AI in Transport helps road transport companies in four areas. The first is route planning and vehicle load optimisation, where algorithms take into account orders, capacities, time windows and driver rest regulations, and find a combination that a dispatcher could not assemble manually. The second is document processing – data extraction from consignment notes, invoices and customs documents. The third is maintenance prediction based on vehicle data, which reduces the number of unplanned downtimes. The fourth is evaluation of driving style and fuel consumption. The benefit is measurable in kilometres saved and in the share of empty runs. The obstacle is usually the quality and fragmentation of data between dispatching, telematics and accounting, which needs to be resolved before deployment. The first step is therefore unifying the records of trips and orders, not purchasing a tool.
See also: AI in Logistics, AI and Company Data Quality, AI for Invoice Processing.
