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Do you work in the car industry? The world is changing (but you knew that). Here is an article from The Wall Street Journal about what to expect from a historical perspective.
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Autonomous vehicles may well be the quintessential symbol of the AI age. Cars are a major part of our daily lives. A self-driven car is a concept that requires little explanation, something we can all grasp.
It wasn’t that long ago that the notion of an autonomous vehicle driving us around while we read or sleep would have felt like the stuff of science fiction. Having such experimental vehicles coursing through public roads in Silicon Valley, Pittsburgh and Phoenix is concrete evidence that our smart machines are achieving human-like intelligence, raising a number of important questions: How long before autonomous vehicles are all around us? How will they impact our lives? What unintended consequences might we have to deal with? What should be done to ensure that they arrive as safely and smoothly as possible?
The March 1 issue of The Economist discusses these and other important areas, starting with the assumption that we will overcome whatever technological hurdles may impede us now. But there are wider economic, social and public policy issues to be explored. What can we learn from the transition to horseless carriages in the 20th century that can be applied to the transition to driverless cars?
At the turn of the 20th century, big cities were grappling with the growing volumes of horse manure and the diseases spreading from thousands of dead horses. By comparison, cars seemed clean and hygienic, and promised to provide safe and fast transportation — key reasons why they were so quickly embraced.
Cars granted enormous personal freedom and changed the world in unforeseen ways. But there were heavy societal costs. Just like cars were first viewed as a fix for the problems caused by horses, people are now looking to autonomous vehicles to help address problems brought about by cars, especially accidents, pollution, and congestion.
Accidents. The National Highway Traffic Safety Administration estimates that 37,461 lives were lost on U.S. roads in 2016, an increase of 5.6% from 2015. More than 2.4 million people were injured in 2015. Ninety-four percent of serious crashes can be linked to human choices and errors. The Economist notes that about 1.25 million people die, and another 20 million to 50 million are injured, in road accidents around the world each year. It’s the leading cause of death among young people aged 15 to 29.
Autonomous vehicles promise to reduce these numbers drastically. Even at this early stage, there’s evidence that these vehicles are considerably safer than human-driven cars. Moreover, safety is the highest design priority for autonomous vehicles because to succeed they will have to be almost infallible. While people tolerate deaths caused by human drivers, they’re much less likely to do so when no humans are driving.
Pollution. Electric cars are much cheaper to run than gasoline-powered versions, so most autonomous vehicles will almost certainly be electric, especially those used as robotaxis, a market that will demand low operating and maintenance costs. This should help reduce harmful emissions, particularly in high-density urban areas. In addition, electric vehicles are quiet, helping to reduce noise pollution.
Congestion. It’s less clear how autonomous vehicles will help reduce congestion. Computer-controlled vehicles should be able to optimize routing to ease congestion. Over time, they should be able to travel more closely together than human-driven cars can, thus increasing road capacity.
In just a few short years, autonomous vehicle technologies have advanced from the phase of “not sure it can be done” to “it’s just a matter of time.” Alphabet Inc.’s Google, Uber Technologies Inc. and just about all auto companies are developing autonomous vehicles. But, there’s still a ways to go before the technology is ready for mass deployment.
“A fully autonomous car must solve three separate tasks: perception (figuring out what is going on in the world), prediction (determining what will happen next) and driving policy (taking the appropriate action),” explains The Economist.
Perception. Autonomous vehicles use a combination of technologies to perceive the world. These include cameras, radar and lidar — a method that creates a high-resolution 3-D map by using pulsed laser light, measuring the reflected pulses with sensors. These technologies have strengths and weaknesses that complement each other. Cameras are cheap, for example, but cannot measure distance. Lidar provides fine detail, including distance, but is expensive.
Prediction. To predict how the objects around it will behave, an autonomous vehicle must first identify those objects — such as other vehicles, pedestrians, cyclists, road signs and so on. The hardest things to identify are unanticipated objects such as debris, roadwork, broken-down vehicles, and accidents. Rain, snow and puddles can also confuse an autonomous vehicle. Once objects are identified, the vehicle has to predict how they will behave in the next few seconds and then determine what actions to take.
Driving actions. Autonomous vehicles are at a considerable disadvantage compared to human drivers, who are used to dealing with exceptions to the normal flow of traffic. In the near future — even as technologies continue to advance — it’s quite likely that the vehicles will need to ask for human assistance every so often. Humans providing assistance will likely be in central control rooms with access to all the data the vehicle is receiving. They will be able to direct the vehicle or even to take control and guide it remotely, to get around problems.
Advances in machine learning will be a great help, especially as autonomous vehicles can learn from each other’s data and experiences. Over time, there will likely be road lanes and entire areas dedicated to the vehicles, which will coordinate their actions.
The Economist predicts that self-driving vehicles will be initially deployed by fleet operators, not by individual owners, for two main reasons. First are the high costs of technology and a required support structure. These costs can be amortized over a fleet of vehicles in use almost all the time but don’t make financial sense for an individual likely to use the vehicle just 5% of the time. In addition, local governments may limit the use of autonomous vehicles, at least initially, to dense city centers and other specific areas where they would be used widely. That’s fine for a robotaxi but not for a private car.
Autonomous vehicles will have a profound impact on the auto industry. Car markers will have to reinvent their business models, perhaps to sell rides, not cars, The Economist says. Such a shift could open new opportunities. Whereas the car market is worth about $2 trillion a year, the market for personal transport is significantly bigger, perhaps as much as $10 trillion a year. That’s why it’s attracting a number of new competitors, including big technology companies.
People who drive taxis, delivery vehicles and trucks are threatened by self-driving vehicles. But it’s quite possible that their jobs will be redefined rather than eliminated. Truck drivers, for example, could oversee platoons of vehicles traveling on highways, The Economist speculates.
Regulating complex, high-impact and rapidly evolving technologies is hard. Policymakers should work closely with autonomous vehicle firms to develop new safety standards, issue guidelines, and permit limited testing on public roads. But they should wait for evidence that the vehicles are safe before approving widespread deployment.
“A century ago cars raised fundamental questions about personal autonomy, freedom of choice and mobility,” writes The Economist. “Driverless cars present an opportunity to forge a new and better trade-off between personal mobility and societal impact. But [autonomous vehicles] will deliver on their promise only if policymakers — like passengers climbing into a robotaxi — are absolutely clear about where they want to end.
By Irving Wladawsky-Berger, Wall Street Journal
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