Autonomous Vehicle Quotes

More than 90 percent of these accidents are caused by very human errors: somebody drinking alcohol and driving, somebody texting a message while driving, somebody falling asleep at the wheel, somebody daydreaming instead of paying attention to the road. The National Highway Traffic Safety Administration estimated in 2012 that 31 percent of fatal crashes in the United States involved alcohol abuse, 30 percent involved speeding, and 21 percent involved distracted drivers.7 Self-driving vehicles will never do any of these things. Though they suffer from their own problems and limitations, and though some accidents are inevitable, replacing all human drivers by computers is expected to reduce deaths and injuries on the road by about 90 percent.8 In other words, switching to autonomous vehicles is likely to save the lives of one million people every year.

Human drivers in the United States suffer roughly one fatal accident per one hundred million miles traveled, which sets a high bar. Autonomous vehicles, to be accepted, will need to be much better than that: perhaps one fatal accident per billion miles, or twenty-five thousand years of driving forty hours per week.

In a era of autonomously driven electric cars and vehicles capable of taking us to Mars, our education system is the equivalent of a horse and carriage.

The potential benefits of fully autonomous vehicles are immense. Every year, 1.2 million people die in car accidents worldwide and tens of millions suffer serious injuries.

A reasonable target for autonomous vehicles would be to reduce these numbers by a factor of ten.

Soon, many of us will no longer need to own or drive a car. Instead, we will rely on services that safely and conveniently use autonomous vehicles to take us where we want to go.

In other words, switching to autonomous vehicles is likely to save the lives of one million people every year. It would therefore be madness to block automation in fields such as transport and healthcare just in order to protect human jobs. After all, what we ultimately ought to protect is humans—not jobs. Displaced drivers and doctors will just have to find something else to do.

The letter is only an aid to philosophical communication, the actual essence of which consists in arousing a particular train of thought. Someone speaking thinks and produces—someone listening reflects—and reproduces. Words are a deceptive medium for what is already though—unreliable vehicles of a particular, specific stimulus. The true teacher is a guide. If the pupil genuinely desires truth it requires only a hint to show him how to find what he is seeking. Accordingly the representation of philosophy consists purely of themes—of initial propositions—principles. It exists only for autonomous lovers of truth. The analytical exposition of the theme is only for those who are sluggish or unpracticed. The latter must learn thereby how to fly and keep themselves moving in a particular direction. Attentiveness is a centripetal force. The effective relation between that which is directed and the object of direction begins with the given direction. If we hold fast to this direction we are apodictically certain of reaching the goal that has been set. True collaboration in philosophy then is a common movement toward a beloved world—whereby we relieve each other in the most advanced outpost, a movement that demands the greatest effort against the resisting element within which we are flying.

The “triad”—the convergence of electric vehicles, ride hailing, and self-driving cars—is far from sure. It will take electrics a long time to catch up with gasoline-powered cars as a share of the fleet. People may continue to want to own cars and drive themselves. Autonomous vehicles at scale are far from proved.

More data leads to better AI (artificial intelligence), more automation leads to greater efficiency, more usage leads to reduced cost, and more free time leads to greater productivity. All of these will grow into a mutually reinforcing virtuous circle that will continually and rapidly increase the adoption of AV (autonomous vehicles).

Humanity needs a new transportation system - a new system of moving people and resources. We need greater efficiency with a good bit of joy built in. And Mayflower-Plymouth is providing that.

The new transportation system is multi-modal, autonomous and electric. People utilize a variety of vehicles including cars, bicycles, passenger drones, hoverboards, airplanes, boats, rockets and more. And with ease, efficiency and comfort. At Mayflower-Plymouth, we’re making that real.

According to the New York Times, last year as one of Google’s new cars approached a crosswalk, it did as it was supposed to and came to a complete stop. The pedestrian in front crossed the street safely, at which point the Google car was rammed from behind by a second non-Google automobile. Later, another self-driving Google car found that it wasn’t able to advance through a four-way stop, as its sensors were calibrated to wait for other drivers to make a complete stop, as opposed to inching continuously forward, which most did. Noted the Times, “Researchers in the fledgling field of autonomous vehicles say that one of the biggest challenges facing automated cars is blending them into a world in which humans don’t behave by the book.”15

The age of centralized, command-and-control, extraction-resource-based energy sources (oil, gas, coal and nuclear) will not end because we run out of petroleum, natural gas, coal, or uranium. It will end because these energy sources, the business models they employ, and the products that sustain them will be disrupted by superior technologies, product architectures, and business models. Compelling new technologies such as solar, wind, electric vehicles, and autonomous (self-driving) cars will disrupt and sweep away the energy industry as we know it.

self-driving vehicles could provide people with much better transportation services, and in particular reduce mortality from traffic accidents. Today close to 1.25 million people are killed annually in traffic accidents (twice the number killed by war, crime, and terrorism combined).6 More than 90 percent of these accidents are caused by very human errors: somebody drinking alcohol and driving, somebody texting a message while driving, somebody falling asleep at the wheel, somebody daydreaming instead of paying attention to the road. The National Highway Traffic Safety Administration estimated in 2012 that 31 percent of fatal crashes in the United States involved alcohol abuse, 30 percent involved speeding, and 21 percent involved distracted drivers.7 Self-driving vehicles will never do any of these things. Though they suffer from their own problems and limitations, and though some accidents are inevitable, replacing all human drivers by computers is expected to reduce deaths and injuries on the road by about 90 percent.8 In other words, switching to autonomous vehicles is likely to save the lives of one million people every year.

since every vehicle is an autonomous entity, when two vehicles approach the same intersection at the same time, the drivers might miscommunicate their intentions and collide. Self-driving cars, in contrast, can all be connected to one another. When two such vehicles approach the same junction, they are not really two separate entities—they are part of a single algorithm. The chances that they might miscommunicate and collide are therefore far smaller. And if the transportation department decides to change some traffic regulation, all self-driving vehicles can be easily updated at exactly the same moment, and barring some bug in the program, they will all follow the new regulation to the letter.4

Some of these bots are already arriving in 2021 in more primitive forms. Recently, when I was in quarantine at home in Beijing, all of my e-commerce packages and food were delivered by a robot in my apartment complex. The package would be placed on a sturdy, wheeled creature resembling R2-D2. It could wirelessly summon the elevator, navigate autonomously to my door, and then call my phone to announce its arrival, so I could take the package, after which it would return to reception. Fully autonomous door-to-door delivery vans are also being tested in Silicon Valley. By 2041, end-to-end delivery should be pervasive, with autonomous forklifts moving items in the warehouse, drones and autonomous vehicles delivering the boxes to the apartment complex, and the R2-D2 bot delivering the package to each home. Similarly, some restaurants now use robotic waiters to reduce human contact. These are not humanoid robots, but autonomous trays-on-wheels that deliver your order to your table. Robot servers today are both gimmicks and safety measures, but tomorrow they may be a normal part of table service for many restaurants, apart from the highest-end establishments or places that cater to tourists, where the human service is integral to the restaurant’s charm. Robots can be used in hotels (to clean and to deliver laundry, suitcases, and room service), offices (as receptionists, guards, and cleaning staff), stores (to clean floors and organize shelves), and information outlets (to answer questions and give directions at airports, hotels, and offices). In-home robots will go beyond the Roomba. Robots can wash dishes (not like a dishwasher, but as an autonomous machine in which you can pile all the greasy pots, utensils, and plates without removing leftover food, with all of them emerging cleaned, disinfected, dried, and organized). Robots can cook—not like a humanoid chef, but like an automated food processor connected to a self-cooking pot. Ingredients go in and the cooked dish comes out. All of these technology components exist now—and will be fine-tuned and integrated in the decade to come. So be patient. Wait for robotics to be perfected and for costs to go down. The commercial and subsequently personal applications will follow. By 2041, it’s not far-fetched to say that you may be living a lot more like the Jetsons!

If you’re feeling down about the world, the book, “Resource Revolution: How to Capture the Biggest Business Opportunity in a Century,” is an antidote. Mr. Rogers and Mr. Heck outline how emerging advances — among them 3-D printing, autonomous vehicles, modular construction systems and home automation — might in time alter some of the world’s largest industries and bring prosperity to billions of people.

Machine learning also has a growing role on the battlefield. Learners can help dissipate the fog of war, sifting through reconnaissance imagery, processing after-action reports, and piecing together a picture of the situation for the commander. Learning powers the brains of military robots, helping them keep their bearings, adapt to the terrain, distinguish enemy vehicles from civilian ones, and home in on their targets. DARPA’s AlphaDog carries soldiers’ gear for them. Drones can fly autonomously with the help of learning algorithms; although they are still partly controlled by human pilots, the trend is for one pilot to oversee larger and larger swarms. In the army of the future, learners will greatly outnumber soldiers, saving countless lives.

I can easily envision a future system in which all of our vehicles are autonomous, just like our electric grid and your refrigerator. You’d take out your smartphone and, Uber-style, summon an autonomous get-you-to-work vehicle. The autonomous vehicle company takes care of the car and sends you a bill for each ride. If those vehicles coordinated with each other the way our mobile phones and their communication cells do, and these robot cars were electric … oooh! We’d have far fewer car wrecks, less pollution, and more free time.

Technology innovation is a key factor in retaining the gains produced by business model innovation. After all, if one technology innovation can create a new market, another technology innovation can render it obsolete, seemingly overnight. While Uber has achieved massive scale, the greatest threat to its future doesn’t come in the form of direct competitors like Didi Chuxing, though these are formidable threats. The greatest threat to Uber’s business is the technology innovation of autonomous vehicles, which could make obsolete one of Uber’s biggest competitive advantages—its carefully cultivated network of drivers—essentially overnight.

In this scenario, ten years from now, if the tech giants are not restrained and their power as data-monopolies becomes further entrenched, governments will find themselves increasingly sidelined and impotent. Reduced to mere gatekeepers, politicians and civil servants will likely retreat behind algorithmic government, with laws shaped by data and machine learning, with all its inherent biases and imperfections, and public services gradually surrendered to private businesses. Indeed, we should expect just about every area of human existence, currently managed by government, to be dominated by Big Tech and its outriders: from the future of finance (just about everyone), to healthcare (Google), and from low-cost housing (Apple, Google) to education (Google, again) and autonomous vehicles (Tesla, Alphabet, Amazon, Apple, etc.).

4IR is marked by emerging technological breakthroughs in a number of fields, including robotics, AI, blockchain, nanotechnology, quantum computing, biotechnology, Internet of Things (IoT), 3D printing, and autonomous vehicles.

Many of the AI companies I’ve invested in are looking to build a single AI-driven product that can replace a specific kind of worker—for instance, a robot that can do the lifting and carrying of a warehouse employee or an autonomous-vehicle algorithm that can complete the core tasks of a taxi driver. If successful, these companies will end up selling their products to companies, many of whom may lay off redundant workers as a result.

All of the other stuff—autonomous vehicles, drones—is just chaff, designed to keep customers and, even more so, employees pumped up.

Another great resource is podcasts, but these generally take time to sift through. I think the best all-around podcast comes from the heavyweights at Andreessen Horowitz (stylized as “a16z”). The a16z podcast has become a true force in understanding any given sector through interviews with thought leaders and great entrepreneurs in their space. I began to develop an interest in the bitcoin blockchain protocol, how it works, and if a blockchain network independent of bitcoin (or any other currency) could really exist in the long-term. Aside from the incredible reporting and research coming out of the CoinDesk news site, there seems to be no better resource than a16z’s interview with the CEO of Chain, Adam Ludwin. In a16z’s “Blockchain vs./ and Bitcoin,” Adam explained what bitcoin is, its limitations, and how blockchain can prosper and create decentralized networks for other financial instruments and stores of value like merchant-issued currency (gift card transfer), airtime on a mobile phone, energy credits on a grid and even tokens for machine-to-machine communication as we enter into the internet-of-things (IoT) and the autonomous vehicle era. The Product Hunt, Rocketship.fm and Accidental Creative podcasts are also not bad places to start.

Education hasn’t changed enough to prepare us for the world we live in today. In a era of autonomously driven electric cars and vehicles capable of taking us to Mars, our education system is the equivalent of a horse and carriage.

Urmson and his colleagues learned that as their technology improved, the humans using it would become less reliable. “We realized that this was going to be much much harder to do than we had thought,” said engineer Dave Ferguson. “It just became clear that, look, if we can’t rely on the driver to pay attention, or to hand over control to, then basically we just have to solve the whole problem. We need to have this vehicle not need the driver.

Because autonomous vehicles lack the commonsense reasoning capabilities to handle these unanticipated situations, their manufacturers have only two choices. They can try to collect data on human encounters with rare phenomena and use machine learning to build systems that can learn how to handle each of them individually.

The Insurance Institute for Highway Safety analyzed five thousand car accidents and found that if autonomous vehicles do not drive more slowly and cautiously than people, they will only prevent one-third of all crashes.

due to the lack of commonsense reasoning in autonomous vehicles, coupled with the seeming impossibility of anticipating every possible situation a vehicle might encounter, we will probably not see autonomous vehicles dominating our highways and city streets for a long time.

DARPA—the Advanced Research Projects Agency of the U.S. Department of Defense. In Iraq and Afghanistan, American soldiers riding in tanks and trucks were being maimed and killed by IEDs. In response, the Defense Department was determined to develop vehicles that would not need drivers—what would become known as autonomous vehicles.

The central function of the amygdala, which I call the brain’s smoke detector, is to identify whether incoming input is relevant for our survival.11 It does so quickly and automatically, with the help of feedback from the hippocampus, a nearby structure that relates the new input to past experiences. If the amygdala senses a threat—a potential collision with an oncoming vehicle, a person on the street who looks threatening—it sends an instant message down to the hypothalamus and the brain stem, recruiting the stress-hormone system and the autonomic nervous system (ANS) to orchestrate a whole-body response. Because the amygdala processes the information it receives from the thalamus faster than the frontal lobes do, it decides whether incoming information is a threat to our survival even before we are consciously aware of the danger. By the time we realize what is happening, our body may already be on the move.

Forecasts of completely autonomous road vehicles were made repeatedly during the 2010s: completely self-driving cars were to be everywhere by 2020, allowing the operator to read or sleep during a commute in a personal vehicle. All internal combustion engines currently on the road were to be replaced by electric vehicles by 2025: this forecast was made and again widely reported as a nearly accomplished fact in 2017. A reality check: in 2022 there were no fully self-driving cars; fewer than 2 percent of the world’s 1.4 billion motor vehicles on the road were electric, but they were not “green,” as the electricity required for their operation came mostly from burning fossil fuels: in 2022 about 60 percent of all electricity in general came from burning coal and natural gas.

senses a threat—a potential collision with an oncoming vehicle, a person on the street who looks threatening—it sends an instant message down to the hypothalamus and the brain stem, recruiting the stress-hormone system and the autonomic nervous system (ANS)

There’s no better case study showing how connectivity and computing power will turn old products into digitized machines than Tesla, Elon Musk’s auto company. Tesla’s cult following and soaring stock price have attracted plenty of attention, but what’s less noticed is that Tesla is also a leading chip designer. The company hired star semiconductor designers like Jim Keller to build a chip specialized for its automated driving needs, which is fabricated using leading-edge technology. As early as 2014, some analysts were noting that Tesla cars “resemble a smartphone.” The company has been often compared to Apple, which also designs its own semiconductors. Like Apple’s products, Tesla’s finely tuned user experience and its seemingly effortless integration of advanced computing into a twentieth-century product—a car—are only possible because of custom-designed chips. Cars have incorporated simple chips since the 1970s. However, the spread of electric vehicles, which require specialized semiconductors to manage the power supply, coupled with increased demand for autonomous driving features foretells that the number and cost of chips in a typical car will increase substantially.

The U.S. military is already fielding the first generation of new autonomous vehicles, like Saildrone, an unmanned windsurfer that can spend months roving the oceans while tracking submarines or intercepting adversaries’ communications. These devices cost a tiny fraction of a typical Navy ship,

the years ahead, Tesla would also expand its vehicle fleet, adding a compact SUV, a pickup truck, a heavy-duty truck, and a small bus into the mix. The buses would be autonomous, to be summoned by smartphone app, or via buttons at existing stops. The advent of full self-driving capability, which Musk said would ultimately be safer than human-driven vehicles by an order of magnitude, would also enable a business built around car-sharing. Owners could add their cars to Tesla’s shared fleet to generate income when they weren’t using them. In cities where there weren’t enough customer-owned cars to meet the demand for such shared-use cases, Tesla would operate its own fleet—a move that would put it in direct competition with Lyft and Uber.

for Level 1 the car had some advanced driver-assistance technology, such as automatic emergency braking, but the driver still controlled the vehicle at all times. Level 5 was the highest, at which a car would have no controls for human drivers whatsoever. At that point, you could read a book, take a nap, or watch a movie while the car drove itself. Google has tested fully autonomous vehicles to a Level 5 designation, meaning the cars could perform all “safety-critical driving functions and monitor roadway conditions for an entire trip,” but they haven’t yet left the test circuit. The development of autonomous vehicles goes hand in hand with the development of electric vehicles, because self-driving cars are best controlled by drive-by-wire systems, in which electrical signals and digital controls, rather than mechanical functions, operate a car’s core systems, such as steering, acceleration, and braking.

In 2016, Tesla announced that every new vehicle would be equipped with all the hardware it needs to drive autonomously, including a bevy of sensors and an onboard computer running a neural network.2 The kicker: the autonomous AI software won’t be fully deployed. As it turns out, Tesla will test drivers against software simulations running in the background on the car’s computer. Only when the background program consistently simulates moves more safely than the driver does will the autonomous software be ready for prime time. At that point, Tesla will release the program through remote software updates. What this all means is that Tesla drivers will, in aggregate, be teaching the fleet of cars how to drive.

Volvo has adopted a similar approach. Its ‘Autonomous Emergency Braking’ system, which automatically slows the car down if it gets too close to a vehicle in front, is widely credited for the impressive safety record of the Volvo XC90. Since the car first went on sale in the UK in 2002, over 50,000 vehicles have been purchased, and not a single driver or passenger within any of them has been killed in a crash.

Google has taken a slow-and-steady approach to gathering that data, driving around its own small fleet of vehicles equipped with very expensive sensing technologies. Tesla instead began installing cheaper equipment on its commercial vehicles, letting Tesla owners gather the data for them when they use certain autonomous features. The different approaches have led to a massive data gap between the two companies. By 2016, Google had taken six years to accumulate 1.5 million miles of real-world driving data. In just six months, Tesla had accumulated 47 million miles.

There will be circumstances that force an autonomous vehicle to make agonizing ethical decisions, like whether to veer right and have a 55 percent chance of killing two people or veer left and have a 100 percent chance of killing one person.

How should an autonomous vehicle’s algorithm weigh the life of its owner? Should your self-driving car sacrifice your own life to save the lives of three other people?

In 1830, America’s farmers comprised seventy-one percent of the workforce. Yet, in modern times, this number had plummeted to less than two percent. Improved automation of farms had impacted a greater percentage of the workforce than autonomous vehicles ever could. Even so, society had readily absorbed the loss of these farming jobs, which had morphed into opportunities in other sectors.

The possibility of a seamless network of electrified robo-taxis, self-driving delivery vehicles, and public transit linked to smartphone applications might seem like science fiction, but the COVID-19 pandemic crisis in 2020 gave a flavor of what is to come. In China’s pandemic epicenter of Wuhan, unmanned, autonomous electric vehicles, monitored remotely from a computer screen in a different location, were used to deliver hospital supplies, to disinfect isolation areas, and to deliver meals to quarantined people.