Taxi passenger-carrying hotspot identification recommendation algorithm

Abstract

The invention discloses a taxi passenger-carrying hotspot identification recommendation algorithm. The algorithm is based on massive historical passenger taxi-taking travel data. Electronic fence contours of grids,honeycombs and cell types are constructed on an electronic map according to set parameters; big data mining is carried out on historical resident travel data; a passenger flow travel characteristic model on time and space latitudes is extracted. The method is different from a conventional statistical method. According to the invention,a computer graphics method is applied,firstly,theidea of segmenting the distribution of taxi order receiving points is adopted,then convex hull detection is carried out,and next,different Eps and MinPts are set for each region according to the area,so that reference is provided for parameter selection of a subsequent DBSCAN clustering algorithm,calculation is simplified,and the method can better aim at the situation of non-uniform density.

Description

technical field [0001] The invention belongs to the technical field of hotspot recommendation algorithms for public passenger vehicles, in particular to an algorithm for identifying and recommending hotspots for taxi passengers. Background technique [0002] With the rapid development of society, people's demand for travel is also increasing. Because of its convenience, taxis have become one of the means of transportation that people usually choose when traveling. In crowded areas, people usually encounter the problem of getting a taxi, but most of the taxis are empty for a long time because they cannot carry passengers. Congestion problem. The emergence of GPS trajectory data can provide new methods and ideas for solving these problems. Analyzing and mining taxi mobile GPS trajectory data can not only help understand the distribution of crowd gathering hotspots, but also extract and predict passenger hotspots more effectively. . Help taxi drivers pick up passengers more...

AI Technical Summary

Problems solved by technology

[0004] The present invention aims at the problem that the existing method for determining the hotspot area for getting on and off passengers in taxis cannot identify the specific taxi location and the shortcomings in the process of extracting hotspots for taxis, and provides a hotspot identification and recommendation algorithm suitable for taxis, which can By specifically identifying the location information of taxis’ pick-up and drop-off locations, we can determine the center of taxi pick-up and drop-off hotspots, assist taxi companies in reasonable vehicle scheduling, reduce the empty driving rate of taxis, and facilitate people’s travel

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