Efficiency of routing and scheduling system for small and medium size enterprises utilizing vehicle location data

The routing and scheduling for trucks and vans in an urban road network depends critically on the state of the road network. Trucks and vans impose significant costs on other road users and the environment, so improved routing and scheduling benefits more than just the logistics industry. However, small and medium size enterprises (SMEs) in the logistics business cannot justify investment in planning systems. In this paper, an autonomous routing and scheduling system which is available to SMEs is proposed and the efficiency of the system is investigated. The proposed system accumulates vehicle location data in a central server and uses it to generate traffic information. Test simulations using a grid network demonstrate the effects of utilizing and sharing vehicle location data on delivery efficiency. The simulation results show that the improvement of delivery efficiency is mainly due to the reduction of penalty cost for early and late arrival at the customer location. It is also shown that the system leads to the buffer effect from variations in traffic conditions on delivery cost and this effect is enhanced by taking travel time uncertainty into consideration. It is further shown that the presence of measurement periods with insufficient data results in unreliable routing and scheduling. For a reliable system, data collection over a wider area is required rather than dense data in a subset of links.