Less than a decade ago, the thought of a self-driving vehicle was still a far-off possibility in the minds of most Americans, but in just a few short years several vehicle manufacturers, software engineers, and experts in artificial intelligence (AI) have come together to create autonomous vehicles. Companies like Tesla and Google are spearheading the autonomous vehicle boom, and now self-driving cars are appearing all over the country. Ride-sharing services like Uber and Lyft have also invested heavily in autonomous vehicle technology, potentially offering customers all over the country rides from robotic drivers.
Autonomous vehicles hold tremendous potential to create very positive changes on American roads, including eventually removing human error from the list of causes of traffic accidents. The National Highway Traffic Safety Administration (NHTSA) reported over 37,000 traffic fatalities in 2016 alone*, and the vast majority of those fatal accidents were due to human error. Autonomous vehicles not only offer convenience, but they could easily become safer than human-driven cars.
What Are Autonomous Vehicles?
An autonomous vehicle or self-driving vehicle is something of a misnomer. Currently, self-driving vehicles still require a human operator to take control in certain situations or in the event of an emergency. There are no fully autonomous vehicles yet, but semi-autonomous driving has advanced tremendously in a very short time.
Autonomous vehicles use a variety of technological advances to ensure proper vehicle operation, navigation, and safety. A self-driving car includes various cameras, sensors, and software programs that essentially create a three-dimensional navigational readout for the car to safely navigate and manage changing traffic conditions. Previous years have seen the inclusion of driver-assistance technologies like parking assist, lane-drift warnings, and proximity sensors to help avoid crashes. Current semi-autonomous vehicles take these vehicles a step further, and many analysts and industry leaders expect fully autonomous vehicles to arrive in the very near future.
Who Makes Self-Driving Vehicles?
Tesla currently leads the field when it comes to autonomous vehicle development with its patented Autopilot feature enabling nearly full autonomous driving. Google has developed a bubble-top autonomous vehicle and plans to work with automaker Fiat to develop a fleet of self-driving cars, but they don’t currently have any plans to release autonomous vehicles to the consumer market. Other vehicle manufacturers like GM, Ford, Nissan, and Volkswagen have all committed to developing self-driving vehicles in the next few years.
Autonomous Vehicles And The Ride-Share Boom
Companies like Uber and Lyft have also embraced the autonomous vehicle trend, investing in hundreds of autonomous vehicles for use in cities all over the country. This trend has cast some doubt on the autonomous vehicle boom, particularly due to the incident involving an Uber autonomous vehicle hitting and killing a bicyclist in Tempe, Arizona after the vehicle’s sensors and the safety driver failed to notice the woman**. Despite this unfortunate development and a few other notable accidents involving self-driving cars, the trend continues to gain traction and self-driving cars are no longer an eventuality, they are an inevitability.
What To Look For In 2019
Two of the most important technological advances responsible for the boom in autonomous driving technology include sensor technology and machine learning. Industry analysts and investors expect to see tremendous new developments in these areas***. Sensor technology empowers self-driving vehicles to more quickly and accurately assess and respond to changing traffic conditions and navigate more safely.
Perhaps the most important and valuable piece of technology involved with self-driving vehicles is machine learning, the ability to instantly develop new processes and adjust existing processes with the introduction of new data. Most human drivers learn to drive from other people, usually parents or older siblings. Regardless of how they learn to drive, a driver can only absorb so much knowledge through instruction; most of a driver’s ability to drive safely comes from experience.
If a new driver could instantly absorb the experiences, muscle memories, and driving acumen of other drivers, vehicle accidents would be an extremely rare occurrence. This is unfortunately impossible for humans, but it is easy and instantaneous for self-driving vehicles.
Machine Learning Removes Human Error From The Road
The self-driving vehicles in a fleet use the same software. When developers make a change, the change applies instantly to every vehicle in the fleet. This essentially enables every self-driving vehicle to learn from the experiences of other vehicles in the fleet in mere seconds. Software developers and machine learning programmers can only account for so many eventualities on the road, but some traffic hazards happen unpredictably or do not fall in line with existing safety procedures. In the future, self-driving vehicles can instantly absorb the experiences of other vehicles that share their programming.
Common Concerns With Self-Driving Vehicles
The American public remains divided on the topic of self-driving cars. Some wonder about liability issues and insurance requirements; if a self-driving vehicle causes an accident, does liability fall to the driver, the manufacturer, or a combination of both? Others fear for their safety in light of news like the incident in Arizona where a self-driving vehicle completely failed to stop or even apply the brakes before fatally striking a pedestrian. However, new advances and the ability to instantly absorb the experiences of other vehicles sharing the same programming means that autonomous vehicles could potentially remove human error as a common cause of accidents on U.S. roads entirely.