Autonomous Platooning – Will it Change the World of Logistics?
Recently there has been growing discussion about the future of mobility, a big part of that discussion is focussed on the rise of the autonomous vehicle. The possibilities for the technology are vast, from improving road safety, decreasing carbon emissions to the overall reduction of vehicles on our roads. Alongside this it could also create a new business model for car ownership where no-one owns a car at all, but just uses Mobility as a Service (MaaS).
This piece will not be focussing on the consumer, but will be diving into another area that the autonomous vehicle has the potential to disrupt – the transportation and delivery of goods. Companies spend trillions of $’s every year transporting goods across their supply chain during the manufacturing process and then onto the final customer. One of the biggest costs within that process is the cost of human labour – in short the drivers of the vehicles. There are very strict conditions placed on long haul lorry drivers and for very good reason – humans have a limited concentration span and require sleep in order to be able to do a job properly. So, the vehicle spends a lot of time doing nothing whilst the human operator recharges his or her batteries.
Autonomous trucks have the possibility to change that, supporters of the technology say that by taking humans out of the process you will be able to save time and money and deliver products more efficiently. This is not all theory either as companies have started to put this into practice, albeit in very specific environments and not on public roads. Rio Tinto has been using autonomous vehicles at one of its mines in Australia for a number of years and back in 2015 reported that it had a cost reduction of 12% in comparison to using human operators.
But what is platooning I hear you ask?
For anyone that has visited Australia and gone into the outback you will have at some point come across a road train. 4-5 truck sized vehicles that are joined together and controlled by the driver at the front, they are very effective at transporting goods in straight (ish) lines over very long distances. This is a form of platooning and it is now something that is being tested out with autonomous trucks.
It will work in a similar way, the trucks will not be connected together physically, but will be connected wirelessly and will be programmed to follow the lead truck. At the moment the lead truck will be controlled by a human, but the long term aim would be to take the truck driver out of the process completely. The UK Government has just announced that they will be putting £8.1million into the trialling of electric autonomous platooning trucks, they believe that this technology will offer a decrease in emissions whilst also meaning less congestion on roads.
Tesla are reportedly in talks with the states of Nevada and California to see if they can test out their autonomous trucks in platoon format on public roads, although nothing official has been announced. This pilot test would interestingly not involve a human driver and would therefore be the first test of its kind. Up until now the testing of such technology has involved humans at the wheel, just in case something goes wrong. At some point though the human race will have to have to take the safety blanket away for us to realise all of the advantages of this technological advancement.
It all sounds too good to be true doesn’t it, but surely there is something that humans offer to truck driving that machines cannot?
The answer is of course yes. The human brain has evolved over millions (in fact billions) of years and is therefore able to react to a many different scenarios and situations. Felled trees, crashes, bad weather conditions, animals on the road or even mechanical problems with the vehicle. At this stage our ability to program vehicles to cope with all of these scenarios is slightly limited, but that is one reason that these pilot studies are needed in so that the technology can really develop. The rise of artificial intelligence and machine learning should in time be of assistance in overcoming these challenges in the year to come.
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