Driving is evolving from a task to an experience. Once a series of human-conducted mechanical procedures, the Internet of Things (IoT) has shifted our thinking to expect technology to enhance the driving process and enrich the overall user experience. Until driving is fully autonomous, occupant monitoring (also termed in-cabin sensing) can signal the vehicle to start a process to react to a passenger's or driver's condition. These processes are termed advanced driver-assistance systems (ADAS) and were the first vehicle-sensing applications.

Early ADAS employed sensors to assess the condition of the environment surrounding the vehicle, such as forward collision warning (1995), automatic emergency braking (2003), and blind-spot alert. Adaptive cruise came next, which expanded development toward other non-safety-related automotive sensor market drivers; emissions legislation, vehicle performance, and in-cabin comfort.

Once the focus included in-cab conditions, manufacturers next targeted child-presence detection for in-cab safety. Accuracy is critical to the performance of this feature, where small children are especially hard to detect. Historical technology like digital cameras and weight sensors have limitations, especially for rear-facing car seats and children's lighter weights. The spectrum of use cases for occupant monitoring requires a multi-technology approach. 

Occupant monitoring systems (OMS) focus mainly on child detection, while driver monitoring systems (DMS) prioritize driver safety and performance during vehicle operation. The focus of each of these techniques enables innovation to improve their performance and enhance their benefits.

OMS

Looking first at OMS, these approaches provide significant benefits that enhance safety, comfort, or convenience during the driving experience.

Child-presence detection (CPD)

Historical CPD systems used pressure, temperature, infrared, weight, or ultrasonic sensors, leveraging external sensing technology. Due to the limitations of those approaches to the various child-in-car scenarios (like under a blanket, rear-facing car seat), radar and Wi-fi emerged to improve detection capability. Radar scans the cabin with low-power radio signals (similar to how autonomous vehicles define their environment). At the same time, Wi-fi uses existing networks to detect subtle motion (like breathing under a blanket).

Both are inconspicuous and continuously map the cabin for changes in activity vs. taking a picture or detecting a measurable difference in condition. In addition, rapidly scanning and identifying the child addresses the time sensitivity of the application.

Passenger airbag deployment

Airbag deployment is an even more time-sensitive OMS. Legacy technology employed a sodium azide (NaN₃) reaction, during which the crash trips a sensor that activates an ignitor. NaN₃ is highly exothermic due to the stability of its products, diatomic nitrogen and sodium metal. A drawback to using this reaction is that these airbag systems sacrifice accuracy for speed. Current systems employ additional OMS sensors around the cabin to provide adaptive response even faster than before. Engineers can tailor the airbag's fill level for optimal performance and passenger safety with more sensors. The system accomplishes this improvement by creating a map of occupant position to inform the airbag deployment system where passengers are in the event of a crash.

Personalization by passenger

The above safety features can also enhance the driving experience, another objective of OMS. For example, sensors and imaging technology can detect a specific occupant and initiate a specified set of conditions for that passenger. Seat position and angle, mirror angles, ergonomic adjustments, lighting, or infotainment settings are some features this customized experience provides. In addition, system designers can integrate sensors with in-cabin cameras to customize the experience.

Climate/ventilation control

A unique application extension for OMS is passenger climate control. Added sensors can automate air conditioning or heating system initiation to begin temperature control earlier. In addition, groundbreaking innovations like local heating or cooling pair measurements of cabin surface temperature with occupant metabolic rate, measured at pressure points. An algorithm consumes this data and adjusts the local climate to minimize the passenger's metabolic rate, signifying a more comfortable condition. Finally, the system can learn riders' preferences with usage, creating a microclimate to reduce the time to optimize comfort that rapidly converges for specific occupants.

DMS

There are slight differences between driver monitoring and occupant (or passenger). Much of the driver monitoring resulted from drowsiness and general inattention to operating the vehicle, while occupant monitoring evolved from child presence detection. Implementing biometrics, sensors and smart technology to detect the driver's presence, position, and attentiveness increases safety while avoiding many human errors that can lead to crashes.

Biometrics and iris-scan facial detection

Iris scanning is gaining popularity at airports and elsewhere to enhance security, adding speed and accuracy to the two-step verification approach or facial profile recognition present in many current applications. The same technology can confirm the driver's identity (protecting security) and signal the car to unlock the doors or turn on the engine due to the iris's unique pattern.

When paired with artificial intelligence (AI) and a smart windshield, iris scanning can assess the driver's sight patterns, level of drowsiness, and whether the critical dashboard data is in their line of sight. This benefit is a powerful tool to combat distracted driving.

The scanners work by illuminating the iris with infrared light. These rays detect unique patterns not visible with traditional cameras. Having a unique signature makes the iris a strong candidate to improve the accuracy of facial detection and deliver more rapid and less time-consuming security checks.

Driver position in cabin and seat belt engagement

Some of the technology present in OMS applies to DMS as well. For example, radar or Wifi child presence detection can improve driver position monitoring in the cabin better than traditional cameras. Furthermore, the adaptive sensors used for airbag deployment can also confirm seat belt engagement. According to the CDC, vehicular seat belts reduce the risk of serious injury from a car crash by 50%. As defined by crash simulations with an engaged seat belt, ensuring the driver is in the proper position improves driver safety and is a primary outcome of effective DMS.

OMS and DMS are inherently different. As mentioned above, DMS focuses on precision to detect adverse changes in driver behavior, while OMS has prioritized child safety. As a result, OMS has not required the level of accuracy needed by DMS to date.

Leveraging connected driving, AI, and innovative sensor technology, OMS components could inform DMS to help machine learning algorithms record the same event from a different angle. For example, a driver may move their head from side to side to check for wildlife running across the road. DMS alone may trigger an alarm, but the OMS imaging may capture the behavior more holistically as they look across the field of view. Integrating OMS and DMS enables vehicular autonomy.

With the increase in vehicle autonomy, there will be a decreased need for the driver to be fully attentive to the road and a stronger demand for increased convenience features. In addition, autonomous vehicles will enable the integration of OMS and DMS to assure safety and enhance the driver's capability.

With automotive's digital transformation, occupant monitoring has advanced through improved child detection, local microclimate control, enhanced biometric identification, and expanded customization. However, improving safety remains the primary objective for new applications of OMS. Thankfully, many of the OMS and DMS improvements offer the combined benefits of improved occupant safety and enhanced travel experiences.