Method and system for realizing bus dynamic arrangement model based on OD passenger flow

Abstract

The invention provides a method and system for realizing a bus dynamic arrangement model based on OD passenger flown OD passenger flow-based bus dynamic scheduling model implementation method and system. The method comprises the steps of designing an initial scheduling model, screening the scheduling model, and outputting multiple optimal scheduling models for users to select. The scheduling situation of each day can be dynamically adjusted, the efficiency is maximized, and the enterprise cost is saved under the condition that the requirements of passengers are met. The method has the advantages that the types of basic data, set constraint conditions and the like are richer and more real, various dynamic basic data are contained, more actual factors and real-time conditions are considered,and the scheduling result with higher timeliness and accuracy is dynamically generated. Whether the scheduling model meets the actual situation or not can be verified in time and correspondingly adjusted by verifying whether the time period with the highest vehicle allocation number is in the morning peak or not, the accuracy of initial scheduling is improved, and the scheduling model which doesnot meet the actual situation is prevented from entering the subsequent adjustment and optimization process. A penalty function is introduced to better fit the actual situation of an enterprise, and abnormal data is prevented from interfering with screening of the optimal scheduling scheme.

Description

Technical field [0001] The present invention relates to the field of intelligent transportation technology, in particular, to a method and system for implementing a dynamic bus arrangement model based on OD passenger flow. Background technique [0002] With the rapid development of urban economy, the bus system is playing an increasingly important role in people's travel. In the case of limited bus resources, reasonable bus scheduling has become an urgent problem for bus companies. [0003] In the prior art, the traditional bus scheduling method is manual scheduling. Among them, manual scheduling is relatively fixed, usually updated once 1-3 months or longer, and there are only one or two schedules. For scheduling, the schedule can only be used as a reference, and the actual scheduling process is still based on experience. The scheduling relies on the scheduling timetable obtained from experience; human factors are large and cannot be dynamically changed according to passenger f...

AI Technical Summary

Problems solved by technology

The existing departure schedules generated based on algorithms and optimizations are mostly configured and calculated based on experience or historical data. The factors considered are single, and it is difficult to adjust dynamically according to changes, which leads to being out of reality, lacking rationality, and cannot truly reflect the bus operation of enterprises. Happening

Moreover, there is no systematic and reasonable evaluation method in the prior art to evaluate whether the scheduling results are reasonable, resulting in the existing automatic scheduling methods not conforming to the real operating conditions

[0005] Therefore, there is a lack of a scheme that can reasonably schedule buses according to real operating conditions

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