An Initial Model for Autonomous Trucks in Australia?

Updated with long distance vehicle announcements


A recent announcement in the United Kingdom has the government allocating 8.1 million pounds to a truck platooning trial:

Semi-automated truck convoys get green light for UK trials

Platooning is essentially like bicycle pelotons in road races like the Tour de France, where riders get sucked along in the slipstream. Until you have actually participated in one, you do not realise how much easier it is to ride in the group. I knew that intellectually, but the experience is something else. For trucks this means less congestion and less fuel use. In order to achieve these results the artificial intelligence and sensing systems that controls the trucks have to be much better than human drivers so that the trucks can drive closer together.  In the UK trial the speeds and steering will be controlled by the lead vehicle.

Total autonomy for vehicles on the road is known in the industry as Level 5 autonomy. This is where vehicles can control themselves in all road conditions. We are a long away from this technologically, so the trucks in the trials will have human drivers who can take the wheel at any time. The problem with this is that driver attention will naturally wane and this may impact on reaction time. In this trial this may be dealt with by periodic blocks of time where the human driver must take command of the truck – whether there is a need or not.

The medium term adoption pathway here in Australia may be different due to the road conditions and distances travelled. Here in Australia the situation for truck driving is a little different than the UK. There are much larger travel distances between the major cities, and the major inter-capital highways are less crowded. This is mirrored in the United States, especially in larger states such as Texas and California. This means that the adoption process of the technology may be significantly different.

There are a couple of technology issues in the adoption pathway that is chosen that flow into these sorts of differences and how we might choose to adopt the technologies.

Firstly there is a significant debate in the autonomous vehicle technology world about the approach of using maps versus continuous sensing. As humans we can navigate an unfamiliar terrain because our sensing and vision systems are good enough to recognise and continually process information at a level that is useful. The technology in autonomous vehicles is still not good enough to achieve that yet, and this is where mapping comes in. If an autonomous vehicle has stored in its system a map of the territory it is about to navigate, it only has to compare the environment it is encountering versus the map. This significantly reduces the job that needs to be done, reducing the pressure on the technology. In the long run it is likely that onboard vision and sense making systems will be good enough to do without maps. In the short term  having maps significantly improves performance. The timing of these changes, and the implications for strategic competitive advantage are critical when thinking about strategic decisions for individual companies, and what the overall outcomes might look like (see: Winner-takes all effects in autonomous cars for an excellent discussion on this).

Secondly, at what point will we be comfortable with no driver in the vehicle, and will this be at Level 4 or Level 5 autonomy. At Level 4 autonomy the vehicle can drive itself but is limited either by geography or conditions. This means that while the driver can be removed there needs to be some sort of geofencing, or emergency failsafe systems. For example trucks on the highway may automatically pull over if rain levels go beyond a certain level, affecting visibility. If adoption pathways can be achieved at level 4 rather than level 5 then adoption will occur more rapidly as the technology will not have to be as advanced to achieve the outcome.

So if we can build a model in a specific area of trucking where there are less complicated driving challenges, and mapping  makes a significant contribution we can create faster adoption. Which takes us back to the highways between capital cities in Australia.

In Australia 18-19% of total road freight movements are inter-capital freight movements (Truck Industry Fleet Report 2015), and there has been significant improvement in those roads over the last 20 years. For example once we get outside of the major urban areas of Melbourne and  Sydney the road between the two cities is excellent for trucks. An early adoption model for autonomous truck movements in Australia might start with transfers between Melbourne and Sydney and look like the following:

  1. Autonomous trucks operating the full distance between the two cities except for the last 30 kilometres (plus or minus) in each city.
  2. A truck changeover system on the outskirts of both cities where either the truck takes on a driver, or the prime mover is changed over to a non autonomous prime mover and driver. This is necessary in an early adoption model because the challenges of driving in the major cities are significantly higher than on the open highway.
  3. A cooperative mapping effort coordinated by the Federal Government where the road is mapped in its entirety.
  4. The formal mapping is supplemented by all autonomous trucks contributing their mapping and sensing data to a central system to continually update the maps. Therefore any new hazards or changes such as roadworks are rapidly incorporated into the maps that all autonomous trucks use.
  5. Autonomous truck support centres where the control of the truck can be taken over by a remote driver in the case of difficulties such as problems with sensors, or road conditions which are outside of specified parameters.

Many of the pieces of such an implementation pathway are already in place or soon will be. Autonomous trucks have been trialled in several locations around the world, and we already have remote control of mining systems (Mining industry looks towards a new wave of automation ,  Rio Tinto: rolling out the world’s first fully driverless mines ). We also have remote control of drones for military operations.

Around the world the trucking industry is seeing problems with an ageing workforce, with trucking jobs being seen as unattractive by younger generations (Wheels not in motion: Australia running short of truckies). A system as described above can solve some of this problem by:

  1. Autonomous trucks can operate for more hours than human drivers can, increasing efficiency of truck use and reducing overall demand for drivers.
  2. Increasing the attractiveness of trucking jobs. In many cases the long hours and time away from home are significant factors reducing the attractiveness of driving a truck. If the long distances can be handled by autonomous trucks, and the drivers can go home to their families at night then the job becomes more attractive.
  3. A truck driving job is more interesting, as the easy parts are taken over by autonomous trucks, and the more difficult driving conditions, unloading operations, and interactions with customers are covered by human drivers in short haul operations.

Eventually most trucking operations will be carried out by autonomous trucks If we want to address the shortage of current workers, reduce fuel consumption for long haul freight, and possibly reduce fatigue related accidents, a model which accelerates early adoption should be trialled.


Proterra has announced an 1100 mile (1772.2km) trip of its Catalyst Bus on a single charge. (Proterra Counters Tesla’s ‘Beast’ Of A Semi With 1,100-Mile Range Electric Bus). In addition Tesla will announce its new Semi truck in October. With distances between Melbourne and Sydney of approximately 865 km, Sydney to Brisbane of 928 km, and Melbourne to Adelaide of 725 km this seems to put the intercapital freight market in the sights of autonomous electric trucks.

I am writing a book on autonomous vehicles with Dr Chris Rice of the University of Texas Austin. It is called Rise of the Autobots: How Driverless Vehicles will Transform our Economies and our Communities. Stay tuned for more excerpts as we finalise the book.


Note: The featured image comes from: 











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