Usability and Perceived Efficiency of an Adaptive Route Optimization Solution for Commercial Vehicles

Florian Anghelache, Nicolae Goga, Constantin Viorel Marian*, Dan Alexandru Mitrea, Ionel Bujorel Pavaloiu

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

This paper details the outcome of a European scientific research and development project, funded to prototype a commercial solution for vehicle fleets. While current route optimization solutions have data sources such as real-time road traffic and weather conditions, our solution was developed to offer companies a proposed plan with adapted optimized routes, considering critical operational requirements, local conditions, and drivers’ driving experience. The iRoute solution consists of a module for receiving vehicle positions from GPS devices, an integration layer for end-customer applications, a route optimization engine, and applications for web and mobile users. Unlike other approaches, this innovative solution leverages historical, well-known, and familiar route data to enhance, refine, and adapt the optimized operational routes. This way, the drivers benefit from a more effective daily plan to follow based on business requirements such as locations, quantities, time, and distance. At the end of the day, adding these adjustments results in achieving 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. Also, due to lower incident rates on these known and preferred itineraries, the overall business will benefit from increased vehicle fleet availability and fewer days in service, with lower maintenance costs. The paper evaluates the usability and perceived efficiency value of the proposed solution by statistically analyzing feedback from dispatchers and business owners.

Original languageEnglish
Pages (from-to)61091-61108
Number of pages18
JournalIEEE Access
Volume13
DOIs
Publication statusPublished - 2025

Keywords

  • Adaptive algorithms
  • adaptive systems
  • path planning
  • road traffic control
  • roadmaps (technology planning)
  • vehicle routing

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