A Dispatch Strategy for Shared Bicycles Based on a Levels-of-Detail Model

As an important part of urban public transportation, the shared bicycles have played a positive role in relieving traffic congestion and promoting a low-carbon, environmentally friendly travel system. However, people often encounter difficulties with borrowing or returning a bicycle when tending to use shared bicycles, due to the uneven temporal and spatial distributions of the demands of borrowing and returning bicycles. Such difficulties sometimes make travelers give up using shared bicycles. In order to effectively improve the success rate of borrowing and returning bicycles, a dispatch strategy based on a levels-of-detail model is proposed. First, based on the similarity among bicycles stations, a spectral clustering algorithm is adopted to hierarchically classify the areas where stations locate. Thus, station clusters are formed based on station scopes (i.e., the geographic spatial area of a public station occupied). Second, the total demand of borrowing/returning bicycles among different station clusters at each level is counted, and a genetic algorithm is adopted to solve the transport route for dispatch vehicles. Third, the dispatch strategies at each level are overlaid to form a dispatch strategy for shared bicycles with the granularity from coarse to fine. Compared with the traditional methods, the proposed strategy reduces the total length of dispatch path by 42.70%, and therefore the corresponding dispatch time can also be shortened accordingly.