How Autonomous Cars and Big Data Will Help First Responders

June 3, 2017 Tasking

cooperation between air and ground medical services

It’s a bit strange what things people are afraid of. After watching Shark Week each year I become more and more afraid of sharks, even though I’ve never seen one at the beach. In fact, it’s much more likely that I’d be injured in a car wreck, though I don’t feel any fear each time I get behind the wheel. Whether or not I’m afraid, the risk is still there, though new advances in technology are minimizing that risk.  Advanced driver assistance systems (ADAS) in cars have already reduced the number of wrecks in the US. ADAS may even be able to reduce accidents by 90%, but will never be able to fully eliminate them. If you can’t eliminate a problem, you can at least mitigate the consequences. That’s where first responders come in. Emergency personnel can save lives in the crashes we can’t prevent, and ADAS data can help them do it. Data shared with first responders will cut down response times by providing location information. It will also provide information about crashes and passengers that could save lives.

Great white shark
We can avoid the ocean, but it’s hard to avoid getting on the road.

Big Data and ADAS

Movies like “Jaws” have given sharks a bad rap when really they’re not as dangerous as things like vending machines. “Big Data” usually has a negative connotation as well, one it doesn’t deserve, in this case.

ADAS enabled cars produce a lot of data. That amount will only continue to grow as vehicles incorporate more sensors in their quest for full autonomy. Intel estimates that cars will eventually need to process 1 GB of data per second in order to drive themselves. That information will include things like LIDAR array point clouds, distance information from ultrasonic sensors, and motion information from accelerometers. This is the kind of “Big Data” I’m talking about when it comes to autonomous vehicle safety.

Most cars are processing this kind of information on board, but they are not currently sharing it. However, with machine learning sucking up processing power, car manufacturers may decide to use the cloud to help process data. The same links that send data for processing could also be used to share data with first responders. That would give emergency personnel more to work with if you’re in a crash.

car crash
AACNs will let first responders know if you were in a wreck or just a fender bender. Editorial credit: Happy cake Happy cafe /

Where Are You?

One of my greatest fears is crashing my car in the middle of nowhere where no one can find me. ADAS cars can make sure this never happens by sharing location data with emergency services.

Currently, the vast majority of car wrecks are reported by eyewitnesses or crash victims themselves. These people then have to describe where they are, a difficult task in a traumatic situation. An advanced automatic collision notification (AACN) system can automatically send the location of a crashed car to the police and get help more quickly.

Even if someone calls 911 and accurately describes the location of the wreck, time has already been lost when calling. Vehicles equipped with AACN systems notify authorities within 2 minutes, while normal methods can take more than 5 minutes. Saving seconds can save lives, and an AACN will do just that. Some groups estimate that an AACN with accurate location data could reduce response times by 30-50%. That could mean the difference between life and death.

cooperation between air and ground medical services
AACNs will let emergency services know if they need to send an ambulance or a helicopter.

Damage Control

First responders not only need to know where you are, they also need to know what condition you are in.

In the past AACN systems usually just sent things like speed and which seatbelts were engaged. Even this little bit of data was helpful, allowing an algorithm to predict which occupants in the car had severe injuries. Then medical staff could prioritize those with the most serious conditions. More data can only make predictions more accurate. Instead of just analyzing speed data, algorithms could incorporate accelerometer data to see how many impacts a car experienced and whether it flipped. Ultrasonic data around the car could tell which direction the car was hit from. This kind of data could very accurately predict who in the car needs the most help.

Currently, data is routed through a call center, which processes it and forwards it on to emergency services. However, as more and more cars are equipped with standard communication systems, information could be sent directly to first responders. Again that will further decrease response and reaction times. By the time an ambulance arrives on the scene, EMTs will already know who they need to get to a hospital.

The Jaws theme song might give us goosebumps, but an engine turning over doesn’t scare us. We should be a bit afraid, though, of the dangers of the open road. Increasingly complex ADAS systems will greatly reduce wrecks, but there will always be some crashes. AACN systems will help save lives in the accidents we can’t stop. AACNs will lead to faster response times for emergency vehicles, and will also give them a good idea of who needs the most help. Someday the threat of a fatal car crash will be as low as that of a shark attack.

Now that you know how helpful accurate AACNs can be, it’s time for you to start making them. Just like data can assist first responders, we have something that can help you. TASKING has developed a wide range of products to build the future of ADAS.

Have more questions about AACNs? Call an expert at TASKING.

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