This paper details the outcomes of a European scientific and development project aimed at developing a commercial solution for vehicle fleets, with a particular focus on assessing its usability and perceived efficiency. The solution is designed to enable businesses to optimize their routes in a more adaptive manner, taking into account a range of operational requirements, local conditions, and drivers’ expertise. The iRoute solution comprises a service for ingesting data from GPS devices, an integration layer connecting to end-customer applications, a route optimization engine, and two applications for web and mobile users. Unlike other approaches, this innovative solution leverages historical (well-known and familiar to drivers) route data to enhance, refine, and optimize routes. This approach ensures greater feasibility for drivers to follow these routes based on initial criteria such as time and distance. By incorporating historical track adjustments, we achieved up to a 20% improvement in the accuracy of executed routes, in terms of distance and time, compared to the planned route, outperforming standard optimization algorithms. This allows business owners to rely more confidently on the optimization results, providing a safer itinerary for their drivers. Due to lower incident rates on these known itineraries, the business will benefit from higher availability for their vehicle fleet and a decreased number of days in service which implies lower maintenance costs. The paper demonstrates the value of the proposed solution by statistically analyzing the feedback from dispatchers and business owners who used the iRoute solution.

This article presents the results and conclusions of a research and development project for creating a commercial solution for vehicle fleets that will help businesses to have more adaptive routes optimized to the way they are running their businesses, local conditions, and drivers’ knowledge, avoiding road hazards known by drivers that frequently use the road path. Our solution consists of a data ingestion service from GPS devices, an integration layer with the end-customer applications, a route optimization engine, and two end-user applications: web and mobile. The solution presented in this article differs from other approaches as it uses historical route data to better adjust and optimize the final routes so that the results are more likely to be executed by drivers according to the initial criteria and plan in terms of distance and time. By using an innovative way of adjusting the optimized routes considering historical tracks, we obtained good results with up to a 20% improvement in terms of real executed distance and time versus standard optimizing algorithms. That means the business owners can better rely on the optimization process results, having access to a more realistic optimization plan that their drivers can easily follow.