Development of dedicated solutions and algorithms for fatigue detection at work and in the field of automotive ADAS system testing
Fatigue detection takes center stage in Meccanica 42’s latest project, an innovative initiative aimed at improving workplace safety and enhancing the testing of Advanced Driver Assistance Systems (ADAS) in the automotive sector.
Following a successful bid for a call for tenders from the Tuscan Region, this project seeks to address one of the most pressing challenges in both industries—fatigue and its impact on performance and safety.
In fact, this is an issue Meccanica 42 really cares about: extensive research is being conducted on human-machine interaction to enhance system performance, with the goal of ensuring safer and more reliable driving tests.
The team’s objective is to pool their expertise to develop a solution that, through the analysis of large datasets, enables the objective assessment of a subject’s level of fatigue.
The goal - fatigue detection for safety
Car manufacturers are required to subject driver assistance systems to a validation process before they are placed on the market.
General Safety Regulation 2 (GSR2) required manufacturers to equip new vehicles with a range of ADAS systems with the aim of saving lives and reducing the costs of road accidents. In fact, driver’s fatigue is one of the main causes of road accidents in Europe, estimated at between 10% and 25%.
Today, homologation tests involve a test driver driving on the road in difficult conditions while a verifier visually monitors his state of alertness and fatigue. Third-party devices with sensors are sometimes used to detect indicators, such as eye movement, but such systems are limited in terms of reliability and usability.
Physical and mental fatigue decreases an operator’s lucidity, decision-making capacity and ability to react and is therefore closely related to the increased likelihood of making mistakes and creating situations that are potentially dangerous to the safety of the operator and others.
If we take the construction or shipbuilding sectors as an example, where there is frequently prolonged and simultaneous exposure to harsh working conditions, we can understand how these factors represent important risk elements and can induce physical and psychological stress in the worker and reduce the attention threshold.
The aim of the project is to develop a solution for fatigue detection, stress monitoring and the identification of distraction factors of a vehicle driver, using objective markers.
This solution could be applicable both in the automotive context during the approval of Advanced Driver Assistance Systems (ADAS) and to prevent accidents at work.
Why is this project innovative?
The solution proposed by the team differs from what is available to date for determining the level of fatigue by relying on objective data monitored by a multiplicity of sensors, worn by the operator and installed inside the vehicle cabin, and processed by dedicated and scientifically validated algorithms.
Another key aspect of this project is the companies’ focus on developing a solution applicable across multiple contexts: the automotive industry and workplace safety in the shipbuilding sector.
How fatigue is detected
The team will develop a control unit that aggregates data measured by wearable or installable sensors inside the passenger compartment (without obstructing the driver’s visibility) and vehicle parameters to objectively assess the driver’s state of fatigue.
Central and peripheral biomarkers will be considered, such as
- brain electrical activity
- eye movements and pupil size
- heart rate
- skin conductance
- body temperature
Partners and their roles
The project is supported by a collaboration with highly specialized partners, each contributing unique expertise:
- Meccanica 42 will develop the system in terms of hardware and firmware
- Formula Medicine will develop algorithms for analysing the data retrieved from the system and work on the development of wearable systems suitable for the purpose.
- ScuolaIMT will take care of the reliability of the measurements conducted with wearable instruments and the scientific validation of the data processing algorithms, involving a team of neuroscientists and biomedical engineers.
- Cantiere Navale Arno will be involved as a case study for the validation of the proposed solutions in an operational shipyard environment.
This project aims to make a significant advancement in the state of the art for solutions that provide objective, parameter-based measurements of vehicle driver fatigue.
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