Periodic Reporting for period 2 - FITDRIVE (Monitoring devices for overall FITness of Drivers)
Periodo di rendicontazione: 2023-03-01 al 2024-02-29
The aim of determining fitness to drive is to achieve a balance between minimising any driving-related road safety risks for the individual and the community and maintaining the driver’s lifestyle and employment-related mobility independence. Driving a car is a complex and dynamic task and there is a wide range of conditions that temporarily affect the ability to drive safely like consuming substances or fatigue. Professional drivers are particularly affected by fatigue. The main effect of fatigue is a progressive withdrawal of attention from the road and traffic demands leading to impaired driving performance. The particular practice of professional drivers include working long shifts, working irregular hours, little or poor sleep in the cabin, little physical exercise, quick and unhealthy meals, and stress which in many cases lead to fatigue. Fatigue causes reduced alertness, longer reaction times, memory problems, poorer psychometric coordination, and less efficient information processing. The results of different surveys world-wide show that over 50% of long-haul drivers have at some time almost fallen asleep at the wheel.
The FitDrive project was conceived to identify and prevent driving stress states for professional drivers (and consequently driving fitness) with artificial intelligence and machine learning techniques able to build a “usual" driving profile of each driver after some thousands of kms driven. Once the "usual" driving profile of a specific driver has been defined, the AI system is able to detect “unusual” behaviour (outside the "usual" range of parameters) and associate them with the most probable causes, such as fatigue, or other cognitive disorders. The behavioural function consists of a set of indicators representing the range of usual driving behaviour for each specific driver, which will be defined by the self-learning system during a period of ordinary driving. Deviations are determined by the comparison between daily driving results and the personal “usual” profile.
The FitDrive system will provide a continuous screening of the driver's psychophysical capabilities, alerting him or her to potential impairment on the way: in fact, the abnormal variations detected by the Artificial Intelligence can be associated with early situations of sickness that are not yet apparent to the subject but are about to manifest. The system will continuously learn and adapt itself to the driver: this means that the more a subject drives, the more the system profiles him/her and the more is able to make precise detection of anomalies, and the system will also be able to follow changes in driving habits.
The FitDrive system will also allow roadside patrol officers to interrogate the vehicle wirelessly and thus to focus on those vehicles that have shown recent “unusual” behaviour. Roadside inspections for commercial vehicles, and in particular heavy vehicles, involve an appropriate amount of space and a relatively long time, which can be considerably reduced thanks to the system that the FitDrive project is developing, making inspections more efficient (because vehicles with potential problems are detected immediately) and reducing the time that vehicles remain stationary (those without potential problems undergo a much faster inspection). A further reduction of the controls' time will be achieved through a new and faster drugs screening method.
The FitDrive outcomes can also contribute to face one of the barriers to the deployment of SAE3 level autonomous vehicles. in fact, in SAE 3 level the driver can avoid driving but should be ready to take control if requested by the system; since the FitDrive system continuously checks the driver's psychophysical capabilities, it can also check the readiness of the driver to respond to such kind of request when SAE3 is activated.
The FitDrive project was conceived to identify and prevent driving stress states for professional drivers (and consequently driving fitness) with artificial intelligence and machine learning techniques able to build a “usual" driving profile of each driver after some thousands of kms driven. Once the "usual" driving profile of a specific driver has been defined, the AI system is able to detect “unusual” behaviour (outside the "usual" range of parameters) and associate them with the most probable causes, such as fatigue, or other cognitive disorders. The behavioural function consists of a set of indicators representing the range of usual driving behaviour for each specific driver, which will be defined by the self-learning system during a period of ordinary driving. Deviations are determined by the comparison between daily driving results and the personal “usual” profile.
The FitDrive system will provide a continuous screening of the driver's psychophysical capabilities, alerting him or her to potential impairment on the way: in fact, the abnormal variations detected by the Artificial Intelligence can be associated with early situations of sickness that are not yet apparent to the subject but are about to manifest. The system will continuously learn and adapt itself to the driver: this means that the more a subject drives, the more the system profiles him/her and the more is able to make precise detection of anomalies, and the system will also be able to follow changes in driving habits.
The FitDrive system will also allow roadside patrol officers to interrogate the vehicle wirelessly and thus to focus on those vehicles that have shown recent “unusual” behaviour. Roadside inspections for commercial vehicles, and in particular heavy vehicles, involve an appropriate amount of space and a relatively long time, which can be considerably reduced thanks to the system that the FitDrive project is developing, making inspections more efficient (because vehicles with potential problems are detected immediately) and reducing the time that vehicles remain stationary (those without potential problems undergo a much faster inspection). A further reduction of the controls' time will be achieved through a new and faster drugs screening method.
The FitDrive outcomes can also contribute to face one of the barriers to the deployment of SAE3 level autonomous vehicles. in fact, in SAE 3 level the driver can avoid driving but should be ready to take control if requested by the system; since the FitDrive system continuously checks the driver's psychophysical capabilities, it can also check the readiness of the driver to respond to such kind of request when SAE3 is activated.
The FitDrive system was designed in two versions. The first version has an extended set of sensors and has been used in simulator and test track pilots to measure the onset of fatigue. Analyses including multimodal machine learning determined a series of relevant biophysical and vehicular parameters for detecting the onset of fatigue. Through a literature study the relevant parameters for methamphetamine and cannabis use and for Parkinson and early Alzheimer.
The second version of the FitDrive system has a smaller set of sensors that are all non-invasive and easy to wear for a driver, and will be used in pilots to determine the “usual” driving behaviour; and subsequently tests will be done to detect and classify unusual behaviour. The protocol for these pilots is already nearly finalised.
A first prototype of the handheld drug screening device for methamphetamine and THC is nearly finalised, as well as the technical implementation of connection to police roadside controls. Both will be tested in the last pilot cycle.
The project has adopted an Open Research approach, providing all results publicly to maximise impact and the uptake by the automotive and transport industry and by public administrations and stakeholder associations. In line with this, FitDrive has been presented at numerous events for different audiences (European Parliament, TRA2022, RTR2024 among others).
The second version of the FitDrive system has a smaller set of sensors that are all non-invasive and easy to wear for a driver, and will be used in pilots to determine the “usual” driving behaviour; and subsequently tests will be done to detect and classify unusual behaviour. The protocol for these pilots is already nearly finalised.
A first prototype of the handheld drug screening device for methamphetamine and THC is nearly finalised, as well as the technical implementation of connection to police roadside controls. Both will be tested in the last pilot cycle.
The project has adopted an Open Research approach, providing all results publicly to maximise impact and the uptake by the automotive and transport industry and by public administrations and stakeholder associations. In line with this, FitDrive has been presented at numerous events for different audiences (European Parliament, TRA2022, RTR2024 among others).
The simulator and test track pilots successfully induced fatigue, and EEG has proven to be a very adequate instrument to measure the (onset of) fatigue, serving as a gold standard.
The multimodal machine learning in combination with the fatigue measurements successfully detects unusual behaviour and can most probably classify it as impairment by fatigue onset, drug use or disease.
The drug screening device already meets the goal of delivering results in less than two minutes.
In two meetings at the European Parliament organised by the project about the new Driver Licence Directive, the need for a standardisation of levels of fitness to drive was taken seriously. The new directive will most probably include recommendations on fitness to drive.
The multimodal machine learning in combination with the fatigue measurements successfully detects unusual behaviour and can most probably classify it as impairment by fatigue onset, drug use or disease.
The drug screening device already meets the goal of delivering results in less than two minutes.
In two meetings at the European Parliament organised by the project about the new Driver Licence Directive, the need for a standardisation of levels of fitness to drive was taken seriously. The new directive will most probably include recommendations on fitness to drive.