Driving plan generation method and device

Abstract

The invention discloses a driving plan generation method and device. The method comprises the following steps: step 1, obtaining a historical passenger flow rule; step 2, generating a departure time table; step 3, generating a driving plan; the optimal departure interval can be determined through actual passenger flow prediction in combination with historical passenger flow rule big data by takingminimization of bus company cost and passenger waiting cost as a target, the timetable can be generated in combination with road standard prediction, and the shift number can be controlled by adjusting the target weight coefficient, so that the practicability of the timetable is improved. And finally, a reasonable guideboard can be quickly given by utilizing a scheduling algorithm (a 0-1 planningsolving model), the working hours of a driver can be controlled by increasing constraint conditions, the reasonable rest duration is ensured, and the feasibility of the guideboard is greatly improved.

Description

technical field [0001] The invention relates to the field of intelligent transportation research, especially the field of intelligent bus scheduling, and in particular to a method and device for generating a driving plan. Background technique [0002] With the rapid development of our society, people's living standards are improving day by day, and the scale of urban areas is also expanding, and public transportation is also vigorously developed. There are many forms of urban transportation, among which conventional buses are the most common means of transportation in the public transportation systems of major cities. On the one hand, at present, most urban bus departure timetables are generated manually based on manual experience, resulting in long waiting times for the public to travel, obvious phenomena of "stringing cars" and "big intervals", and serious bus congestion during peak hours , the phenomenon of empty buses during flat peak hours is common; therefore, it is pa...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of our society, people's living standards are improving day by day, and the scale of urban areas is also expanding, and public transportation is also vigorously developed. There are many forms of urban transportation, among which conventional buses are the most common means of transportation in the public transportation systems of major cities. On the one hand, at present, most urban bus departure timetables are generated manually based on manual experience, resulting in long waiting times for the public to travel, obvious phenomena of "stringing cars" and "big intervals", and serious bus congestion during peak hours , the phenomenon of empty buses during flat peak hours is common; therefore, it is particularly important to generate a departure schedule that fits the rules of passenger flow; on the other hand, bus companies artificially formulate passenger and vehicle allocation plans for the schedule, which often leads to overloading of some drivers , Some drivers are relatively idle, unable to take into account the driver's meal and rest time, so the generation of a scientific and reasonable driving plan is more important

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