How Computer Vision Can Change the Automotive Industry
Every year, traffic accidents account for 2.2% of global deaths. That stacks up to roughly 1.3 million a year — 3,287 a day. On top of this, some 20–50 million people are seriously injured in auto-related accidents each year. The root of these accidents? Human error.
From distracted driving to drunk driving to reckless driving to careless driving, one poor or inattentive decision could be the difference between a typical drive and a life-threatening situation. But what if we could neutralize human error from the equation? What if there were a way to monitor bad driving and prevent those actions likely to cause accidents before the accidents themselves occur?
This is where computer vision comes in. With computer vision and intelligent transportation systems (ITS), we can provider drivers with a safety net. These technologies make it possible to mitigate human error in the auto industry, assisting drivers at the wheel with tools and features that keep them from committing serious mistakes and accidents.
In the automotive industry, we’ve seen this technology tested and most immediately applied to common vehicles. However, the technology is also making its way into the realm of autonomous/self-driving vehicles, though this application is still some years off from becoming wholly relevant.
Driver Assistance, Safety Precautions, and Preventive Measures
You know those rear camera some cars use to give you a better look while you’re backing up and going in reverse. Well, computer vision can work like that, except it gives your entire car eyes, not just your bumper.
And it does more than just that. Computer vision acts as a complete sensory apparatus, one that simultaneously takes in the environment around you and analyzes it for potential threats, obstacles, and other relevant situations that you’d need to react to while driving.
Take lane changing, merging, and unintentional lane departure, for instance. Research conducted by the Insurance Institute for Highway Safety (IIHS) estimates that lane departure warning systems (LDW) could potentially avoid or assuage some 37,000 injury-inducing crashes, 7,529 fatal crashes, and 179,000 crashes yearly. If you found yourself swerving or veering off the road while driving, the LDW would pick up on this and issue an alert (either by way of a visual, sound, or vibration). Alternatively, if one of the car’s computer vision cameras sees that another car is merging or veering into your lane unintentionally (without a turn signal, for instance), it would also provide an alert to prevent a potential accident
This technology can also be used to tackle drowsy/distracted driving. The U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA) estimates that more than 3,000 automobile-related fatalities result from driver distractions, while 100,000 crashes, 40,000 injuries, and 1,500 deaths happen each year by way of driver drowsiness. With computer vision technology, your car can help you stay awake and identify when you’re too sleepy or distracted to drive. Measuring a number of features including eye gaze and eye state (e.g., droopy, opened, closed), image recognition and computer vision technologies could pinpoint when you’re not wholly focused on the road in front of you, issuing an alert to get you back on the right course when needed.
Outside of the car, computer vision could help us cut down on pedestrian accidents, as well. Over 39,000 pedestrians die in auto accidents each year, while some 430,000 more are seriously injured. In the same way that computer vision can help us to prevent auto accidents on the road, it can also help us to prevent pedestrian-auto accidents off the road. Computer vision-powered car cameras are being developed to detect pedestrians before drivers may noticing them, giving drivers real-time alerts and responses to prevent potentially deadly accidents.
The Future of Computer Vision and Transportation
These are just a few of the areas in which computer vision can revolutionize the automotive industry, making it safer and more efficient for all.
In the realm of transportation, this technology can also be used to streamline traffic flow. Using computer vision and sensory technologies, we can make modern traffic management processes more efficient. These technologies can also be used in traffic and incident management to make diverting traffic easier than under current practices.
Computer vision in transportation opens up another exciting avenue for Neuromation’s application and development. With our advanced image recognition technology, we have all the tools in place to disrupt the automotive industry and make it safer for the world of tomorrow. Our synthetic datasets could be applied to traffic flow to manage it more efficiently, as well.
Computer vision technologies have the potential to revolutionize our daily lives, making everyday doings like driving and transportation easier and safer for all involved. Neuromation is pioneering computer vision and synthetic data to this end, to give you peace of mind on your morning commute and make your day less of a hassle.
