Passenger vehicle real-time scheduling method based on random opportunity constraints

Abstract

The invention provides a vehicle dynamic scheduling method applying opportunity constraint planning. The method includes the steps of adopting a Fisher ordered clustering analysis algorithm to divideall-day time into a plurality of sub-periods with equal departure intervals, establishing a model according to random system constraint conditions of passenger waiting time and vehicle capacity, checking the random system constraint conditions, calculating a target value in the model, and solving an optimal value based on a stochastic simulation genetic algorithm, thereby determining a multi-time-period real-time scheduling scheme. According to the opportunity constraint-based real-time scheduling model, an optimization objective function and constraint conditions of scheduling decisions underthe condition that uncertain events such as passenger flow randomness, accidents and congestion occur are solved, the optimal solution of the decisions is determined by adopting a genetic algorithm and random simulation, and the problems that an analytical solution of a traditional optimization algorithm such as a quasi-Newton method is difficult to express and is liable to fall into a local optimal solution are solved.

Description

technical field [0001] The invention relates to the technical field of transportation, in particular to a real-time dynamic scheduling method for passenger vehicles. Background technique [0002] The content of passenger vehicle scheduling includes passenger flow distribution technology, determination of departure frequency, selection of passenger vehicle capacity, and reasonable allocation of vehicles. This paper studies real-time dispatching, and does not study passenger flow distribution technology and passenger vehicle capacity. [0003] When dispatchers of passenger vehicle lines encounter problems that affect the normal implementation of the timetable, they must deal with them in a timely manner and adopt corresponding real-time dispatching methods to minimize the impact of sudden problems on line operation, so as to make up for possible problems. loss. Therefore, this requires the line dispatcher not only to understand the passenger flow dynamics of each time group ...

AI Technical Summary

Problems solved by technology

The real-time requirement of the dynamic scheduling algorithm is very large, but the real-time requirement is still one of the main obstacles that many methods are difficult to apply at present.

[0022] At the same time, frequent urban passenger services in urban traffic are vulnerable because even if the scheduled departure interval is fixed, the actual departure interval will vary greatly. In addition, various uncertainties, such as passenger arrival time, The number of arrivals, the departure time of vehicles, the speed and time of vehicles, as well as the traffic paralysis caused by major or general traffic accidents, and the interaction with other modes of transportation, etc., are the existence of these factors that make passenger vehicle services vulnerable

Once congestion occurs, the deviation from the scheduled timetable will expand on the passenger vehicle route, which will inevitably increase passenger waiting time and cause passenger dissatisfaction, which will increase the difficulty of passenger vehicle scheduling

Images