Road safety is a priority for everyone, well beyond the statistics:
- Almost 1.3 million people are killed in road accidents each year – that’s an average of 3,287 deaths every day
- Almost 50-60 million people are injured or disabled in road accidents every year.
Yet whenever autonomous (or ‘driverless’) vehicles have grabbed headlines over the last few years the mainstream media has mainly focused on personal cars, rather than organisations’ fleets of vehicles. The sentiment in this type of coverage is mainly down to simple human feelings:
- Humans feel fine with a computer helping them navigate and even drive some or most of the journey, as long as the human stays in charge – and as long as the human can easily take over the controls at any second
- Humans may feel threatened by autonomous vehicles that could take jobs away from people
Massive change is imminent: convoys of autonomous and semi-autonomous heavy vehicles have already safely performed long haul jobs and thus not only challenged the status quo in the transport industry, but also challenged law makers.
The most famous street-legal heavy transport is The Freightliner Inspiration Truck from Daimler North America, which has driven on open roads in Nevada. But it wasn’t allowed to travel alone: it had to have a qualified driver on board at all times; and while that human checked emails, watched videos and made a big show of being relaxed the truck motored along using smart navigation gear.
“The human brain is still the best computer money can buy,” said Martin Daum, CEO of Daimler Trucks North America (DTNA) at a test run of the Freightliner Inspiration in May 2015, while emphasising to media that the truck is not a driverless vehicle. Instead he explained it’s “designed to create the best possible experience for drivers, and to be the driver’s partner on the road,” and that DTNA has no plans for a fully driverless truck.
The US Army has also tested seven-vehicle-strong convoy formation driving (or ‘platooning’) scenarios though in much more controlled conditions. As soon as lawmakers come to terms with the technology, road users could see many more convoys of vehicles platooning because they promise to be extraordinarily efficient:
- Computer-controlled slip streaming can ensure the optimum distance between vehicles to reduce drag on following vehicles (in effect, a mega road train), which means they use less fuel
- Improving fuel efficiency can mean that each vehicle has reduced emissions
- Vehicles travelling in platoon could transport larger loads more efficiently, which could drive cost and productivity improvements for fleets overall
In the short term, while Governments work out how to legislate for them on public roads, more automated vehicles will be rolled out for haulage on private or segregated transport routes, such as at mining sites or on bus runs.
Still, there are several other exciting technologies that could shape the future of fleet management – and many of them will have their own special artificial intelligences.
Future Fleet trend #1: connected traffic
The machine-to-machine (M2M) technologies that help fleet managers monitor the location, performance and safety of their fleets of vehicles will play an important role in smart traffic management too, sharing data with traffic control systems along their routes to help ease congestion and alert trailing vehicles to hazards.
Current M2M technologies work well with close-to-real-time data updates. As more vehicles are fitted with these monitoring systems and broader, data rich applications become available, there will be a lot more demand for mobile data access at near-real-time speeds – and often in significantly remote locations. This opens up greater opportunities for existing and new technology and network operators, and users alike, to innovate to deliver pioneering, competitively advantages systems and processes.
Future Fleet trend #2: scanning the road in 3D
Accurately scanning the world around a vehicle and determining how and where it fits has become a lot easier with depth-sensing 3D camera technologies such as those found in Intel RealSense, PrimeSense (bought by Apple) and Google Project Tango.
Now that the 3D cameras are small enough to fit into devices the size of smartphones, they’re becoming a viable and affordable replacement for older proximity-sensor kits currently built-in or retrofitted to vehicles to help detect potential hazards.
More accurate depth-perception means that the artificial intelligence responsible for keeping a vehicle safe could also be tasked with warning less-alert vehicles and even pedestrians nearby of danger.
Google recently filed a patent for an external alert system fitted to a self-driving vehicle that scans its surrounds for pedestrians and notifies them of the vehicle’s intentions. Most of the technology (apart from the robot driver) could be retrofitted to other vehicles too, including electronic screens, audio speakers and a robotic arm for signalling to humans close by.
Nissan wants to popularise a similar (albeit simpler) display system, which it recently mounted inside the windscreen of its IDS Concept vehicle. The well-mannered AI communicates to cyclists and pedestrians nearby to reassure them that it has spotted them, and even politely says things such as “After you: it’s safe to cross” if it has stopped and wants a person to cross in front of it first before moving again.
Finally, ScanLab has created a beautiful 3D drive-through of the streets of London using its 3D laser scanners to show what roads look like to these artificial eyes.
Future Fleet trend #3: human alertness
Major marques, such as Volvo, Volkswagen and Ford have helped popularise hazard scanning systems in their recent models, mainly using proximity systems and steering monitoring.
The promiximity systems in new models combine distance sensors and small cameras to help drivers reverse or see into blind spots, and some include sensors to detect sudden lane changes; while steering monitoring systems use simple gyros to track sudden or wobbly steering wheel movements that could indicate the driver is distracted or has fallen asleep.
Australian technology companies such as SmartCap and Seeing Machines are among the best in the world committed to improving driver safety by monitoring eye blink, brain waves and head movement.
Both systems relay reports to fleet operators, keeping them in the loop on how their drivers are travelling.
SmartCap measures a driver’s brain waves to predict microsleeps then triggers alerts in risk situations: “The operations around the world that are using SmartCap have, with over a million hours of use, effectively eliminated fatigue incidents from their business,” explained Dan Bongers, co-creator of the SmartCap in a July 2015 interview with the AFR. “A measurement of your ability to resist sleep is put on a scale for you to respond to. That [information] can be fused with other information, such as positions on the road, to learn about other factors that influence fatigue like road design. Hopefully people with this information can do something about it to prepare better for work.”
Seeing Machines tracks the movement of a person’s eyes, face and head to analyse alertness (or distraction), triggers alerts when risks are identified and can record what happens inside and outside the vehicle on every journey.
“Our customers are consistently being surprised by the results of our assessments because it’s the first time they’ve been able to objectively see the risks of fatigue and distraction to their organisations and their drivers,” noted Paul Angelatos, CEO of Seeing Machines in his report to investors in February 2016.
He also reported that demand for road-recording cameras has seen exponential growth in the last 24 months in commercial fleet and mass automotive markets as more “motorists and businesses alike seeking the reassurance of an ‘objective source of truth’ in the event of an accident”.
Again, face or head-reading technology is becoming increasingly miniaturised and will cross over from industry-only technology to every day devices in the mainstream: Intel is researching technologies for tracking ‘user liveliness’ via eye reflections; and Samsung has patented a face tracking feature for smartphones that changes how the device operates based on the angle of the user’s face and position of the eyes. If face-tracking becomes normalised, these technologies could quickly be adopted by other road users too.
For now, the transport industry is working on solving the present day multitasking challenge for human drivers in (increasingly) smart vehicles. Is working on the move all about hands-free?Read the report