Abstract
In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs.
Highlights
Location selection has an important impact on such aspects as public facilities, maintenance service stations, logistics distribution centers, gas stations, charging stations, and so on
Based on the big data of the vehicle trajectory, this paper proposes a method for selecting theon location of data maintenance stations trajectory, by partitionthis and paper classification
Taking the big for seBased the big of the vehicle proposes a method data of vehicle trajectory as the demand point, the maintenance stations are divided into the lecting the location of maintenance stations by partition and classification
Summary
Location selection has an important impact on such aspects as public facilities, maintenance service stations, logistics distribution centers, gas stations, charging stations, and so on. Yang et al [7] conducted mining and analysis on electric vehicle travel modes and massive movement data to determine the locations of electric vehicle charging piles This method accurately locates the demand for electric vehicles and increases the accuracy of site selection. Wang et al [10] established an economic model and a location model by analyzing various factors that affect the location of a substation; this was based on a distributed design incorporating various data, such as remote sensing data and environmental factors, and using an analytic hierarchy process combined with big data analysis mode to design and select the sites of substations. Aiming at the problem of heavy-duty vehicle maintenance station location, this paper uses big data technology to collect and organize data and establish a twodimensional planning location model.
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