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Why You Should Trust Self-Driving Cars

Living in 2020, self-driving cars are admittedly difficult to trust. The same way humans were wary of hot air balloons in 1783, the steam locomotive in 1801, and the automobile itself in 1886 (which reassuringly crashed into a wall during Karl Benz’s first public demonstration). This skepticism is nothing new, and is inseparably bound with the notion of innovation - especially in transportation. The hesitant disbelief undoubtedly felt by the ancient people gazing upon the first canoes more than likely parallels that of the onlookers to the first commercial flight in 1914. We often judge through the omniscient lens of hindsight, mindlessly blaming our ancestors for their inability to see the future, and scoff at their ignorance. Entering new domains of transportation is inherently intimidating, and autonomous vehicles are no exception. While the idea of humans relinquishing total control of the vehicle appears alien and alarming, close inspection into the subject reveals a bright future characterized by safety and efficiency. 


To put it frankly, humans are dreadful drivers. According to the Association for Safe International Road Travel, every year, more 1.3 million people around the world die in road crashes; 400,000 of which are under 25 years old, making road traffic injuries the leading cause of death for young people. That toll goes beyond human life, however, costing an astonishing $518 billion annually. Fortunately, those experts estimate 81% of all those accidents could be avoided by removing what is inarguably the faultiest part of the car: the driver. While one might conclude that people would be passionately interested in such a solution, cruel irony dictates that one of the fundamental concerns surrounding this technology is in fact the most significant improvement self-driving cars will bring with them: safety. It’s no secret that we fear that which we do not understand, and very few people are truly and properly familiar with the mechanisms of an autonomous vehicle. Operating a vehicle is a complex task; one must recognize intricacies like construction, bikers, weather, and bad drivers. Admittedly, it is difficult to imagine any algorithm capable of instantly processing these factors and acting accordingly to the extent that human drivers can.


Fortunately for us, then, that this concept has transcended the necessity of imagination; the technology is here, now. Companies like Tesla, Google, BMW, Uber, Mercedes, Volkswagen, Audi, and more have already taken a large interest in the new industry. More than 40 individual companies have applied for self-driving car development permits. Autonomous vehicles are no longer a fringe idea of the future, and the increasingly effective driving algorithms reflect it. In essence, these algorithms operate on the principle that every task, no matter how complex, can be broken down into much smaller tasks with a “yes” or “no” response. When the car identifies a pedestrian about to cross the street, it can either say “yes, they are crossing, stop the car,” “no, they are not crossing, continue as planned,” or “it is too difficult to decide, slow to take a closer look and ask the question again”. The cars can even easily recognize hand signals from bikers and traffic cops. 


Photo by Deb Dowd on Unsplash

The binary process works great for situations and items we have seen, but more nervousness is generated by those which we have not. As more self-driving cars like Google’s “Waymo” take to the streets, their AI is able to learn from more and more real-life situations. The algorithms have gone through countless hours of simulation testing to beef them up, and Google’s Waymo fleet has driven more than 20 million miles in the real world with nearly all of the very few accidents being minor and, notably, not the fault of the car. All pedestrians, cyclists, police officers, construction workers, animals, and more could be aggregated and generate not only a clearer, more versatile imagine of what one looks like, but also a model of how they are expected to move throughout the world. The algorithms were even able to come across an elderly lady chasing ducks around in a circle in the middle of the road, recognize the situation, and slow down and drive safely accordingly. This innovation is all happening now, but the real change happens when autonomous vehicles begin to dominate. Enabling cars to communicate with each other and share information is absolutely game changing, and will transform the way cars are able to avoid accidents.


Inter-vehicle communication will not only astronomically increase safety, but efficiency as well. Wrapping one’s mind around the dystopia of a world filled with infrastructure designed for self-driving cars is near impossible. Traffic is perhaps the second largest hurdle that comes with contemporary driving, having spent the last few decades increasing dramatically. While experts predict that only a few self-driving cars on the road could significantly reduce congestion, things will change most significantly with the addition of inter-vehicle communication abilities. The first system likely to be tossed would be the traffic light. Traffic signals are, all things considered, simply a means of communication between drivers; green and red conveying "go" and "stop" respectively. However, when cars can communicate with each other at the speed of light, traffic lights are rendered useless. Simulations of these hyper-efficient intersections are marvelous (and mildly addicting) to watch, cars taking left turns seamlessly into oncoming traffic without interrupting the startling fluidity of the non-traffic. Parking lots, public transportation, lanes, and every other part of current infrastructure would, in all likelihood, also be comprehensively reimagined. Just look at how Elon Musk is revolutionizing city transport by applying Tesla's autonomous driving capabilities in the Boring Company.


Photo by Eduardo Arcos on Unsplash

Though there remains a handful of satellite fears orbiting the concept of autonomous vehicles, these can be effortlessly jettisoned simply by diving in a little deeper. Those who are wary of the amount of consumer education the novel cars would mandate are perhaps overlooking the reality that, throughout history, virtually every innovation has faced this same hurdle. Even a lengthy, expensive implementation process fails to pose an obstacle that time cannot hurdle. Finally, the age-old concern over the clash over job market stability versus innovation finds itself needlessly present in the self-driving car debate, where jobs created directly by the industry (mechanics, instructors, innovators, and data analysists to name a few) combined with the countless peripheral jobs to become available will overwhelmingly outweigh those lost. Some experts even estimate a global economic boost of 7 trillion dollars from the implementation of autonomous vehicles.


Self-driving cars face an all-too-familiar culture of apprehension as the next step in transportation innovation. Their alien-like independence appears more sci-fi than current technology, and this invites concern, hesitation, and disbelief. This inherent nervousness dissuades potential consumers from taking the first step in trusting the vehicles, it only serves to distract from the safe, efficient future self-driving cars would provide. 

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