Stress While Driving Sensor Network and AI Algorithms Help Manage Traffic Congestion

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The cognitive load while driving a car can be monitored using sensors and AI algorithms. Once the stress level reaches its limit, the technology is set to assist people in the future. Pilots or surgeons in operating rooms could also benefit.

When driving, we should focus on traffic. But in everyday life, the reality is often different. Studies show that cognitive distraction is one of the invisible but common causes of accidents. 40% of drivers admit to using their phones to make calls or read messages while driving, which increases cognitive load and raises the risk of accidents.

Against this backdrop, researchers at the Fraunhofer Institute for Integrated Circuits IIS in Erlangen (Germany) are working on innovative systems to support drivers in road traffic.

For this purpose, they are developing two technologies: A sensor network measures biosignals such as pulse, breathing rate, or movements. AI algorithms detect when a person reaches the limit of their individual cognitive load capacity.

The evaluation of biosignals was developed using studies in which researchers investigated the correlation between biosignals and cognitive load in test subjects.

In practical use, the system can ensure that the vehicle's electronics take over certain tasks from the driver, for example, thereby reducing complexity or simply recommending a break at the next rest area.

Detection of Cognitive Load Through Sensors

The centrally developed system is based on a mobile, multimodal sensor network called 'maphera.' "We have integrated a variety of different sensors into a system that not only works in the lab but is also mobile and therefore applicable in various contexts. Accordingly, 'maphera' is modular in design. Depending on the application or need, we combine a wide range of sensors," explains Norman Pfeiffer, Head of Medical Sensor Systems at Fraunhofer IIS.

The sensor systems can be integrated into textiles or, for example, into wristbands and so-called smart patches. These are small, usually skin-adhesive sensors that continuously monitor biosignals. The data is transmitted via Bluetooth LE (Low Energy).

Technical Challenges and Synchronization

A technical challenge lies in ensuring the temporal synchronization of the sensor data. For long-term measurements, such as those that occur while driving, clock frequency drifts of the microcontrollers must be accounted for. Fraunhofer IIS has managed to process the data with a synchronization tolerance of just 30 µs, which underscores the name Maphèra, derived from Ancient Greek for "simultaneously transmitted."

The second part of the research project focuses on the relationship between biosignals and cognitive load. The test subjects sit in an exposure cabin where they are undisturbed by external influences such as temperature changes, drafts, or noise. Here, they solve tasks of increasing difficulty. Participants are also allowed to play computer games for this purpose.

As a chef or kitchen staff member in the sushi restaurant, they take orders and prepare a sushi dish. Over time, the number of orders and the complexity of the dishes increase. Meanwhile, sensors record the body's biosignals. The collected data is combined with the so-called n-back test, a standard psychological test that assesses cognitive abilities such as attention and memory. Following the tests, individual interviews with the test subjects are conducted.

Dr. Nadine Lang-Richter, group leader for Medical Data Analysis at Fraunhofer IIS, says: "In the final step, we compile all the information and analyze it using AI algorithms that we have developed ourselves. This allows us to create an individual cognitive load profile of the person."

Practical Applications and Further Developments

The potential applications of this technology extend far beyond the automotive sector. As camera-based driver monitoring systems will be mandatory in new vehicles from 2026 under EU regulations, this offers groundbreaking implementation opportunities. Additionally, pilots could benefit from individualized stress profiles during their training, and surgeons could be supported during lengthy operations. (heh)

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