As we race to a future of self-driving cars, many argue it won’t happen in South Africa. But, writes ARTHUR GOLDSTUCK, it’s already here.
The future of the automobile is here. You only need look in your rear-view mirror. There’s a good chance that one of those cars you see is an Audi or a Subaru or a Ford or a BMW that has an assisted driving feature activated.
That means, on a current Audi A5, a “lane assist” feature that alerts drivers when they are veering over lane demarcations, “active lane assist” that steers the vehicle back into a lane when it detects the car moving over the lines, and “side assist” that detects vehicles coming up in the next lane when the driver signals a lane change – even forcing the car back into its own lane.
In the new Land Rover Discovery, an Autonomous Emergency Braking system spots potential collisions and applies brakes automatically if an accident is anticipated. It has a form of self-driving as well, with an off-road feature called All-Terrain Progress Control, which allows the driver to hand control over to the vehicle when the terrain is particularly difficult. The driver steers while the ATPC takes over all other functions, including braking, applying torque to the wheels, individually, for maximum traction, and controlling the speed.
In the Subaru XV, EyeSight Driver Assist Technology comprises two colour cameras positioned near the rear-view mirror. They monitor traffic movement, and feed the information to an artificial intelligence systems that fine tunes cruise control automatically and keeps an eye on unintended lane changes. It also features Pre-Collision Braking, in effect watching for cars that brake suddenly in front or – that perennial South African road hazard – cars cutting in dangerously.
The new Ford Fusion features the whole bang-shoot of automated safety, from Adapative Cruise Control that slows the car if it detects traffic ahead, to automated perpendicular parking and park-out assist for getting out of tight spots. Cross-Traffic Alert is like having a built-in assistant to warn of approaching traffic when a car is backing out of a driveway or parking spot.
The cherry on top is Pre-Collision Assist with Pedestrian Detection, which warns of potential collisions with both cars and pedestrians. The brakes instantly “precharge” and increase sensitivity for full responsiveness when the brakes are applied – which happens automatically if the driver doesn’t respond to the alarm.
The Volvo CX90 features all of the above, along with City Safety, designed to avoid collisions in slow-moving, stop-and-go city traffic. It brakes automatically, avoiding or helping to reduce the effects of a collision.
Every one of the above is a car I’ve tested on the South African roads. In the automobile industry, science fiction is not fiction anymore.
It’s not a great leap for such features to evolve to fully automated driving as well. The big catch, aside from the law, is that none of them are cheap, and none are aimed at the mass market. Yet.
In cars, future shock is no longer about how much of driving can be automated. It’s about how much of that automation can be built into mass-market cars.
The biggest shock comes when the high-end features like reverse cameras suddenly appear in entry-level cars. The nippy little Ford Fiesta ST2000 may not be a beginner car, but it points the way. It already features rear-view colour cameras for safer reversing, and AvanceTrac, which automatically applies brakes and adjusts engine torque when it detects wheelslip.
The true breakthrough, for the ordinary driver, will come when standard features in all cars include lane-assist and park-assist, as well as the predictive braking systems appearing in the high-end vehicles. That will gradually prepare drivers for their next upgrade: the self-driving vehicle, or at least a significant turn of the wheel closer to that dream.
Laws will have to evolve to allow for many of these changes, but that is already beginning, says Trevor Hill, Head of Audi South Africa.
“Germany will soon change its legislation, then the USA, probably in parallel, and then the rest of the world will follow,” he says. “But you have to have infrastructure, you have to have lines in the road. In Polokwane right now, an autonomous vehicle would end up in the bush. The sensors in the car will need to read the road markings, as well the traffic.
“But this will all happen in time. Once we get this technology into South Africa, we can start to explain to authorities what the benefits are. This will save lives. If you could put the current predictive braking features on trucks and taxis, you would save a lot of lives. But then everyone has to do it, because if one car brakes suddenly and others don’t, you have a problem.
“There are real safety benefits, though. Once costs come down and it becomes standard, most cars will get it. The technology is there; you just have to put it in the cars.”
The current Audi A5, already on South African roads, is a car of the future, available today, and does not need any change in law to be allowed on the roads. Like the Land Rover Discovery and Ford Fusion, it can detect a collision about to happen, with a technology called “pre sense”, which applies brakes automatically. That is just the beginning.
The new Audi A8, revealed in Barcelona a few months ago and due to arrive in South Africa next year, has built in numerous new features that also improve both autonomy and safety, without flouting any laws.
It features a parking space finder, similar to that of the Ford Fusion, which scans for open parking spaces. Chances are that the next model will drive itself to and from parking spaces after it drops you off at the front door of a building. It’s safety features are right out of the future.
“If the car is about to be hit from the side, it will first try to avoid accident. But, if it is unavoidable, the side of the car lifts 8cm so that it exposes the underside of car and distributes the impact, protecting passengers from the direct impact. An artificial intelligence active suspension means electronic actuators on the wheels smooths out potholes, bumps, and rough surfaces.”
It’s not only about safety and comfort, however. Hill presents a fascinating vision for the role of the self-driving car: “With autonomous driving, we want to create a 25th hour for the customer. The hour spent driving can become productive time in the car, in effect giving you an extra hour to get things done.”
The promised delivery date for autonomous vehicles, from most manufacturers, is 2021. It cannot come a day too soon.
- Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube.
Project Bloodhound saved
The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.
Two weeks ago, and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.
“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.
“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”
Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.
“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.
“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”
The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.
The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”
Motor Racing meets Machine Learning
The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK
The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.
Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.
Now there’s a new name to add to the roster of technology giants driving the future.
Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com, last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.
AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.
But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.
AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.
Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.
As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.
“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.
“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”
Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information.
During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.
This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.
“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.