As much of South Africa’s transportation is still road-based, the country needs to ready itself to take advantage of the Fourth Industrial Revolution – doing so, will play a transformative role in future-proofing transportation in the country.
Transportation remains one of the most important sectors for its potential influence on most other industries and growth in the economy. As much of South Africa’s transportation is still road-based, the country needs to ready itself to take advantage of the Fourth Industrial Revolution – doing so, connectivity, data and analytics, and autonomous vehicles will play a transformative role in future-proofing transportation in the country beyond 2030.
“Effective implementation of the National Infrastructure Plan (NIP) should be considered in earnest that will see selected major infrastructure projects fast-tracked to get the backlog moving, which could help with increasing capacity in transport industries and, as a direct result, influence positive growth in the economy,” says Vishaal Lutchman, transport and infrastructure divisional director, WSP ∣ Parsons Brinckerhoff Africa. “Though it shouldn’t be thought of in isolation, but rather viewed as a starting point to get the country’s infrastructure and supporting networks ready for the technological advances we are seeing globally, and better enable the 5.5% GDP growth the country is said to be able to achieve with relative ease.”
In reality, 2030 is a medium-term planning timeframe for major infrastructure projects. “While it’s important to have this planning and set targets in place, we also need a long-term vision that encapsulates how people will live, work and play beyond 2030. This will enable us to design what the future demand of transport networks will be. If we look at the pervasiveness of mobile devices and the uptake of the Internet in the country as well, then the adoption of key technologies becomes crucial to this vision and its implementation,” adds Lutchman.
“The National Infrastructure Plan (NIP) will see selected major infrastructure projects fast-tracked to get the backlog moving, which could immensely help with increasing capacity in transport industries and, as a direct result, influence positive growth in the economy,” says Vishaal Lutchman, transport and infrastructure divisional director, WSP ∣ Parsons Brinckerhoff Africa. “Though it shouldn’t be thought of in isolation and it should be viewed as a starting point to get the country’s infrastructure and supporting networks up to scratch – to better enable and facilitate the 5.5% GDP growth the country is said to be able to achieve.”
In reality, 2030 is a medium-term planning timeframe for major infrastructure projects. “While it’s great to have this planning and set targets in place, what we really need is a long-term vision that encapsulates how people will live, work and play beyond 2030 – and thereby design what the future demand of transport networks will be. Also, if we look at the pervasiveness of mobile devices and the uptake of the Internet in the country, then the adoption of key technologies becomes crucial to this vision and its implementation,” adds Lutchman.
Grant Fraser, Product and Marketing Director at MiX Telematics (Africa) agrees: “Today, we live in a digitally connected society and the expectations of individuals and business, alike, is to remain connected. However, managing this usually requires mobile connectivity in the form of Wi-Fi, GSM, GPS and wireless technologies.”
In fact, according to Riaan Graham, sales director at Ruckus Wireless, sub-Saharan Africa; “Mobility goes hand-in-hand with travel and transport and the proliferation of mobile devices is certainly driving the adoption of wireless technologies – particularly Wi-Fi connectivity – in transportation. Whether it’s an individual, or a company transporting people or goods, there is a distinct desire and expectation from consumers, customers and business, alike, to be able to; communicate, do seamless and real-time route checking or planning for improved time management and productivity, manage safety and security from anywhere, as well as access certain application services while on route.”
Graham confirms that Wi-Fi is ideal to incorporate in transport planning. “It doesn’t require fixed infrastructure to establish, can handle offloading 3G/4G capacity – particularly in high user density areas – with reliable connections and ubiquitous coverage and, it can differentiate service and access by user and device. For instance, a bus can be transformed into a moving Wi-Fi hotspot, which will create great value for the passengers and become a unique selling point for the bus company. However, the potential of Wi-Fi in transport is not just about passengers – when with the amplification of the Internet of Things (IoT) – it can enable smarter lifestyles for everyone.”
“Passengers also need real-time access to schedules, gate and ticket information, maps and/or other guidance as they pass through the bus terminal. Wi-Fi not only provides an ideal method for these activities, it also provides a platform for new revenue generating services such as additional Wi-Fi access or 3G/4G offload, as well as support for bus terminal operational needs such as point-of-sale, digital signage and video security. From a commercial perspective, there is also a global trend for transportation cargo and fleet services to become more involved in value added activities such as cargo processing and logistics, which will require new processes, practices and technological advances around stock control and integration, as well as better wireless connectivity,” adds Graham.
This is particularly true when we consider the significant advances in telematics technology and the future of smart vehicles. Fraser says: “The combination of connectivity, IoT and on-board technologies continues to drive the use of Big Data, which now lies at the centre of telematics technology. While the on-board computer is still an important component, advances in IoT and analytics provides the opportunity to access much richer data about the vehicle, its movements, the driver, etc. – and being able to effectively utilise this data to provide added value.”
The proliferation of Big Data and IoT are certainly two of the most significant change agents that continue to shape the future of telematics, however, when converged with leading-edge thinking into connected and autonomous vehicles (AVs) we can recognise the potential to truly transform transportation in the country.
Lutchman adds: “Autonomous vehicles or AVs are coming. A number of countries are already investing in supporting infrastructure and undertaking successful case studies. South Africa has the most sophisticated networks of transport infrastructure on the continent, and with the right planning and investment into required supporting infrastructure for connectivity, we could be ready for AVs post 2030.”
Global research* undertaken by WSP ∣ Parsons Brinckerhoff in the UK, in association with Farrells, found that AVs have the potential to support a better quality of life, economic growth, health, safety and social connections. They offer convenient and safer mobility, regardless of the driver’s capabilities, and could also help to improve the way that existing spaces and route networks work.
“Imagine a connected network of vehicles on our major highway, freeway and city centre routes. Because the vehicles will be pre-programmed to abide by the laws of the road, and able to connect to and access the latest in GPS mapping and data from other sources, these vehicles will be safer, more sustainable and more efficient than the vehicles of today,” adds Lutchman.
The company’s research also shows that in time AVs will be able to move around without direct driver input to transport people and goods, on demand, from door-to-door using the most efficient routes. Added to this, road transport systems of the future will interact seamlessly with other transport systems, offering end-to-end journey connectivity and resilience.
“Having networks of automated vehicles capable of completing journeys safely and efficiently – in normally encountered traffic, road and weather conditions – could significantly reduce collisions caused by driver error on our roads. Sophisticated telematics will still have a key role to play in ensuring visibility and, in the future, to monitor what will be known as the ‘robo driver’ (which too can come with its own set of challenges). If we consider that road fatalities cost the country billions of Rands every year – with the majority being caused by irresponsible driver behaviour – this should certainly be motivation for the country to adapt to these sophisticated transport modes in the future. Telematics data will remain an invaluable source of real-time insights when automation is present,” says Fraser.
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.