Our Zenzic CAM Creator series continues with Raunaq Bose, co-founder of Humanising Autonomy.
Before establishing predictive artificial intelligence (AI) company Humanising Autonomy in 2017, Raunaq Bose studied mechanical engineering at Imperial College London and innovation design engineering at the Royal College of Art. Focusing on the safety of vulnerable road users, Humanising Autonomy aims to redefine how machines and people interact, making cities safer for pedestrians, cyclists and drivers alike.
RB: “Our model is a novel mix of behavioural psychology, deep learning and computer algorithms. We work with OEMs and Tier 1 suppliers on the cameras on vehicles, with the aftermarket on retrofitted dashcams, and also with infrastructure. Our software works on any camera system to look for interactions between vulnerable road users, vehicles and infrastructure in order to prevent accidents and near misses. While most AI companies use black box systems where you can’t understand why decisions are made, we set out to make our models more interpretable, ethically compliant and safety friendly.
“When it comes to questions like ‘Is this pedestrian going to cross the road?’, we look at body language and factors like how close they are to the edge of the pavement. We then put a percentage on the intention. Take distraction, for example, we cannot see it but we can infer it. Are they on the phone? Are they looking at the oncoming vehicle? Is their view blocked? These are all behaviours you can see and our algorithm identifies them and puts a numerical value on them. So we can say, for example, we’re 60% sure that this pedestrian is going to cross. This less binary approach is important in building trust – you don’t want lots of false positives, for the system to be pinging all the time.
“One of the main things we’re likely to see over the next decade is increased use of micromobility, such as cycling and e-scootering. At the same time you will see more communication between these different types of transportation, and also with vehicles and infrastructure. The whole point of ADAS is to augment the driver’s vision, to reduce blind spots and, if necessary, take control of the vehicle to avoid a shunt. Then there’s the EU agreement that by 2022 all buses and trucks must have safety features to detect and warn of vulnerable road users.
“We currently only look at what’s outside the vehicle, but with self-driving there will be monitoring of the cabin. In terms of privacy, we have a lot of documentation about our GNPR processes and how we safeguard our data. Importantly, we never identify people, for example, we never watch for a particular individual between camera streams. We look to the future with autonomous cars but for now we’re focused on what’s on the road today.”
Our Zenzic CAM Creator series continues with Mika Rasinkangas, founder and President of Chordant.
Originally part of the global wireless and internet of things (IoT) research company, InterDigital, Chordant was spun out as a separate business in 2019, as “a dynamic data sharing expert”. The spark was a UK government initiative to test the hypothesis that regional transportation data has tremendous value, especially when shared between different parties. The results of this two-year public-private partnership were startling.
Please can you outline your work on connected and automated mobility?
MR: “First of all we looked at the mobility space. There’s the segment that maintains the road network and their supply chain, the mobility service providers – bus companies, train operators and new entrants such as Uber – then the whole automotive sector, OEMs and their supply chain partners. We sit right in the middle of all this and our role is data exchange – bringing dynamic data sets from different sources to come up with something different that solves problems with data driven solutions.
“The hypothesis was that a lot of data in the transport segment was either underutilised, in really small silos, or not utilised at all. The idea was to work with different entities – organisations, companies and universities – to bring data together and make it more widely available, leading to innovation and efficiency.
“It was obvious from early on that this was not only a technical issue, there was a human element. Data is controlled by different entities and departments so the challenge was to get these different data owners comfortable with the idea that their data could be used for other purposes, and to get consumers comfortable with it too. The result was more usable and more reliable dynamic data.”
What major shifts in UK transport do you expect over the next 10-15 years?
MR: “Last mile transport, micromobility solutions are ballooning and Covid19 will only accelerate this. People are walking, scootering and biking more, making short trips by means which don’t involve public transport or being in close contact to others.
“In terms of automotive, we’re living through a massive change in how people perceive the need to own a car, and this shift in perception is changing the fundamental business models. Autonomous vehicle technology keeps developing, connected vehicles are everywhere already and electric cars represent an ever bigger proportion of the vehicle population. In all these segments data utilisation will continue to increase. New cars collect huge amounts of data for lots of purposes and this can be used for lots of things other than what it was originally collected for.”
Can you address the data privacy concerns surrounding connected cars?
MR: “Data privacy is a multifaceted topic. On the one hand, Europe has been at the forefront of it with GDPR. That puts businesses operating in Europe on a level playing field. In terms of connected and autonomous vehicles (CAVs), these regulations set limitations on what data can be harvested and what has to be anonymised in order for someone to use it. It fits the norms of today’s society, but you can see in social media that this kind of privacy seems less important to younger people, however perspectives vary greatly and companies need to be transparent in usage of people’s data.
“From a business perspective, we have to take privacy extremely seriously. The explosion of data usage can have unintended consequences but by and large the regulatory environment works quite reasonably.
“We typically deal with conservative entities which put privacy and security in the middle of everything – if there’s any uncertainty it’s better to not do it, is the attitude. Think of all the sensitive personal data that entities like car companies and mobile telephone companies have. It can give an extremely accurate picture of peoples’ behaviour. There are well established procedures to anonymise data so customers can be comfortable that their personal data cannot be identified.”
What are the main risks in the shift to self-driving and how can these be mitigated?
MR: “One could talk about a lot of different challenges. What about the latency in connectivity in order to ensure processing takes place fast enough? There’s a gazillion of things, but to me these are technical nuts that will be cracked, if they haven’t been already. One of the biggest challenges is the interaction between human-controlled vehicles and automated vehicles. When you add in different levels of driver assistance, urban and rural, different weather conditions – all sorts of combinations can happen.
“The UK is at the forefront of CAV testing. There are government sponsored testbeds and companies are running trials on open roads, so the automotive industry can test in real-life environments. We cannot simulate everything, and the unpredictability of interactions is one of the biggest challenges. A traffic planner once told me that in his nightmares he sees a driverless car heading toward a granddad in a pick-up truck, because there’s just no telling how he might react!”
Is there anything else you’d like to mention?
MR: “I’d like to address the explosion of data usage in mobility and how dynamic data enables not only efficiency improvements but new business models. According to recent studies by companies like Inrix, congestion costs each American nearly 100 hours or $1,400 a year. Leveraging data-driven insights can drive change in both public policies and behaviours. In turn, these can result in reduced emissions, improved air quality and fewer pollution-caused illnesses.
“CAVs can be data sources providing tons of insight. Think about potholes – new vehicles with all these cameras and sensors can report them and have them fixed much more efficiently. This is just one example of entirely data-driven efficiency, much better than eyeballing and human reporting. There will be a multitude of fascinating uses.
“Organisations such as vehicle OEMs, transport authorities and insurance providers will require facilities for the secure and reliable sharing of data, and that’s where we come in. I would urge anyone interested in data driven solutions in the mobility space to visit chordant.io or our Convex service site at convexglobal.io.”
Prof John McDermid says the trolley problem is a nonsense, requiring self-driving vehicles to make distinctions that you or I could not.
Our Zenzic CAM Creator series continues with Professor John McDermid OBE FREng, Director of the Assuring Autonomy International Programme at the University of York.
Professor John McDermid has been Director of the Assuring Autonomy International Programme, a partnership between Lloyd’s Register Foundation and the University of York, since 2018. He advises government and industry on safety and software standards, including Five and the Ministry of Defence, and was awarded an OBE in 2010. The author of 400 published papers, his 2019 article, Self-driving cars: why we can’t expect them to be ‘moral’, was highly critical of the oft-quoted trolley problem in relation to driverless vehicles.
Professor John McDermid, University of York
PJM: “I’ve been at York for 30 years working on the safety of complex computer-controlled systems. What you define as complex changes all the time. In January 2018 we started a new programme, looking at the assurance of robots and autonomous systems, including automated mobility, but also robots in factories, healthcare and mining.
“It’s important to demonstrate the safety and security of novel technologies like machine learning, but there’s often a trade-off involved, because you can make things so secure they become unusable. If I open my car with the remote key I have a couple of minutes before it automatically locks again, and there’s a small possibility that someone could get their finger trapped if they try to open the door just as it automatically re-locks. We encounter these types of trade-offs all the time.”
What major shifts in UK transport do you expect over the next 10-15 years?
PJM: “Over the next decade we will get to Level4 autonomous driving, so in defined parts of the road network cars will drive themselves. We will solve the safety problems of that technology, but I’d be surprised if it is within five years. Despite the rhetoric, Tesla’s approach is not on track for safe autonomous driving within the year.
“At the same time, there will be a trend towards Mobility as a Service (MAAS). I love my car, but I’ve had it for 18 months and have only driven 7,000 miles. I sometimes ask myself why I have this expensive piece of machinery. A recent study showed that the average car in the UK is only used for 53 minutes a day. Mostly, they sit doing nothing, which, considering the huge environmental impact of manufacturing all these vehicles, is very wasteful.
“If I could call upon a reliable autonomous vehicle and be 99% certain that it would arrive in a timely manner, say within five minutes, I’d probably give up my car. It should also be noted that the two trends go hand-in-hand. Having Level4 is critical to achieving MAAS, delivering all the convenience of having your own car without any of the hassle.”
Can you address some of the data privacy concerns surrounding connected cars?
PJM: “We are back to this issue of trade-offs again. I want my MAAS so I’ve called it up and given the service provider some information about where I am. If they delete that information after I’ve paid then I’m prepared to accept that. What if the company wants to keep the information but won’t allow access except for law enforcement – would that be acceptable to the public? What can government agencies require this company to do?
“Another example: What if your 10-year-old daughter needs MAAS to take her to school? A reasonable concerned parent should be able to track that. What if the parents are divorced, can they both access that data? There’s clearly a privacy issue and there needs to be a legislative framework, but it’s a balance. For the purposes of getting from A to B, most people would accept it, so long as their data is normally kept private.”
Can you address concerns about the trolley problem in relation to self-driving cars?
PJM: “My basic feeling is that the trolley problem is a nonsense, a distraction. All these elaborate versions require self-driving vehicles to make distinctions that you or I could not.
“The big Massachusetts Institute of Technology (MIT) study sets a higher standard for autonomous vehicles than any human can manage. Who do you save, a child or an older person? The child because they can be expected to live longer and benefit more. However, this is based on false assumptions. I don’t believe in the split second of a crash you go into that sort of thought process – you focus on controlling the vehicle and in most cases the best option is to (try to) stop.
“I don’t know why people find the trolley problem so compelling, why they waste so much energy on it. I really wish it would go away. Fortunately, most people seem to be coming to that conclusion, although one of our philosophy lecturers strongly disagrees with me.”
Which sectors do you think will adopt self-driving first?
PJM: “Farming applications might come first as they are short of people in agriculture and the problems are simpler to overcome. If you geofence a field where you wish to use a combine harvester and equip it with technology so it doesn’t run over a dog lying asleep in the field – there’s already tech which is getting quite close to that – then that’s an attractive solution.
“Last mile freight via small delivery robots (like Nuro in the US and Starship here in the UK) might also come quickly, but longer distance freight will probably require a segregated lane. Even last mile robots come with risks, like people tripping over them.
“There’s a lot of commercial desire for robotaxis, and this is potentially a very big market. There are already genuine driverless taxis in the US now, but they have a much simpler road structure than here in the UK.
“The crucial technical bit is finding accepted ways of assuring the machine learning. I would say that, I work on it, but without that regulators and insurers won’t allow it.”
Our Zenzic CAM Creator series continues with Yosuke Ushigome, Director at design innovation studio Takram.
Listing his primary interest as “emerging technologies”, London-based creative technologist, Yosuke Ushigome, has been working with Toyota on future car concepts for over 10 years. Here, he gives his thoughts on the key issues in driverless car design.
Yosuke Ushigome, director Takram
YU: “We come from a user experience (UX) background and over the years our projects with Toyota have got bigger and higher level. In 2018, with the e-Palette concept, we started taking a more holistic approach to mobility and automation – an on-the-ground people perspective on the entire system, rather than the UX of an interior, exterior or service.
“There’s going to be a trend in transparency and trust. How can designers help the systems, passengers, pedestrians and others to communicate? In the past, this has usually been based around the driver and passenger, but that’s got to expand. In cars of the future, pedestrians will not be able to look into the driver’s eyes – what’s driving might not even be on the car, it might be in the cloud.
“How can you communicate interactions that facilitate trust? That’s really interesting. People pick things up from little movements in their peripheral vision, so you come back to old school ideas like patterns of flickering lights. How fast it flashes, or flashing from left to right, could give people a little nudge, maybe help them to detect danger. This kind of experimentation will definitely increase.
“Level5 autonomy seems to me to be very far off. Level4, in areas where the road system is designed for self-driving, or on private roads where there’s more separation between vehicles and pedestrians, is coming rapidly – things like deliveries between factories. Starship delivery robots are already deployed in Milton Keynes and economics will drive adoption, especially with the pandemic.
“I would like to be part of this transformation, so long as it is inclusive. There’s an opportunity to meet the needs of people left behind by our existing transport, whether that’s physical disability or economic disadvantage.”
Toyota e-Palette concept, via Takram
Toyota had planned to showcase its e-Palette mobility solution at the Tokyo 2020 Olympic and Paralympic Games, so hopefully we’ll get to see it next summer.
Our Zenzic CAM Creator series continues with the founder of Vivacity Labs, Mark Nicholson.
Vivacity uses sensors, cameras and artificial intelligence (AI) to provide “up-to-the-minute data on urban movement”, helping local councils to promote active travel, improve safety and reduce congestion. Big Brother you say? Well, it’s 2020 not 1984 and CEO Mark Nicholson is very happy to have that debate.
MN: “As the transport network becomes more complicated, local authorities need more powerful tools. Tech giants have invaded the ecosystem, and when you’re dealing with Uber and driverless cars, sending someone out with a clipboard just isn’t going to cut it. We bring new technology which tells them about their transport, so they can adapt and gain control over the ecosystem.
“We started with sensors and then video-based sensors, generating huge data sets and better quality data. We’ve looked at everything from cyclists undertaking to lockdown journey times and asked: how can we use this data to make the road system more efficient? The next phase is autonomous vehicles, because that ecosystem needs to work with both infrastructure and other road users.
“Privacy is not just a key issue in self-driving but in the whole smart city. There are basically two visions – the Chinese and the European. The Chinese vision is very invasive, it’s 1984 and that’s the point. The alternative is the European vision, with the General Data Protection Regulation (GDPR). For a while it looked like there might be a third, a corporate American vision. Google were running a smart city project in Canada, but it didn’t work out so we’re back to two models.”
If you don’t know about the Quayside project in Toronto, a much-shared Guardian article from 2019 warned of surveillance capitalism, data harvesting and the possibility that algorithms could be used to nudge behaviour in ways that favour certain businesses. You can read it here or, er, Google it.
MN: “We’re very much on the European, privacy-centric, citizen first side – an ecosystem that gives the benefits of mass data without the costs to privacy. All our data is anonymised at source, everything. Each camera or sensor unit has its own processor on board which uses AI to extract information, for example, what are the road users? The imagery is discarded within a few milliseconds, all we keep is the data. We recently looked at how socially distanced people were in Kent and, although no personal data was collected, it caused a bit of controversy.”
It did indeed. “Big Brother is watching your social distancing: Fury as traffic flow cameras are secretly switched to monitor millions of pedestrians in government-backed Covid project”, screamed the headline in the Daily Mail. We’d better get back to self-driving.
MN: “Over the last couple of years the hype around driverless cars has died down. There’s been a recognition that autonomous vehicles are not as close as Elon Musk promised. The technology is progressing though. They can drive quite well on motorways and in quiet areas, but in busy, congested areas they struggle.
“What would happen if you rolled out driverless cars today? My suspicion is they would probably perform to about the same level as human drivers. The question is: Are we happy with systemic risk rather than personal risk? Can we engineer out that risk? Can we make the infrastructure intelligent enough so it works with vehicles in even the most challenging situations?
“The best way to end the no-win scenario is to have enough data to dodge it. Most of these incidents come about due to an unforeseen element, such as a pedestrian stepping out, a cyclist skipping a red light or someone speeding round a corner. If the vehicle knows about it in advance, the trolley problem never occurs. For me it’s about having the data earlier, and how we, as representatives of infrastructure, can help to give cars that information.”
Welcome to a new series of interviews with our fellow Zenzic CAM Creators. First up, Clem Robertson, CEO of R4dar Technologies.
As a keen cyclist who built his own Cosworth-powered Quantum sportscar from scratch, it’s no surprise that the founder of Cambridge-based R4dar takes a unique approach to self-driving. Indeed, his involvement can be traced directly to one shocking experience: driving down a local country lane one night, he had a near miss with a cyclist with no lights. He vividly remembers how a car came the other way, illuminating the fortunate rider in silhouette and enabling an emergency stop. It proved to be a light bulb moment.
R4dar urban scene tags
What does R4dar bring to connected and automated mobility (CAM)?
CR: “I’d been working in radar for five or six years, developing cutting edge radar for runways, when the incident with the cyclist got me thinking: Why could my cruise control radar not tell me something was there and, importantly, what it was? This kind of technology has been around for years – in World War II we needed to tell the difference between a Spitfire and a Messerschmitt. They placed a signal on the planes which gave this basic information, but things can be much more sophisticated these days. Modern fighter pilots use five different methods of identification before engaging a potential bogey, because one or more methods might not work and you can’t leave it to chance whether to blow someone out of the sky. The autonomous vehicle world is doing similar with lidar, radar, digital mapping etc. Each has its shortcomings – GPS is no good in tunnels; the cost of 5G can be prohibitive and coverage is patchy; cameras aren’t much good over 100 metres or in the rain, lidar is susceptible to spoofing or misinterpretation; digital maps struggle with temporary road layouts – but together they create a more resilient system.”
How will your solutions improve the performance of self-driving cars?
CR: “Radar only communicates with itself, so it is cyber-resilient, and our digital tags can be used on smart infrastructure as well as vehicles – everything from platooning lorries to digital high vis jackets, traffic lights to digital bike reflectors. They can tell you three things: I am this, I am here and my status is this. For example, I’m a traffic light up ahead and I’m going to turn red in 20 seconds. Radar works in all weathers. It is reliable up to 250-300m and very good at measuring range and velocity, while the latest generation of radars are getting much better at differentiating between two things side-by-side. We are working with CAM partners looking to use radar in active travel, to improve safety and traffic management, as well as with fleet and bus operators. We are also working with the unmanned aerial vehicle (UAV) industry to create constellations of beacons that are centimetre-accurate, so that delivery drones can land in a designated spot in the garden and not on the dog!”
R4dar cyclists in fog
What major developments do you expect over the next 10-15 years?
CR: “Fully autonomous vehicles that don’t carry passengers will come first. There are already little robots on the streets of Milton Keynes and, especially with Covid, you will see a big focus on autonomous last mile delivery – both UAVs and unmanned ground vehicle (UGVs). You never know, we might see delivery bots enacting a modern version of the computer game Paperboy. More and more people in urban areas with only roadside parking will realise that electric cars are tricky to charge, unless you put the chargers in the road, which is expensive. If you only need a car one or two days a month, or even for just a couple of hours, there will be mobility as a service (MAAS) solutions for that. Why would you bother with car ownership? E-scooters are one to keep an eye on – once they’re regulated they will be a useful and independent means of getting around without exercising. Town centres will change extensively once MAAS and CAM take off. There will be improved safety for vulnerable road users, more pedestrianisation, and you might see segmented use at certain times of day.”
Do you see any downsides in the shift to self-driving?
CR: “Yes! I love driving, manual gearboxes, the smell of petrol, the theatre, but you can see already that motorsport, even F1, is becoming a dinosaur in its present form. People are resistant to change and autonomous systems prompt visions of Terminator, but it is happening and there will be consequences. Mechanics are going to have less work and will have to retrain because electric motors have less moving parts. Courier and haulage driving jobs will go. Warehouses will be increasingly automated. MAAS will mean less people owning their own cars and automotive manufacturers will have to adapt to selling less vehicles – it’s a massive cliff and it’s coming at them much faster than they thought – that’s why they’re all scrambling to become autonomous EV manufacturers, it’s a matter of survival.”
R4dar lights in fog
So, to sum up….
CR: “Fully autonomous, go-anywhere vehicles are presented as the utopia, but there’s a realisation that this is a difficult goal, or at least a first world problem. There might always be a market for manned vehicles in more remote locations. A lot of the companies in this industry specialise in data, edge processing and enhanced geospatial awareness, and that will bring all kinds of benefits. How often have you driven in fog unable to see 10m in front of you? Self-driving technology will address that and many other dangers.”
Hearing bold predictions like these from a petrolhead like Clem, suddenly Zenzic’s ambitious 10-year plan seems eminently achievable.
In an explosive exclusive interview with Cars of the Future, transport expert Christian Wolmar presents a devastating critique of the self-driving dream.
As an arch critic of the UK’s autonomous vehicle plans, transport commentator Christian Wolmar sums up his views in the title of his book, Driverless Cars: On a Road to Nowhere.
“The problems are almost too great to list, but my primary concerns are two-fold: technological and environmental,” he says. “There are huge worries about rushing into it, cutting corners which might result in accidents and deaths, as they already have.
“Then there’s a bigger issue: what is the positive outcome? I just don’t see it. People are not asking for it, it doesn’t solve problems such as congestion or pollution, yet huge amounts of money are going into it with almost no return.
“The technology can be hacked. There’s the risk of deskilling drivers with the adoption of more automated driving aids, then expecting them to take over in the event of an emergency. The more you look at the driverless vision, the more dystopian it appears.”
At this point, Wolmar casually mentions a host of other potential pitfalls concerning legality, privacy, practicality. You get the picture. He’s not a fan. Following this initial brutal attack on the foundation stones of the self-driving dream, he quickly covers off some popular retorts.
“The argument goes that driverless cars will help the blind and others who can’t drive, but logically this must mean more cars on the road and therefore more congestion,” he says. “The response is “ah, no, because there will be shared use”, but there’s no evidence that people want that. It isn’t a realistic concept, but even if we get there it will not be a good place.”
So why are governments, vehicle manufacturers and tech companies so obsessed with it? “The proponents of driverless have managed to create a climate in which the public and politicians think it is inevitable, but it isn’t,” he says.
“After 12 years of testing robotaxis in sunny climates on nice wide geofenced highways you still have to sign a nondisclosure agreement to get in one! The developers are driven by fear that someone else will make the technology work and become the market leader, but everything points to the fact that this is a technological dead end. Like Concorde, lots of great ideas have floundered.”
Finally, Wolmar relents briefly from his devastating critique. “There may be some limited uses such as airport transit,” he admits. “It’s a bit like the moon landing, some great technologies will come out of it. Indeed, if you speak to people at trade shows, a lot of them are very skeptical about driverless ever becoming a dominant technology. They already have successful businesses supplying cameras or software or lidar, and that’s where their interest lies.
“Outside of the industry, many think driverless cars are already available to buy. It is pure hype. They don’t exist. Headlines in the media claim driverless cars can do this or that, and then in paragraph five it says there’s a safety driver.
“You saw it with covid and the supposed benefits of driverless delivery. If anything, the impact of the pandemic on driverless was to completely undermine the shared use argument, which is vital to the business case. Coronavirus, and whatever comes after it, is as much a problem for shared use as it is for public transport.”
So, what’s Wolmar’s preferred solution? “The approach must be different for each town or city, but urban areas are not suitable for the unregulated use of private cars,” he says. “You have to recognise that road space is a limited asset, to do otherwise is bad economics. This is not a war on the motorist. There will be cars of the future, but cars in their proper place, particularly rural areas.”
Driverless Cars: On a Road to Nowhere second edition (2020)
2020 has been an epic year for Tesla. While virtually every other vehicle manufacturer continues to build petrol, diesel and hybrid cars, Elon Musk’s commitment to pure electric has paid off handsomely.
Back in February, the Model 3 was named UK Car of the Year. By July, a share price surge had made Tesla the world’s most valuable car company, worth a staggering $208bn, overtaking Toyota (on $203bn) and miles ahead of Volkswagen ($74bn), General Motors ($36bn) and Ford ($24bn).
Since 2016, with the introduction of the Autopilot Hardware 2 package, Tesla has made ever bolder claims about full self-driving. “It’s almost getting to a point where I can go from my house to work with no interventions,” boasted Musk this summer.
Such remarks have drawn stinging criticism. “Tesla has repeatedly rolled out crude beta features, some of which can put people’s safety at risk and shouldn’t be used anywhere but on a private test track,” said William Wallace, manager of safety policy for Washington-based Consumer Reports.
Not so long ago, rival carmakers were similarly dismissive of battery power. What they’d give to be as desirable as Tesla now!
Last week, as part of his 2020 annual shareholder meeting (and much-publicised #BatteryDay), Musk laid down an ambitious new marker: “I think probably like in about three years from now, we’re confident we can make a very competent, very compelling $25,000 electric vehicle that’s also fully autonomous,” he said.
Given how quickly they’ve revolutionised the industry, who’s to say Tesla won’t also win the race to driverless?
Whenever anyone spends a billion dollars in the self-driving world it is probably worthy of a mention here.
In this case, unmanned delivery vehicle specialist, Nuro, has been boosted by a US$940m investment from Japanese multinational, SoftBank.
Founded in 2016 by two former Google engineers, Dave Ferguson and Jiajun Zhu, Nuro operates mainly in San Francisco but plans to expand its delivery service to new areas, add new partners and expand its fleet.
“We’ve spent the last two and a half years building an amazing team, launching our first unmanned service, working with incredible partners and creating technology to fundamentally improve our daily lives,” said Ferguson.
“This partnership gives us the opportunity to take the next step in realizing our vision for local commerce and the broad application of our technology.”
Nuro’s other backers include Greylock Partners and Gaorong Capital.
