Bus intelligent scheduling method and device based on historical passenger flow big data

Abstract

The invention discloses a bus intelligent scheduling method and device based on historical passenger flow big data. The method comprises the following steps of: step 1, acquiring a bus company basic data set; step 2, acquiring historical passenger flow big data; step 3, processing the historical passenger flow big data; step 4, obtaining the time distribution characteristics of the passenger flow;step 5, obtaining a driving schedule; step 6, intelligently generating the schedule for the driving schedule; and step 7, outputting the automatically generated schedule. The bus intelligent scheduling method and device are closer to the law of passenger flow and meet the travel demand of the citizens. When there are more passenger flows, more capacity is arranged to ensure the service level, andafter the passenger flow is reduced, the capacity is reduced in time to save resources; the resource utilization efficiency and the degree of satisfaction for the bus travel by the citizens are improved, the operation cost of the vehicle operation company is reduced, the exhaust gas discharge of the vehicle and the consumption of electric power or fuel resources can be indirectly reduced, and theprocessing efficiency of traffic emergencies is optimized.

Description

technical field [0001] The invention relates to the field of intelligent transportation research, in particular to a bus scheduling method, in particular to a bus intelligent scheduling method and device based on historical passenger flow big data. Background technique [0002] The traditional bus operation planning and scheduling method in my country is mainly based on the experience of practitioners and historical operating conditions. With the rapid development of public transportation and the increase of public travel population, the previous bus scheduling can no longer meet the ever-changing bus travel needs. This not only affects the ride experience of passengers during the peak period, but also causes a lot of waste of resources during the off-peak period. Therefore, it is particularly important to provide a bus intelligent scheduling method based on historical passenger flow big data that is closer to the passenger flow pattern. Contents of the invention [0003] ...

AI Technical Summary

Problems solved by technology

[0002] The traditional bus operation planning and scheduling method in my country is mainly based on the experience of practitioners and historical operating conditions. With the rapid development of public transportation and the increase of public travel population, the previous bus scheduling can no longer meet the ever-changing bus travel needs. The typical mismatch of transport capacity and volume not only affects the riding experience of passengers during the peak period, but also causes a lot of waste of resources during the off-peak period

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