Choosing the fastest route for urban distribution based on big data of vehicle travel time
Kesheng Tang, Min Qian, Limei Duan · 2017
With the increase in the number of urban cars, the city's road congestion is getting heavier and heavier. Often, we choose the shortest path to reduce costs and improve efficiency during logistics distribution, but now, in order to improve timeliness, it is necessary to choose the fastest route to deliver because of traffic jams. This paper proposes a method to select the fastest route based on big data of vehicle travel time, replacing distance values with travel time values, by using the improved Floyd algorithm. The method can improve the efficiency of urban distribution and reduce the time cost, and has significant application value.