Bus scheduling method based on big data

Abstract

The invention discloses a bus scheduling method based on big data. The bus scheduling method based on the big data comprises the following steps of obtaining current geographic locations of buses running in a bus route in the same direction from a starting station to a terminal station of the bus route at the current time, reading the predicted geographic locations of the buses at the current moment, and the like. The bus scheduling method based on the big data has the following effects: the problem of a huge error caused by determining a scheduling scheme only relying on the single positioning method of the prior art under a complex communication and electromagnetic environment is avoided, therefore, the positioning speed is improved, and the accuracy and stability of bus scheduling is improved; and when a standby scheduling scheme is started, the calculation speed is greatly improved through the combination of station acquisition and flow acquisition, therefore, the best scheduling scheme is identified quickly; and finally, the license plate number is found through the hash algorithm to locate a problem bus, and the calculation speed is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of big data, and in particular relates to a bus dispatching method based on big data. Background technique [0002] With the development of the economy, urban traffic is becoming more and more congested, especially when encountering travel peaks, due to traffic congestion, buses often cannot arrive on time, and passengers have to wait for a long time, which brings inconvenience to people's travel, and sometimes Because the road is too smooth and the bus speed is too fast, the number of cars in each section of the line is uneven. [0003] The existing dispatching method determines the current operating interval of each bus by obtaining the current geographic location of each bus corresponding to the target line, and performs dispatching and deployment according to the abnormal condition of the bus in each operating interval; or Before the departure of each bus, the dispatching system determines the initial d...

AI Technical Summary

Problems solved by technology

However, in the existing technology, due to the influence of complex communication and electromagnetic environment, the results of positioning and obtaining the geographical location of the bus are easily disturbed. For example, Didi and Uber often have such problems, which leads to relying on the existing single There is a large error result between the positioning method and the dispatching system, and the positioning speed is relatively slow. When starting the backup dispatching plan, it is often relatively random. The calculation speed cannot keep up with the real-time dispatching according to the road condition information, and the positioning problem of the bus Calculation speed is also slower

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