iRoute—An Adaptive Route Planning Solution for Commercial Vehicle Fleets

Abstract

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.

Keywords

• adaptive route planning solution
• historical track data
• vehicle fleets
• real-world execution