Simulated annealing algorithm based traffic demand estimation method

A simulated annealing algorithm and demand quantity technology, applied in computing, instrumentation, data processing applications, etc., can solve problems such as simple objective function, dependence on information, and large limitations of road network balance

Active Publication Date: 2016-04-13
TSINGHUA UNIV
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Problems solved by technology

As mentioned earlier, the objective function of linear programming and nonlinear programming methods is too simple, and the solution process is complex; the minimum entropy method relies on the mining of information; the road network balance method has great limitations

Method used

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  • Simulated annealing algorithm based traffic demand estimation method
  • Simulated annealing algorithm based traffic demand estimation method
  • Simulated annealing algorithm based traffic demand estimation method

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Experimental program
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Effect test

Embodiment

[0063] In the actual process, the OD information is obtained from the scattered vehicle terminals, so that we can iteratively calculate the confidence of the two kinds of information.

[0064] The specific operation process is: (1) use simulated annealing algorithm to obtain the optimal solution according to the initial seed; (2) obtain part of the information according to other information sources; (3) calculate the result according to the confidence level, and calculate the confidence degree of the two methods according to the actual result , to update the confidence level.

[0065] 1. Estimation of a single OD matrix

[0066] Assume that the demand level of the road network is known, that is, the average demand of each OD pair, as the initial seed (for example, in the program, the OD seed is set to be a matrix of 40 except for the diagonal elements). The simulation data randomly sets the OD pairs so that the mean value falls near this (for example, in the program, a random...

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Abstract

The invention discloses a simulated annealing algorithm based traffic demand estimation method, belonging to the technical field of dynamic traffic distribution in traffic guidance systems. The method involves two calculation modes of a target function and result evaluation. A specific operation process comprises: (1) obtaining an optimal solution by utilizing a simulated annealing algorithm according to an initial seed; (2) obtaining partial information according to other information sources; and (3) calculating a result according to a confidence level, calculating the degree of confidence of the two modes according to an actual result, and updating the confidence level. The method has the beneficial effects that in view of the fact that an actual road network runs dynamically, a traffic dispatcher always can obtain initial information through a dispersed vehicle-mounted device or priori knowledge, so that a continuously changed OD matrix is estimated.

Description

technical field [0001] The invention belongs to the technical field of dynamic traffic distribution in a traffic guidance system, and in particular relates to a method for estimating traffic demand based on a simulated annealing algorithm. Background technique [0002] In the traffic guidance system, optimizing the allocation of road network resources is the ultimate goal of the system. The calculation basis is the user's demand, that is, the total traffic flow from one node to another. [0003] For a city or a local road network, the total demand for traffic flow from each node to all other nodes is arranged to obtain a demand matrix, also known as the OD matrix of the road network. The OD matrix is ​​an unobservable quantity, while the observable quantity is the actual flow generated on the road section. In the same way, the road flow from each node to the surrounding nodes reachable in one step is arranged together to form a traffic matrix, which is called the F matrix ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/30
CPCG06Q10/04G06Q50/40
Inventor 胡坚明裴欣张似衡张毅谢旭东李力姚丹亚
Owner TSINGHUA UNIV
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