TY - JOUR
T1 - Usability and Perceived Efficiency of an Adaptive Route Optimization Solution for Commercial Vehicles
AU - Anghelache, Florian
AU - Goga, Nicolae
AU - Marian, Constantin Viorel
AU - Alexandru Mitrea, Dan
AU - Pavaloiu, Ionel Bujorel
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Adaptive algorithms
KW - adaptive systems
KW - path planning
KW - road traffic control
KW - roadmaps (technology planning)
KW - vehicle routing
UR - http://www.scopus.com/inward/record.url?scp=105003088664&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2025.3556891
DO - 10.1109/ACCESS.2025.3556891
M3 - Article
AN - SCOPUS:105003088664
SN - 2169-3536
VL - 13
SP - 61091
EP - 61108
JO - IEEE Access
JF - IEEE Access
ER -