The Algorithm People continues to drive efficiency improvements for clients, while mapping the route to carbon zero. TAP’s current R&D efforts harness the formidable brain power of AI to take road transport beyond efficient scheduling into holistic fleet optimisation at the click of a button.
The Algorithm People’s (TAP’s) CEO Colin Ferguson says the question is no longer whether operators can afford optimisation, it’s whether they can afford to be without it. His view of the future – and the AI TAP is developing – takes us beyond current optimisation capabilities and beyond traditional fleet management. And beyond that rainbow, he says, there’s definitely gold for road transport operators.
The Algorithm People (TAP) is well established with its pay as you go optimisation product, My Transport Planner. Its no muss, no fuss cloud-based platform can do in a couple of minutes what an experienced transport planner might stress over for a number of hours – and do it more efficiently.
“The time’s coming when anyone running vehicles will have to optimise them,” says CEO Colin Ferguson. “The savings on fuel, the increase in productivity and the reduction in the number of vehicles needed speak for themselves commercially. But it’s also a vital first step in the decarbonisation journey that all operators have to take.”
Optimisation in final mile or van fleets can produce fuel savings of up to 20%. To put that in a decarbonisation context, a 500-strong facilities management fleet could be saving more carbon through optimisation than if it exchanged 80 ICE vehicles for electric – with none of the cost.
Although HGV fleets tend to still rely on the experienced transport planner, their fuel bills are so high and the availability of alternative powered vehicles so limited, that exploring optimisation is a no-brainer.
“Optimisation is available today for all HGV fleets, where commercially and operationally, viable electric vehicles are still being fully developed,” says Ferguson. “Making your existing fleet as efficient and productive as possible now, is a necessary first step to decarbonisation – but in the long run it will be essential to commercial survival.”
Changing market
While parcel fleets and service LCV fleets have quickly seen the benefits of optimisation, haulage has typically been more reluctant, even for urban delivery. However, the high costs and lengthy implementation periods are a thing of the past. MTP offers a pay-as-you-go model which can be used by anyone who has the skills to shop on Amazon.
Ferguson says the marketplace is shifting, and TAP has seen this in very practical ways through the wave of interest from suppliers to the fleet industry.
Recently it has signed deals with the Fuel Card Services, and with FORS (Fleet Operator Recognition Scheme), which has rebranded My Transport Planner to sell into accredited fleets.
“FORS can see the value of optimisation and recognise that their customers and members will need to access tools like this for cost control, decarbonisation and competitive advantage,” says Ferguson.
My Transport Planner uses machine learning in order to become better at solving multi-vehicle routeing with each use. The more data it accepts, the better it understands the effect of different factors upon success, and it can also compare its plans with actual fleet performance, using the discrepancies to refine its approach.
TAP has also been involved with an Innovate UK-funded Knowledge Transfer Partnership with Teesside University, to bring a more innovative product to commercial reality. Mobile and Transient Hubs solves the problem of low payload in electric vans and micro vehicles, by dynamically optimising their movements in synch with a mobile Hub –a much larger vehicle which can reload them in the field.
Akin to in-flight refuelling for the aviation industry, this not only makes many electric micro vehicles viable for the parcels sector, but could also allow 3.5 tonne e-LCVs to run back and forth through Clean Air and Zero Emission Zones delivering pallets and reloading from an 18-tonner which can stay on the edges of the city. The vans would no longer have to waste range travelling between the depot and their delivery zone, but can be almost constantly productive.
TAP’s head of R&D Dr Ross Conroy, a specialist in artificial intelligence and machine learning, is currently working on a ‘super algorithm’ which will be able to determine which AI technique – or specific algorithm – will be best to solve any specific problem a fleet operator presents to it.
One of the issues with optimisation is that most products do not use AI – their approach applies basic rules to the data and identifies a viable solution. However, you cannot apply the same rules to urban multi-drop as to national trunking or primary distribution. So the products themselves are essentially optimised for a single type of solution.
“Our approach isn’t simply producing better results than a human can. We’ve already established this, and the technology is proven,” says Ferguson. “Our approach is considerably ahead of our competitors, both in terms of the savings and efficiencies we generate, and its potential.
“Traditional approaches are bottom up and iterative, where operators have to do, or pay for, extensive modelling, and resetting of parameters to get a good outcome. They are essentially having to feed in new and repetitive data, depending on the use case.
“What we’re doing is top down, where you set your business objectives, and parameters and the software will give you a good outcome very quickly without you having to worry about any of that,” he says.
It’s a game-changer, according to Ferguson. “You get better, faster results, with none of the time-intensive iterations or costly scenario modelling. It’s no longer necessary,” he says.
The super algorithm will enable TAP to encase all its algorithms for logistics applications, including Mobile and Transient Hubs, into one software suite, with the super algorithm choosing the best ‘solver’ for the data presented.
“We can bring all our technology and all our learning together in one comprehensive and intelligent package, which will think and learn,” says Ferguson.
This will mean that operators can feed all of their contracts and data into the AI super-solver and it will not only be able to optimise them all with the correct mathematics, but it could also suggest further efficiencies about how fleet vehicles are deployed across contracts, potentially over-turning years of established practice.
It becomes, says Ferguson, a holistic approach which optimises not just selected jobs or contracts but the entire operation. “It will be practical, it will still be easy to use, you can still drag ‘n’ droptimise – but the savings it unleashes will be beyond standard optimisation,” he adds. The super algorithm will be commercially ready in Q1 2023.
Foundations for growth
The Algorithm People has finalised its fourth funding round, having already developed its core optimisation product, My Transport Planner, and scaled up its operation to national coverage. This round of seven figure funding will help it further develop the super solver.
And Ferguson’s plans go further. They are already rolling out product for key customers in Belgium and France, with the US also planned, and he intends to build on these international sales.
The tech is also destined for greater things. The current Knowledge Transfer Partnership (KTP) which has helped to develop the MATHs product ends in April 2023. TAP is applying for a follow on KTP, again with Innovate funding, in order to develop its API version of the super solver.
Its ultimate goal is to produce a product which can take a top-down approach to all of a fleet operator’s systems. “This isn’t simply about integrating disparate data sources and jamming them together. This is about looking at all of that data from above and seeing the patterns of usage and the correlations which would otherwise never be found, and uncovering actionable, money-saving or money-making truths from that,” says Ferguson.
The road transport industry is at the edge of huge change, commercially, operationally and in terms of future roads and environmental policy. “Our super solver and the API version are designed to future-proof fleet operations as today’s knowns dissolve into tomorrow’s uncertainties. The industry will need all this intelligence to create tomorrow’s solutions.”
