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As I drove my commute this morning, I was almost in an accident. I had slowed down for some backed-up traffic ahead, and I looked in my rearview window—and saw another car barreling down on mine, seemingly with no intent to stop. At the last minute, the car screeched to a halt, raising tire dust and making my heart rate shoot through the roof. The car stopped just inches from my fender.
Now, I have no idea what was going on in the mind of the woman who was driving. Since we didn’t collide, I didn’t get to talk to her. But I would bet my front left tire that the reason she almost rear-ended me was that she was somehow distracted as she was flying along the highway. Was she on her phone? Was she eating breakfast? Was she putting on makeup, fiddling with her radio, or falling asleep? No telling. All I know is that it was a close call.
I’ve written about the future of transportation before, but this post isn’t about those mythical automobiles of the future. I’m talking about right now, this minute.
There are three main types of distraction:
Texting while driving is especially dangerous because it combines all three types of distraction . That said, distracted driving also includes other activities such as eating, talking to other passengers, or adjusting the radio or climate controls. Age of the driver also seems to play a role in the percentage of distracted driving that occurs, particularly for younger, newer drivers. 
I’m not going to preach here about not texting or putting on mascara while you’re driving; you know that already. And yet, we still do it. Each day in the United States alone, approximately nine people are killed and more than 1,000 injured in crashes that are reported to involve a distracted driver, passenger, pedestrian, or cyclist. 
So, if public safety announcements and gruesome or heart-felt commercials don’t do the trick—and they haven’t—the car manufacturers will attempt to tackle the problem.
Part of the safety features that are now being developed are related to monitoring the health, mental state, and alertness of the driver through in-cabin monitoring of the driver and passengers in the vehicle. This is done using cameras, multi-spectral imaging, gesture tracking, and occlusion detection. These cameras are not facing outward towards the environment, they’re turned towards the driver of the automobile, looking for signs of distraction.
These signs might include:
When the in-cabin sensors detect a probable issue with the driver’s and/or passenger(s) distraction level, an alert notifies the driver to the risk of impending danger. These advances would not be possible without sophisticated sensing and AI technologies.
For this level of intelligence to succeed, a combination of embedded vision and AI processing must be in the sensors that are in the cabins of these cars. These sensors must be able to scan the “cockpit” at some rate that makes sense, “learn” what your resting face looks like, what your driving style may be like, and what your resting—or driving—heartbeat might be. The sensors must be able to orient themselves in the space and recognize different drivers by facial recognition, size detection, even detecting the approximate age of the driver.
This is a lot to ask.
Fortunately, Cadence offers embedded processors that specialize in vision and AI processing. The Tensilica Vision Q6 DSP specializes in vision and AI processing and can be used together with the DNA 100 processor, which is a tightly coupled Tensilica DSP for on-device neural network inference applications such as these.
We do have the technology to make these sensors a reality. Now if I can just make it home tonight without incident…