Synthetic Data Cloud for real-time Driver Monitoring System (DMS) development and validation of Vision AI models
By SKY ENGINE AI 01 September 2022
Driver Monitoring | Generative AI | Automotive | Synthetic Data | Deep Learning
Driver monitoring systems (DMS) based on the AI and Computer Vision (CV) are quickly becoming standard on board of vehicles of any type and model. The safety standards push the sensitivity and alerting adequacy to play critical role when assessing the DMS’s applicability to broad adoption. The drivers do not need to face additional distraction coming from misleading alerts as their attention should be laser focused on the driving task. Although there are several apprentice DMS systems on the market yet, the gap still exists but the good news is that it can be filled by the deep learning in virtual reality with Synthetic Data where the AI models are tested and trained prior to the real-world deployment leading to improved adherence to the regulations, better interoperability with ADAS systems, and most importantly thousands of fatalities can be prevented.
Synthetic Data Cloud for real-time in-cabin monitoring system development and validation of vision AI models
The Driver Monitoring System (DMS) will become a standard safety component throughout the world as early as 2023. In the United States the Department of Transportation will compel to begin developing guidelines and rules to combat distracted and intoxicated driving, as well as to modernize the New Car Assessment Program (NCAP). Initially, European regulations will apply to distracted and sleepy driving. Eventually, Europe will need impairment detection systems to cover alcohol and drugs.
There is always time to consider improvements in safety through this technology. According to the National Highway Traffic Safety Administration, distracted driving was responsible for over 3,000 deaths in 2019, a 10% increase over 2018. Drunk driving has also grown. In 2019, 10,142 people were killed in drunk driving accidents. Early projections for 2020 show a 9% rise in DUI fatalities. Many people anticipated road deaths to decrease during the epidemic, but the reverse happened.
To further boost the reliability up to higher Safety Levels it is critical to develop scalable, complementary and interconnected AI models with high adequacy. This can be mostly ensured by training sensors in a virtual environment prior to the real-world deployment. The SKY ENGINE AI platform enables Data Scientist friendly development of such AI models using platform’s deep learning in virtual reality technology for computer vision applications. Driver monitoring systems usually employ RGB or infrared (IR) cameras and computer vision software to guarantee that the driver is awake and aware, and is paying attention to the road. The system may be configured to do a sequence of consecutive actions, beginning with a mild alert or warning and advancing to slowing or halting the vehicle if the driver is no longer able to control it.
Key benefits of the DMS/OMS for manufacturers, fleet owners, insurers, drivers and occupants
The key benefits of using the driver and occupants monitoring system include:
- Increased safety of the driver, passengers and others on the road by activities, emotions, attentivness and drowsiness detection
- Alerting driver before collisions happen — avoid collisions than report on after the fact
- Compliance to General Safety Regulations (GSR)
- Improved comfort and experience by driver and occupants identification for settings personalization with i.e. facial recognition
- Supports autonomous driving L3+
- EuroNCAP 4–5 star rating relevance
- Helps drivers improve their skills — especially important for newer drivers
- Track and confirm drivers following the regulations and procedures in fleet safety policy
- Highly decrease operational costs, reduce insurance claims and expenditure, reduce collisions
- Cost-efficient system based on scalable, modular approach and seamless integration with exisiting systems (ADAS)
- High flexibility of adaptation to the universe of models, markets, and vehicle interiors
- Driver’s position, weight and pose monitoring (3D skeleton) to facilitate optimization of the safety systems
SKY ENGINE AI approach to the in-cabin monitoring system development
For the human driver, the scene is too complex, reactions too slow and timeframe too short to provide quick and adequate reactions in any conditions. The combination of the DMS with Advanced Driver-Assistance Systems (ADAS) can use predictive analytics to further boost crash-prevention capabilities. ADAS incorporates technology like as automated emergency braking, blind-spot recognition, and lane departure alerts and its capabilities may be further enhanced when integrated with the DMS. For instance, after detecting drowsiness or high distraction level the DMS can send signal to the ADAS to increase the distance to preceding vehicle first before stopping the car completely.
Such DMS can be developed at a fraction of cost of real data acquisition and labelling providing complete solution for driver monitoring and in-cabin sensing. Also, it is viable to employ low-cost cameras in the car as synthetic data and complex vision AI algorithms can be created in the SKY ENGINE AI platform to allow reliable driver monitoring.
The computer vision AI models for the Driver Monitoring System (DMS) that can be developed and effortlessly retrained (when necessary) in the SKY ENGINE AI Synthetic Data Cloud:
- Identification of the driver in order to allow the vehicle to automatically restore its preferences and settings
- Monitor driver fatigue to alert him when potential drowsiness situation is detected
- Monitor driver attentiveness by ensuring he’s keeping his eyes on the road, hand on the wheel and that he/she is aware of any dangerous situation
- Recognize and track any additional objects and elements floating inside the car
- Monitor actions and activities of children, babies, toddlers in a child seat
- Detect and monitor activities/actions by pets
- Pilot a user interface using gestures or gaze by automatically selecting HMI areas, highlight important features on the road, etc.
In addition, training the AI models for the DMS in the SKY ENGINE AI platform preserves the privacy as these models are trained in virtual reality with synthetic data: humans, cars, objects, etc. Virtual vehicle interiors serve the purpose of training, testing and validation of the AI models before deployment in a real car saving hundreds of hours and highly reducing the overall cost of such DMS.
