads every 25 minutes, with a total of 18,844 people that lost their lives. It represents an unprecedented annual fall of 17% on 2019 result of lower traffic volumes due to the COVID-19 pandemic, but it is expected that traffic accidents will soar again once the pandemic subsides. More than 46% of those killed in Europe in 2018 were Vulnerable Road Users (VRUs) – pedestrians, cyclists and motorcyclists – and it was estimated that human error was involved in about 95% of all road traffic accidents. HAVs have the potential to improve road safety by reducing crashes due to driver error and also by representing an alternative to high-risk drivers (e.g., drunk or distracted drivers).
More than 46% of those killed in Europe in 2018 were Vulnerable Road Users (VRUs) – pedestrians, cyclists and motorcyclists – and it was estimated that human error was involved in about 95% of all road traffic accidents.

Object: Safety systems and human-machine interfaces oriented to diverse population

AWARE2ALL aims to pave the way towards the deployment in traffic of highly automated vehicles (HAV) – Connected and Automated Vehicles (CAVs) presenting SAE-L4 features – by effectively addressing the changes in road safety and in the interaction of different human road users (HRUs) caused by the emergence of HAV.

The project will develop safety systems adapted to these new scenarios in mixed traffic along with the corresponding assessment tools and methodologies. Two perspectives are considered:

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Project: Development of safety systems for HAVs in mixed traffic

The Horizon Europe (HE) project will develop safety systems adapted to these new scenarios in mixed traffic along with the corresponding assessment tools and methodologies. Two perspectives are considered:

1 —

Inside the vehicle

Oriented to occupant safety: a continuous occupant state monitoring (OMS) will assess the interior situation (e.g., activities performed by the occupants). In case of an emergency situation (e.g., sudden reach of the ODD limit due to an abrupt change of weather), the OMS will decide if it is possible to perform a transition of control to a driver or to perform a fallback manoeuvre and avoid a collision. If a collision is unavoidable, then advanced passive safety systems are adapted to the occupant status to reduce the severity of injuries. At any time, the behaviour of HAV systems needs to be adequately and timely communicated to the occupants by internal HMI (iHMI).

2 —

Outside the vehicle

Oriented to HRUs safety: a surround perception system will allow the HAV to identify the HRUs behaviour and to anticipate safety critical situations. By allowing the vehicle to effectively communicate with HRUs through external HMI (eHMI), dangerous situations could be avoided.

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Last news & events

News
Transfer Learning: An AI assisted method to accelerate the passive safety validation

Transfer Learning: An AI assisted method to accelerate the passive safety validation

14 / 11 / 24

Crash protection will be one of the 4 main focus points of the future EuroNCAP assessment plan due to raising requirements for the occupants’ safety as well as more sophisticated passive safety systems. To assess the performance of passive safety systems the vehicle size, the structural design and the restraint systems are crucial. Assuming a […]

News
DiverSim: an Inclusive Simulator for Diverse Synthetic Pedestrian Data Generation

DiverSim: an Inclusive Simulator for Diverse Synthetic Pedestrian Data Generation

25 / 10 / 24

One of the critical challenges in autonomous driving and AI-based systems is the lack of diverse and representative datasets. Existing datasets often fail to reflect the broad range of pedestrians found in real-world scenarios—especially underrepresented groups such as people with disabilities or individuals from various ethnic minorities. This gap in representation can lead to the […]

News
Improving Pedestrian-Vehicle Communication with Acoustic and Visual Interfaces (eHMI)

Improving Pedestrian-Vehicle Communication with Acoustic and Visual Interfaces (eHMI)

27 / 09 / 24

The primary goal of AWARE2ALL is to tackle the new safety issues that arise with the introduction of highly autonomous vehicles in mixed traffic environments. This will be achieved by developing inclusive and innovative safety systems (both passive and active) and Human-Machine Interaction (HMI) systems, both external and internal. These systems will consider the diverse […]

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🚗 New on the AWARE2ALL Blog! 🚗

Discover how we're using AI and transfer learning to make crash testing safer, faster, and more inclusive of diverse body types. Read our latest article:
#AWARE2ALL #CrashSafety #AI

🚗 Advancing Inclusive AI for Autonomous Vehicles! 🚶‍♀️
We've developed #DiverSim to address the lack of diverse pedestrian data for #AI. Built on #UnrealEngine5, DiverSim generates inclusive, realistic datasets to enhance safety in autonomous driving.

🚗 How can we make #AutonomousVehicles safer for all? At AWARE2ALL, we're creating inclusive safety systems & HMIs to improve communication between AVs & pedestrians, especially vulnerable road users. Read more on how we're enhancing road safety: #Safety

📢We are at #TRA2024 Conference in Dublin 🇮🇪‼️
And our colleague Dr. 𝗡𝗲𝗿𝗲𝗮 𝗔𝗿𝗮𝗻𝗷𝘂𝗲𝗹𝗼, researcher of Connected & Cooperative Automated Systems presented yesterday the @AWARE2ALL_he project💥

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