Tesla
Tesla FSD mastered driver attention monitoring with no wheel nag
Tesla has resolved one of the major issues in Full Self Driving (FSD) technology known widely as wheel nag and almost mastered driver attention monitoring.
FSD is a self-driving tech developed by Tesla and it can drive through different traffic conditions using its intelligent computing. However, FSD needs to be supervised by a human driver to take wheel control when required.
This self-driving system has some safety features including the driver attention monitoring system. This feature warns the user whenever it detects user distraction via wheel torque (pressure).
The torque-based detection also has flaws. Users blame the FSD monitoring on being less responsive and failing to detect wheel grip. It requires customers’ hands on the wheel all of the time and even with that, some users have found this unuseful.
FSD 12.4.1 addresses this problem with Vision-based driver attention monitoring. It uses the cabin camera and an algorithm to detect the driver’s posture and head movement. Although the system still uses wheel torque but prioritizes detection via the cabin’s camera.
How it’s working?
A review published by the Dirty Tesla YouTube channel walkthroughs this new software update. The video shows that the driving intervention has been improved compared to the FSD 12.3. But the demonstration is all about the new driver monitoring system.
Once enabled, the Vision-based driver monitoring goes into action. Hence, the system allows hands-free driving when you follow some rules including:
- Not obstructing the camera view
- Not wearing hat
- Not wearing sunglasses
The system keeps checking these aspects in real-time and warns the user accurately as shown in the video. However, FSD also monitors wheel torque during turns and driving at increased speed.
Tesla Full Self Driving (FSD) showing driver attention system warning (Image Source – Dirty Tesla/YouTube)
The tech still needs improvements as it randomly shows attention warnings even when the driver is paying attention. It might be resolved in a future version. Watch the full video linked below.
