#Self-driving - Cars of the Future

AI and IoT expert Karim Jaser presents a resolute defence of the trolley problem.

Ethics in self-driving: The trolley problem strikes back

The trolley problem – the question of who to save, or kill, in no-win crash situations – continues to divide opinion like no other subject in the driverless world.

I must admit to flip-flopping on it myself. From being quite taken with it in 2018’s Autonomous now: the shift to self-driving, through 2019’s The driverless dilemma: touchstone or red herring?, to last month’s Self-driving experts across the world agree: the trolley problem is a nonsense.

That, I thought, was conclusion reached, the end of the matter. Far from it! In response to the latter article, Karim Jaser, Senior Product Manager specialising in artificial intelligence (AI) and internet of things (IoT) for blue chip companies, posted a resolute defence of the much-maligned thought experiment on our LinkedIn page.

“I do agree that humans don’t go through the trolley problem evaluation in the split decision second, however I also think not all experts agree it is a nonsense,” he said. “It is for society as a whole to discuss these ethical problems. From the point of view of self-driving technology, this can be solved in many ways, with probability theory and estimations on minimal loss, but it is not up to developers or self-driving experts alone to decide how to tackle the point. It needs the involvement of regulators, governments and the industry.”

Well, with our mission to encourage debate about all aspects of autonomous vehicles, how could we resist? We asked Karim if he’d be up for an interview. He kindly agreed and here we present his thoughtful and cohesive opinion.

KJ: “I was always fascinated by robot intelligence, so at university I studied telecommunication engineering. There were lots of exams on probability theory, system control, software engineering. I was also involved in coding in my spare time, and later did it as a job.

“Self-driving is a control problem first and foremost. There are elements of robotics, including perception state estimation and trajectory planning, but also software, hardware and AI working together.

“The interest grew stronger when I started studying machine learning and AI about four years ago. When I was at university in the 90s, AI was not really a popular subject. It was a topic I picked up later in my career. As a senior product manager at a high technology company, AI is everywhere now – it’s an essential part of the skills necessary to perform and innovate, from biometric scans and image recognition to automated travel.

“AI has a lot of potential to have a beneficial impact on society – fewer accidents, better mobility, less pollution, more autonomy for people with disabilities – but it doesn’t come without challenges, for example, cyber threats, and also ethical and regulatory issues, which is why I got involved on the trolley problem.”

“It’s not straightforward. If we take a step back, you we need to understand how self-driving cars take decisions. They’re using supervised learning, reinforcement learning, convolutional neural networks (CNN) and recurrent neural networks (RNN), deep learning for computer vision and prediction. Specifically, reinforcement and inverse reinforcement learning are very tightly linked to the way driverless vehicles behave through means of policies.

“Policies are related to the distribution of probabilities, but the trolley problem is an ethical choice, so I understand why a lot of people in the industry dismiss it. It’s not the way autonomous vehicles take decisions, going through philosophical considerations in a split second, so it might seem irrelevant, right? Like the Turing Test and Asimov’s Robot Rules, the trolley problem can be perceived as a distraction from more practical considerations.

“It can be distracting for two reasons: first, these considerations are corner cases – there are other priorities, more likely scenarios still to be addressed; second, autonomous vehicles will not be given ethical guidelines to link with probabilities.

“With regards to the first objection, as Patrick Lin (director of the Ethics and Emerging Sciences Group at California Polytechnic State University) has pointed out, it shouldn’t matter if these scenarios are impossible, because the job of these thought experiments is to force us to think more carefully about ethical priorities, not to simulate the realities.

“The second objection is related to self-driving cars taking decisions through distribution of probabilities. The actions of these vehicles are linked not to hard coding, but all statistical contextual information, and that makes each scenario difficult to interpret. You can potentially have millions of mini trolley problems in different contexts.

“The trolley problem is a reminder that corner cases and autonomous vehicle behaviours are not a technical irrelevance. This is an issue that belongs to society and should be discussed in the same way as other AI pitfalls like privacy and bias.

“Actually, the trolley problem is more related to the third pitfall of AI, replicability. When trying to understand why and how an autonomous vehicle takes a decision, it is important to note that most autonomous vehicle developers are taking ethical considerations into account.

“In 2017 in America, Apple commended the National Highway Traffic Safety Administration (NHTSA) for including ethical considerations in its Federal Automated Vehicles Policy. It even highlighted three particular areas: 1) the implications of algorithmic decisions for the safety, mobility and legality of automated vehicles and their occupants; 2) the challenge of ensuring privacy and security in the design of automated vehicles; and 3) the impact of automated vehicles on the public good, including their consequences for employment and public spaces.

“The automotive industry has also approached the issue of accidents caused by autonomous vehicles in relation to ethics. For example, Volvo stated in 2015 that it would take responsibility for all Volvo self-driving car accidents. This is an ethical decision, because it did so without regulation forcing it to do so.

“We will see what happens. If there are no ethical decisions by the industry, the regulators will step in. On a fun note, looking to the past, horses were not considered responsible for their actions, the rider was. Whereas in this case, responsibility for the autonomous vehicle will lie not with the owner but with the carmaker.

“So, to conclude, automakers and AV developers are taking ethical and regulatory matters into account, which underlines the importance of these discussions. We cannot just dismiss the trolley problem because it’s not the way an autonomous vehicle decides, or because it distracts from technical development.

“The way to deal with this is to discuss the implications in the right context, being aware of how autonomous vehicles are developed without scaring the public with sensationalist articles. The trolley problem might be perceived as a Terminator-style situation, and that’s where it gets on the nerves of a lot of people that are developing and testing AI. It’s not black and white, it’s a grey area, and that takes us to the path of discussions.

“The trolley problem forces us to consider ethics in vehicle development and confront the fact that ethical principles differ around the world, as documented by the Massachusetts Institute of Technology (MIT) simulation.

“Are we at the point where discussing the trolley problem should be a priority? I believe that would be beneficial to the success of the self-driving industry, guiding us in the thinking process of building the right mix of safeguards and transparency.”

CGA’s simulations train autonomous vehicles to deal with environments specific to the UK.

Self-driving and smart cities: stop wishcasting and get real with predictive simulation

Our Zenzic CAM Creator series continues with Liverpool-based Jon Wetherall, Managing Director of CGA Simulation, and Max Zadow, Director of Future Coders.

By applying gaming knowledge to real-world mobility questions, CGA has created engaging simulations to study autonomous driving and smart city solutions.

JW: “My background is gaming. I used to work for the company that did Wipeout and F1 games. We made a racing game called Space Ribbon and one day, about five years ago, we got a call from The Department for Transport (DfT). They were doing a research project on virtual reality (VR) in the testing and training of drivers, specifically hazard awareness.

“We turned it into a game and it worked – people said their attitudes changed as a result of our simulations. The hardest scenario came early in the game – a parked lorry with a big blind spot – and a lot of people crashed. VR feels so visceral, the experience can be quite vivid and shocking. Of course, smarter cars will hopefully fix these types of situations.”

To pursue this goal, CGA received a grant from Innovate UK to create an artificial learning environment for autonomous driving (ALEAD).

JW: “The aim was to make these cars safer and we stayed true to our computer game history. We didn’t have the resources to lidar scan the whole area, so we did our own thing using mapping data. We made a digital twin of Conwy in north Wales and unlike other simulations we kept all the ‘noise’ in – things like rain. This was important because it is now well-understood that noise is a big challenge for autonomous vehicles (AVs).

“Modern autonomous driving stacks have 20 different subsystems and we generally focus on only one or two, to do with perception. There’s been massive progress in this area over recent years, to the extent that artificial intelligence (AI) can identify an individual by their gait. What’s more, you can now do this on a computer you can put in a car – this is one of the cornerstones of driverless.

“It’s not the first time people have been excited about AI. In the 50s they were saying it was only a few years away. It has taken much longer than people thought, but major problems have now been solved.

“We are lucky to have one of the world’s leading experts in radar on our doorstep, Professor Jason Ralph of The University of Liverpool, and he helped us develop the simulation. You have to feed the car’s brain, a computer, all the information it will need – from sensors, cameras, GNSS – and you can do all that in the software.”

MZ: “In particular, The University of Liverpool were interested in how weather affects things, right down to different types of rain and mist. In California, if an AV encounters conditions it can’t handle, like heavy rain, it pulls to the side of the road. That’s ok for San Francisco but not for Manchester!

“A few years ago, everyone seemed to be using the example of an AV encountering a kangaroo. How would it cope? The point is you can use our simulations to train cars, to create algorithm antibodies for once in a lifetime events and regular things in different environments. That remains an essential part of what’s needed to make AVs a reality.

“We picked Conwy partly because it has very different patterns of land use to America. An early use case for AVs is predicted to be taxis, but in the UK these are most frequently used by people who don’t own their own car, and they often live in high density housing or narrow streets. The operational design domains (ODDs) are going to have to deal with environments specific to this country – steep hills, roads which twist and turn, and changeable weather.”

Mobility Mapper

Wetherall and Zadow’s latest collaboration is Mobility Mapper, a project to create greener and more intelligently designed transport hubs. The technology underpinning Mobility Mapper has been used previously by the team to model Covid 19 spread, autonomous vehicle technology and by the Liverpool 5G Create project (funded by DCMS as part of their 5G Testbeds and Trials Programme).

JW: “E-hubs are basically an extension of what used to be called transport hubs – train or bus stations. They’ll provide charging facilities and access to different modes of transport, for example, you can drop off an e-scooter and hop into a shared autonomous car.

“Here in Liverpool, there was a big trial of e-scooters, big in international terms not just UK. The worry was that a lot of them would end up in the canal, but that didn’t happen. The trial was incredibly successful. It’s all about linking that movement and nudging people away from car ownership.”

MZ: “We were already thinking about how Jon’s technology could be used for mobility as a service (MAAS) when we attended a virtual future transport conference in LA with the Centre for Connected and Autonomous Vehicles (CCAV).

“That was an influence, as was an Intelligent Transportation Systems (ITS) trade show in Copenhagen, where we saw an autonomous tram system designed to take bicycles. It was a small step from there to imagining autonomous trams carrying autonomous delivery pods.

“This is classic smart city stuff but you need to know how these e-hubs are likely to be used, with no track record, nothing to go on. We need simulated environments to make best guesses in. That’s Mobility Mapper.”

JW: “It is early days, still in the development phase, but the authorities in both Manchester and Liverpool have agreed there’s a need for such a predictive simulation tool.”

As we wrap-up a thoroughly enjoyable interview, Max dons his Director of Digital Creativity in Disability hat: “Autonomous delivery bots are basically electric wheelchairs without a person, so there’s clearly a potential benefit, but there needs to less wishcasting and more real work on how accessibility will be affected.”

For further info, visit CGAsimulation.com

The UK’s National Physical Laboratory is working on a framework for virtual sensor testing.

Developing test frameworks which build a bridge of trust to driverless cars in the UK

Our Zenzic CAM Creator series continues with Andre Burgess, digital sector strategy leader at the National Physical Laboratory (NPL).

NPL is the UK’s National Metrology Institute, responsible for developing and maintaining the national primary measurement standards. For over a century, it has worked to translate scientific expertise into economic prosperity, skilled employment and improved quality of life, covering everything from cancer treatments to quantum computing. In the self-driving sector, Andre Burgess’s focus is test frameworks to support the deployment of safe and reliable autonomous transport on land, sea and air.

Andre Burgess, digital sector strategy leader at NPL.

AB: “We’re all about measurement and how it can be applied to the autonomous vehicle space. Artificial intelligence (AI) and machine learning represents a great transformation. Whereas in the past we’ve developed tests for whether a human is fit to do something, in this new world we need a new set of tests to assure autonomous systems and build a bridge of trust. This is not a one-off test, it is ongoing work to develop new methodologies and support the development of new standards.

“One of the key things this country has developed is Testbed UK, a collaboration between government and industry which has delivered a formidable testing environment – a network of safe, highly controlled environments increasingly linked to virtual testing.

“Working with the Met Office on behalf of the Centre for Connected and Autonomous Vehicles (CCAV) over the last year we have focused on the usability and reliability of sensors in different weather conditions. How do you know if sensors are performing well? How do you validate the decision making? How do you apply metrics and KPIs to this? Having undertaken a proof of concept for a testing framework, we are confident this can be delivered and deployed throughout the industry.

“There is much talk about pass/fail tests but our focus is confidence, improving confidence in the outputs and building confidence in the system. We collaborate across the board, with regulators, testers, developers – engaging with them to understand their requirements. Our approach is to provide tools which help reduce the barriers to innovation without compromising regulation and safety assurance. Striking the right balance between reliability and usability is key. Our work will support validation and help the UK to influence international standards.

“The biggest transformation in road transport over the next decade will be emissions reduction and self-driving vehicles and smart mobility systems will be key drivers. It will require changes to infrastructure and changes in habits – batteries or hydrogen will be critical, perhaps a need to drive more slowly, maybe less private car ownership. The impact of Covid has led to a move away from trains and buses, so a resurgence of public transport is vital.

“In terms of self-driving, I envisage there will be personally driven vehicles and on-demand vehicles. Increasingly I expect we’ll see a transition into smaller public transport vehicles, perhaps for 8-10 people, in continuous use. There’s real value in getting to places that don’t have bus stops and there’ll be benefits from autonomous safety features too. It won’t be everywhere but I hope within 10 years there’ll be good examples of that in the UK. The question is will we be ahead or behind the curve? In some more authoritarian countries implementation might be faster but maybe not better.

“We’ll also start to see autonomous low level aviation and autonomous shipping, for example, short cargo sea freight. Combined, these things will make roads less congested. Key transport stakeholders have expressed the need to integrate, to pursue the most efficient way to get goods into and around the UK.

“For our part, we are focused on the framework for virtual sensor testing, and also integration between virtual and physical testing. To give an accurate level of confidence requires understanding the common metrics and the areas of uncertainty. The human factor is so important, for example, what about the people with cars that don’t have this tech – how do they respond?”

For further info visit www.npl.co.uk.

Autonomous vehicle software specialist set to become a major UK success story.

Oxbotica secures huge BP investment and targets anything that moves people or goods

Oxford University spin-out, Oxbotica, has been on our must-speak-to list for a while, and on Friday we got some Zoom time with the top people – CEO, Ozgur Tohumcu, and co-founder and CTO, Professor Paul Newman.

It’s three weeks since the autonomous vehicle software specialist announced a US$47m Series B investment led by bp ventures. Yes, that BP. The press release asserts that this will accelerate the deployment of Oxbotica’s platform “across multiple industries and key markets”, but Prof. Newman is quick to emphasise this is not about robotaxis, not even about cars.

Prof Paul Newman, Oxbotica co-founder and CTO.

“We’ve been deploying our software in industrial settings – mines, airports – for six years now, and not only in the UK, in Europe, North America, Australia,” he says. “Everyone talks about cars but all vehicles are game for us – anything that requires moving people or goods. That’s the advantage of being pure software.

“We’re a global business and raising this kind of money during a pandemic speaks volumes. We have clear water behind and blue sky ahead. Having these new investors and strategic partners will really allow us to drive home the opportunities that came last year. Vehicles are common but software of our standard is not. We’re showing that great IP can be generated everywhere, not just Silicon Valley, and that’s very refreshing.”

While Prof. Newman focuses on the vision, Tohumcu provides the detail. “Since the funding announcement, the exchange rate means it’s actually worth closer to $50m, so that’s not bad,” he says. “We’ve just conducted a review of the business and it was pleasing to see that we achieved exactly what we said we’d do two years ago – delivering results against measurable goals.

“We’ve done a lot of planning recently – some well-defined, other things we’re still making choices about. We’ve been approached by new companies interested in using our tech and there are exciting deals in the pipeline, deals that come with investment. We’ll be making further announcements over the coming weeks and months.”

Make no mistake, Oxbotica is set to become a major UK success story… just don’t mention driverless cars!

Humanising Autonomy uses behavioural psychology and computer algorithms to make cities safer for pedestrians and cyclists.

Using cameras and AI to protect vulnerable road users

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.”

For further info visit humanisingautonomy.com.

UK government sparks global business sharing transport sector data.

Sharing data collected by connected cars

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.

Why assuring machine learning is crucial to self-driving

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.”

For further info, visit www.york.ac.uk/assuring-autonomy

Creative technologist Ushigome on future vehicle-to-pedestrian (V2P) communications.

Self-driving news flash: flickering lights to replace eye contact in facilitating trust

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.

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 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.

For further info, visit Takram.com.

Vivacity Labs founder backs the citizen first vision of 21st century privacy.

Time for a grown-up conversation about cameras, AI, traffic flow and privacy

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.”

For further info, visit vivacitylabs.com.

Bold predictions about our driverless future by petrolhead Clem Robertson.

Meet the maverick radar expert of UK drones and driverless

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.

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!”

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.”

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.

For further info, visit the R4dar website.