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Scheduling method of networked vehicle system

A scheduling method and network technology, applied in transmission systems, data processing applications, marketing, etc., can solve problems such as supply and demand imbalances between service parties, achieve high income, increase income, and increase order response rates

Pending Publication Date: 2022-07-22
BEIJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the technical problem that the existing networked vehicle system does not jointly consider pricing and scheduling, resulting in an imbalance between the supply and demand of both parties, the present invention provides a scheduling method for the networked vehicle system, and at the same time improves the order response rate and The benefit of the service party and reduce the waiting time of the service object

Method used

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  • Scheduling method of networked vehicle system
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  • Scheduling method of networked vehicle system

Examples

Experimental program
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Embodiment

[0142] The scheduling method of the connected vehicle system is specifically:

[0143] In step S11, the supply and demand information in the area is acquired.

[0144] Divide the city into M non-overlapping hexagonal regions, that is, Z={Z 1 ,...,Z M }; where the area range of each area includes the current area and adjacent areas. Divide each day into T time slots, ie T={1,...,T}. Statistics for each zone z in time slot t i The number of service providers and service objects is recorded as and as supply and demand information;

[0145] Step S12, input the supply and demand information into the trained neural network, and output the pricing strategy and value of each region, specifically:

[0146] Step 1, input the supply and demand information in a region into the trained neural network, and output the pricing factor and its value of the region; wherein, the pricing factor is a discrete multiplier factor in a given interval;

[0147] Step 2: Select the pricing facto...

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Abstract

The invention discloses a scheduling method of a network connection vehicle system, and belongs to the field of intelligent traffic. The method specifically comprises the following steps: firstly, acquiring the number of service parties and service objects of a to-be-scheduled region and an adjacent region in real time as supply and demand information for the current moment; then, inputting supply and demand information into the trained neural network, and outputting value estimation values of all pricing factors in each region; a unique pricing factor is selected for each region by using an epsilon-greedy strategy; and finally, inputting the number of the service objects in each region and the unique pricing factor into an adjustment function, calculating the number of the service objects accepting pricing in each region, and randomly selecting the same number of service parties for service. Meanwhile, the remaining service parties which do not accept pricing in each region are input into the learned network flow scheduling model, and a scheduling strategy for each service party is output and executed; according to the method, constraints of multiple aspects such as scheduling cost, unloaded driving time, space-time pricing and supply and demand balance are considered, and revenue maximization of the service party is realized.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, in particular to a scheduling method of a networked vehicle system. Background technique [0002] Vehicle wireless communication technology (Vehicle-to-Everything, V2X) is a new generation of communication technology that connects vehicles with things, where V represents the vehicle (service party), and X represents any object that interacts with the vehicle, including vehicles, people and network. V2X organically links the elements of traffic participation, which not only supports vehicles to obtain more perceptual information than bicycles, but also helps to build an intelligent networked system, which can improve traffic efficiency, save resources, reduce pollution, and reduce accident rates. As well as improving traffic management is of great significance. [0003] However, a major obstacle to the connected car system is the imbalance of supply and demand in time and space; for exa...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q30/02G06Q50/30H04L67/12
CPCG06Q10/06315G06Q10/06312G06Q30/0283H04L67/12G06Q50/40
Inventor 王强刘天骄徐琛
Owner BEIJING UNIV OF POSTS & TELECOMM
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