Multisource data-based customized bus route generation method

Abstract

The invention discloses a multisource data-based customized bus route generation method, and belongs to the technical field of public traffic information processing. The method comprises the followingsteps of: extracting a multisource data-based customized bus route demand; clustering and fusing a site; matching the demand with the site; constructing a customized bus route optimization model; designing a genetic operation-based heuristic method; and solving the model to obtain a customized bus route set. According to the method, bus IC cards, GPS data and novel internet data are combined to extract trip demands of passengers, and both the coverage rates of routes and an average trip time cost of the passengers are considered to construct the bus route optimization model and output a routescheme, so that a theoretical method is provided for practical planning of customized buses. Compared with the traditional investigation-based method, the method is capable of recognizing potential demands so as to extract customized bus trip demands to a greater extent. Results obtained through the method can provide decision support for the customization of practical customized bus routes and scheduling optimization of subsequent dispatching frequency, time tables and crew members.

Description

technical field [0001] The invention relates to the technical field of public transportation information processing, in particular to a method for generating customized bus routes based on multi-source data. Background technique [0002] With the continuous acceleration of urbanization and motorization in our country, the demand for urban traffic is growing rapidly, and traffic problems such as road traffic safety, congestion and environmental degradation are becoming more and more serious. Therefore, the "public transport priority" development strategy has become a consensus to deal with urban traffic problems. However, due to the unbalanced layout, organization and scheduling of my country's urban public transport network, residents' travel characteristics, road network structure, and space-time resource allocation of transportation facilities, the existing public transport system cannot meet the growing travel needs of residents. Under the prominent contradiction between...

AI Technical Summary

Problems solved by technology

Due to the fact that the current demand data collection method for customized public transport systems is relatively single, based on survey data in most cases, travel demand cannot be accurately captured, resulting in unreasonable line network planning, low coverage of open lines, and inability to meet the travel needs of residents. The attendance rate is not high, resulting in a waste of public resources

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