Government plans to cut traffic jams with Artificial Intelligence

The government could soon open up data surrounding planned roadworks, allowing navigation apps with artificial intelligence (AI) technology to …

The government could soon open up data surrounding planned roadworks, allowing navigation apps with artificial intelligence (AI) technology to predict jams months in advance.

More on how data and AI are being used to make motorists’ lives easier:

According to the Department for Transport (DfT), the government plans to release data on “planned changes to the road network”. This, the department says, will give tech firms the chance to feed the information to their AI route planning systems, allowing them to predict traffic jams and provide more accurate journey time estimates.

It’s all part of a review of legislation around Traffic Regulation Orders (TROs) – the orders that allow for temporary roadworks or permanent changes to the road. This, in turn, is part of the government’s Future of Mobility Grand Challenge, considering whether current legislation is fit to maximise the potential of future technologies.

UK roadworks cones and directional signs on motorway

As a result, the government says it plans to introduce legislation that will make it easier for tech firms to access data around the predicted 50,000 yearly road closures. The DfT says the change, which will be achieved in collaboration with organisations including councils and automotive technology companies, could lead to drivers being warned of planned disruption well ahead of the event, helping them to save time and money.

In a statement, the DfT said the plans will “give drivers confidence” to plan important trips without the fear of being stuck in traffic, while the system will also help to reduce congestion and delays. Furthermore, the department says the scheme could also improve air pollution by reducing the number of vehicles in traffic hotspots.

Roadworks signs on a street in London

“As a road user, there is nothing more frustrating than discovering roadworks and getting stuck in traffic jams,” said George Freeman, the Conservative MP for Mid-Norfolk. “Today’s announcement will help open up data, reducing congestion, pollution and frustration for road users.”

But the DfT says the new rules could do more than just improve journeys for motorists. The department points to evidence that suggests opening up TRO data could also help with route planning systems for self-driving vehicles.

This would help the government achieve its goal of becoming a world leader in autonomous vehicle technology. Such is the government’s ambition that it has already set a target of having self-driving cars on the roads of Britain by 2021.

Google Driverless Car

Speaking in February, automotive minister Richard Harrington said the government wanted to ensure the UK was the country chosen to develop and build driverless cars.

“The UK has a rich heritage in automotive development and manufacturing, with automated and electric vehicles set to transform the way we all live our lives,” he said. “We want to ensure through the Industrial Strategy Future of Mobility Grand Challenge that we build on this success and strength to ensure we are home to development and manufacture of the next generation of vehicles.”

Sensing and wireless communication systems of autonomous self driving cars

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Porsche invests in autonomous vehicle sensor startup

The strategic investment is part of a Series A financing round, initially led by Intel Capital and Israeli venture fund Grove Ventures. Porsche has held …

With an eye on the autonomous vehicle market, German automaker Porsche has acquired a minority stake in TriEye, an Israeli startup that’s working on a sensor technology to help vehicle driver-assistance and self-driving systems see better in poor weather conditions like dust, fog and rain, according to an online article on TechCrunch.

The strategic investment is part of a Series A financing round, initially led by Intel Capital and Israeli venture fund Grove Ventures. Porsche has held shares in Grove Ventures since 2017.

Founded in 2017, TriEye has patent-pending technology that promises to solve the low visibility problem created by poor weather conditions. The startup’s co-founders argue that existing sensors such as radar, LiDAR and standard cameras don’t solve this problem. The company believes the answer centers on short-wave infrared (SWIR) sensors.

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TriEye has developed an HD SWIR camera that is smaller, has higher resolution, and is less expensive than other technologies. The camera is due to launch in 2020. The technology is based on advanced nano-photonics research by Uriel Levy, a TriEye co-founder and CTO who is a professor at the Hebrew University of Jerusalem.

Michael Steiner, a Porsche AG board member focused on R&D, believes TriEye’s technology has strong promise. “We see great potential in this sensor technology that paves the way for the next generation of driver assistance systems and autonomous driving functions,” Steiner said in a statement. “SWIR can be a key element; it offers enhanced safety at a competitive price.”

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Your Car Will Probably Be Driven By A Remote Human Before A Computer

But I was reminded of it recently when gig economy company Doordash purchased Scotty Labs, which TechCrunch describes as “a tele-operations …

Illustration for article titled Your Car Will Probably Be Driven By A Remote Human Before A Computer
Photo: AP

If we’ve learned anything from Silicon Valley, it’s to over-promise and under-deliver. And if we’ve learned anything else from Silicon Valley, it’s that replacing humans with artificial intelligence is not nearly as easy as it sounds.

Put these two tendencies together, and you get an awful lot of humans performing grunt work that tech companies previously wanted to automate away only to find they couldn’t write algorithms that performed as well as any human could. The first examples that immediately jump to mind are content moderation on the major social networks, transcribing recordings from smart speakers, and Elon Musk’s attempt to automate the Tesla assembly line only to admit “humans are underrated.”

Don’t look now, but self-driving cars are a prime candidate to be the latest major “automation” technology that is performed not by a computer, but by a human you can’t see. Think of it kind of like drone piloting, except if the Department of Defense had initially promised drones would fly and bomb all by themselves.

I’ve been thinking about this possibility for a while—partly after reading my colleague Jason Torchinsky’s book—as there are a number of startups working in what they call the tele-operations field. But I was reminded of it recently when gig economy company Doordash purchased Scotty Labs, which TechCrunch describes as “a tele-operations company that is working on technology to enable people to remotely control self-driving cars.” “Remotely control self-driving cars” is one hell of an oxymoron!


Scotty’s approach seems to be to combine autonomous driving in some scenarios with remote driving in others. And they’re far from the only ones. According to WIRED, “Waymo, General Motors’ Cruise, Nutonomy, Zoox,, Uber, and Nissan are all quietly developing teleoperation systems” in addition to the subject of WIRED’s article, Phantom Auto (WIRED did not mention Scotty).

In some ways this makes sense. The available evidence so far is that self-driving cars can probably get pretty damn good at driving in uncomplicated situations like well-marked highways without road work, but more complex situations like urban driving may remain vexing for decades to come. Calling up a human elsewhere to take control of the complicated situations doesn’t sound so crazy.


But driving a car in a populated area from hundreds or thousands of miles away is a bit more complicated than piloting a drone. Remote pilots have long been plagued by latency issues, where what’s on the screen is seconds behind what’s happening in real life. For drone pilots, latency is problematic and annoying but not a deal-breaker.


That’s not the case with cars. Even a single second of latency would make it nearly impossible to drive the car safely, not to mention if the car experienced connectivity issues or other network failures.

And that’s just the most glaring complication tele-operation poses. Liability in the case of crashes, labor issues, and regulatory hurdles are all giant cans of worms. Who will the drivers work for? What kind of safety regulations or driving standards will apply to them? Can they live in one state and drive in another? What about another country? Will people want some random stranger driving their car?


Regardless of how these questions get sorted, remote drivers feels much more in keeping with the reality Silicon Valley has actually delivered rather than the ones it continually promises with extended deadlines. Derek Thompson of The Atlantic called this reality “a new underclass of urban servants” which includes “the ‘Uber for X’ economy—that nebulous network of people contracted through online marketplaces for driving, delivery, and other on-demand services,” an economy of which Scotty’s new owner Doordash is very much a part.

For those lucky enough to benefit from such services—as with anyone rich enough to have servants—life becomes a frictionless amalgam of goods and services magically appearing before you. But for the servants, it means long, underpaid hours with no benefits and limited protections from labor law.


Obviously, tele-operations doesn’t exist yet, so one cannot say what life will be like for these hypothetical remote drivers. But if history is any guide, it will be a race to the bottom in terms of pay and work conditions, perhaps involving endless terminals in a vast warehouse. As with so many aspects of our lives these days, it’s only too easy to envision a future that is not only sub-optimal, but dystopian.

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Self-Driving Cars Still Face A Long Road

Uber CEO Travis Kalanick promised in 2016 that his company would get rid of human drivers by 2020. Various automakers heralded a huge shift in …

Self-driving cars are the future. Probably. Just maybe not as near a future as the automotive industry – and optimistic investors – had imagined.

A few years ago, the rise of driverless cars seemed not only inevitable but imminent. Google CEO Sergey Brin once predicted that “ordinary people” would be using fully autonomous vehicles by 2017. Uber CEO Travis Kalanick promised in 2016 that his company would get rid of human drivers by 2020. Various automakers heralded a huge shift in the type of vehicles they’d be making within a handful of years. Just a few years ago, the federal Transportation Department worried that technology would outpace regulation.

But more recently, a future without drivers seems much further off. In 2018, a self-driving car owned by Uber killed a pedestrian in Tempe, Arizona. That accident put a chill on not only Uber’s testing, but the development of other autonomous vehicles, as popular sentiment shifted toward greater wariness. Companies abruptly seemed to realize the high stakes that testing in populated areas might involve.

Popular distrust may also hinder the widespread adoption of driverless cars, even as the technology improves. Beyond worries about accidental collisions, security is a major concern. No passenger wants to be in a car when the driver is subject to hacking. AAA found that 71% of Americans surveyed were afraid to ride in a fully autonomous car. Industry experts suggest that this fear will decrease as people have more experience with these vehicles. But when and how most people will get that experience isn’t clear.

Beyond safety concerns, there are other practical considerations. As Timothy B. Lee observed for Ars Technica earlier this year, there are two phases of development for self-driving cars. The first involves making sure the vehicle obeys traffic laws, preserves the safety of passengers and pedestrians, and generally avoids obstacles. Some companies, including Waymo, have made it this far.

Yet the second stage may be equally important for widespread adoption. In stage two, vehicles will have to learn to make quick, accurate decisions in order to move as a skilled human driver might. Otherwise, the vehicle could have trouble navigating roundabouts, merging onto highways, or completing other potentially dangerous but essential elements of driving. A car that doesn’t master stage two may get you safely from point A to point B, but it would be a long and frustrating ride. As Sam Anthony, the chief technology officer of Perceptive Automata, told The Huffington Post, “The difference between a good self-driving car and a perfect self-driving car is massive.”

Creating a smooth and straightforward ride has proven more challenging than automakers initially anticipated. While driving on well-paved roads in good conditions is one thing, autonomous vehicles have had trouble with heavy rain and other challenging weather. Construction and badly maintained roads also cause problems. Self-driving cars will need to anticipate the actions of human drivers, cyclists and pedestrians, which may be hard to predict through programming. All of this means development has taken more time than companies originally projected.

Regulation is also a concern. No federal rules currently govern the testing or development of autonomous vehicles, though some states make it harder or easier for developers to operate. Carmakers also may try to influence lawmakers. Some have suggested that updating road infrastructure could mitigate some of the vehicles’ technological shortcomings. An unnamed automotive official suggested to The New York Times that Manhattan could install anti-jaywalking gates at each intersection. (I’ll let you imagine how New Yorkers are likely to take this idea.) How the interplay between government and business evolves may hinder or help the rollout of self-driving cars and trucks.

While boosters remain – Tesla CEO Elon Musk remains confident that driverless vehicles will shuttle people to their destinations by late 2020 – most industry insiders agree we’re decades away from fleets of cars that don’t need monitoring from a human driver. General Motors’ subsidiary Cruise said in 2017 that it would launch automated taxis in San Francisco by the end of 2019. This July, Cruise announced that it would not meet the deadline and did not set a new one. Waymo launched a taxi-like service in Arizona last year as promised, except that human drivers remain behind the wheel.

In light of all these setbacks, it seems reasonable to wonder: Just how far away are self-driving cars from commonplace use? What if they never arrive at all, at least to the extent developers have promised?

Self-driving cars are not an all-or-nothing proposition. Many vehicles on the road now boast “advanced driver assistance systems” that automate at least some tasks, such as adaptive cruise control or the ability to park with minimal driver input. Much like automatic transmissions and power steering, such features are likely to become an everyday part of how we drive as older cars leave the roads. Even if we don’t reach a point where there is no driver, the driver may be able to rely with increasing confidence on the car’s computing power.

SAE International, an organization that develops engineering standards in the automotive industry and others, describes vehicle automation on a scale of zero to five. At level zero, the human driver is responsible for all driving tasks. Most cars with “advanced driver assistance systems” would be around a level two, though level three automated vehicles may become common in the future. Think of the way autopilot systems today assist in most, if not all, aspects of flying a commercial jet. Level five would be a fully autonomous experience, in which the only thing a human needs to do is enter the destination. That has yet to arrive.

In some cases, full level-five autonomy may never be the goal. For example, most startups focused on long-haul trucking intend to leave urban driving to humans for the foreseeable future, even when trucks are ready to handle highways unaided. Yet for those invested in a completely autonomous future for cars, levels one through four likely aren’t good enough.

Based on indications today, I would not be surprised to see autonomous vehicles in more limited use in the near future. On a closed course under controlled conditions, they can work. For instance, Optimus Ride recently launched a shuttle service in the Brooklyn Navy Yard, which will carry passengers between the office park’s entrance and its new ferry dock. (For now, this service still involves human operators as a safety precaution.) Autonomous vehicles may be useful in areas that are otherwise closed to motor vehicles – say, moving people around amusement parks, airports or college campuses.

Investors, however, have plenty of reasons to be wary of any champagne-tinted predictions that traditional, human-driven cars will vanish. Self-driving cars are unlikely to revolutionize the auto industry in the next few years. They are not going to resolve the economics of ride-hailing services like Uber in the next year or two, either. In fact, like ride-hailing – as well as food delivery services and a variety of other sectors – self-driving cars are attracting a lot of hype but haven’t yet proven a profitable and reliable part of our future.

When it comes to truly driverless cars, the future may or may not be coming, but it certainly isn’t now.

Vice President and Chief Investment Officer Paul Jacobs, of our Atlanta office, contributed several chapters to our firm’s book, Looking Ahead: Life, Family, Wealth and Business After 55, including Chapter 12, “Retirement Plans;” Chapter 15, “Investment Approaches and Philosophy;” and Chapter 19, “A Second Act: Starting a New Venture.”

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The Driverless-Car Pile-Up and the Folly of ‘Industrial Policy’

One early backer, the firm Lux Capital, recently raised a $1 billion fund based on the company’s success as a crown jewel in its portfolio. It’s one of a …
A fleet of Uber self-driving cars at a technology demonstration in September 2016. (Aaron Josefczyk/Reuters)

If our best and brightest venture capitalists can’t pick winners, the government doesn’t stand a chance.

The idea that the government might successfully support and steer innovation is making a comeback as wonks both left and right show a renewed interest in “industrial policy.” But faceless functionaries steering anything from D.C. should terrify us all. Even the most credible, savvy venture capitalists and entrepreneurs fail at an astonishing rate. Why would a bureaucrat with a ton of money do better?

To see how difficult it is to push the frontier, take the coming wave of innovation in the auto industry.

Over the past three years now, I have watched from my perch at the corner of Broadway and Front Street in San Francisco as a small fleet of SUVs suffers the most dreadful punishment outside my office window. Circling and circling, sometimes farther and sometimes closer, but always coming back like two-ton boomerangs, these SUVs have taken the same routes around the same city blocks, every day, day after day.

It would make Sisyphus weep, so I can only imagine how the drivers must feel. Why would anyone condemn them to this fate? The rack of lidar sensors, radar, and cameras on top of each vehicle gives it away. Their owner, a startup down the street called Zoox, believes that if the fleet captures enough data — if it encounters enough wildly different urban anomalies that might pop up on the road (a plastic bag in the air, a bike on the back of a car, a child chasing a ball in the rain) and learns to recognize and plan around them — then boom! The age of self-driving vehicles will have arrived, ushering in the greatest tectonic shift in transportation since the Wright brothers took off at Kitty Hawk.

Zoox is a five-year-old company worth over $3 billion, having raised $800 million from some of the best venture capitalists out there. One early backer, the firm Lux Capital, recently raised a $1 billion fund based on the company’s success as a crown jewel in its portfolio. It’s one of a number of companies — including Aurora, GM’s Cruise, Alphabet’s Waymo, and even Tesla — betting on the super-intelligent Mr. Magoo theory of self-driving cars. Like Mr. Magoo, their vehicles experience technical hitches due to near-sightedness and a stubborn refusal to admit the problem. Their hope is that if they jack up Mr. Magoo’s brain to superintelligent power and have him circle the block a trillion times, his poor eyesight won’t stop him, because the recognition algorithms running on his visual cortex will be able to identify the intentions of another driver from the faint blur of a mere handful of pixels, even at a 150 yard distance while traveling 60 miles an hour.

Good luck with that, especially at night in the rain.

Of all the Magoos, Tesla at least has the advantage of drawing data from 500,000 cars let loose on the roads. As of this spring, Tesla was training and updating its self-driving software from the experiences of 500,000 cars with a radar, eight cameras, and twelve ultrasonics. “All the cars being produced have all the hardware necessary — computer and otherwise — for full self-driving,” Tesla CEO Elon Musk said at his company’s Automation Day presentation on April 22 of this year. “I’ll say that again: All Tesla cars being produced right now have everything necessary for full self-driving. All you need to do is improve the software.”

Full self-driving hardware! Just take Mr. Magoo around the block a few trillion times and he’ll be fine. They’ll update his brain. Of course, as the many videos of Teslas self-parking on YouTube will attest, Musk’s cars park like, well, Mr. Magoo: poorly and slowly. Perhaps failure to live up to Musk’s proclamation explains why 32 Tesla executives have been fired or asked to step down in the 18 months or so.

Musk has to exaggerate because Tesla is a car company whose stock trades like a tech company. Tesla might sell 400,000 cars this year. By contrast, Ford might sell 6 million, GM 8.5 million. Granted, the Tesla Model 3 looks and drives like a dream. But when you count salaries and overhead according to Tesla’s own quarterly statements, it costs more to make a Tesla than people are willing to pay for it. And that calculus includes the federal subsidies that will dry up on December 31 of this year. Ford is worth $35 billion and makes money on its cars. Tesla is worth $40 billion and doesn’t. How is this math possible?

Tesla’s stock trades at such a large multiple of its revenue because Musk has convinced shareholders that it’s not a car company, but an artificial-intelligence company that happens to use a fleet of 500,000 cars to collect and label data. It’s a clever sleight-of-hand, but it’s not fooling those who matter. As a fund manager on Wall Street once told me, “You’re not a hedge-fund manager until you’ve shorted Tesla at least once.”

Well, win some, lose some, wreck some. The venture-capital industry and the autonomous-vehicle market wouldn’t be nearly as exciting if some people didn’t get sacked, sued, go under, blow up, or beg for mercy in Chapter 11 proceedings every so often. For those in the grandstands watching the tech world, it’s lights out and away we go. The industry is one or two hairpin turns away from a colossal crash of bankruptcies, acquisitions, foldings, and consolidation. If the prize is rich and the future a golden promise, there is still a long way to go, and in the short term things are going to get nasty.

In fact, we estimate that ninety percent of the startups in the autonomous-vehicle space today will not exist in five years. A startup called was putt-putting on fumes when Apple scooped it up for pennies in an acquisition this summer. Driving-assist startup Scotty Labs was just acquired by DoorDash. Intel bought the automotive-camera maker MobileEye for $15 billion. Ford and Volkswagen recently announced they were teaming up instead of going at it alone. For the industry itself, this is the beginning. But for many of the players, the end is near.

The big crunch is coming because, over the next year, all the major auto and trucking companies will decide on who will be the suppliers for their main production lines in 2022. This won’t be for full self-driving, but for something a little more modest if still vitally important: a car so safe it is incapable of crashing. Once the major auto companies settle on their suppliers, once the music stops, it’s going to be kaput for anyone else who doesn’t have a chair.

To lay my cards on the table, my own venture-capital company, the 1517 fund, is betting that the Magoos’ labor will continue to yield weak results. Our biggest investment is in Luminar Technologies, a company making a perception system using a wholly unique lidar. Instead of only giving self-driving cars a brain, Luminar wants to give them better-than-human eyes, too. With key improvements on four core components — laser, receiver, microchip, and scanner — Luminar’s lidar is the only one that currently satisfies the major auto companies’ technical requirements for full autonomy in a vehicle. In other words, the data coming into the Luminar system is so rich that recognition algorithms can work faster and more accurately with less time to learn, even at night or in the rain.

Given these advantages over the Magoos, our fund fully expects to have a chair when the music stops. Our bet is that all the genius VCs backing contrarian founders and all the CEOs of companies commanding fleets that drive in circles for years will end up disappointed, while the rest of us building the future without lies and exaggerations celebrate. This is provided, of course, that government bureaucrats aren’t allowed to tip the scales and ruin the fun in the meantime, as I certainly hope they aren’t.

After all, if Elon Musk, Google, Apple, Intel, and the best and brightest VCs in the business could make such a colossal miscalculation, a federal pencil-pusher doesn’t stand a chance.

Michael Gibson is a co-founder of 1517 Fund and was previously the vice president for grants at the Thiel Foundation.

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