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An iterative method for traffic signal optimization based on message matrix gridding

A traffic signal and grid technology, applied in the field of intelligent transportation systems, can solve problems such as large amount of calculation, poor real-time performance of the method, and difficulty in applying the actual control system, so as to improve the optimization rate, speed up the convergence speed, and reduce the waiting time of vehicles Effect

Inactive Publication Date: 2019-03-12
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI +1
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Problems solved by technology

However, because some algorithms for simplifying the model cannot guarantee the optimal control parameters in large random situations, and complex control methods require a large amount of calculation, the real-time performance of the method is relatively low under the limitation of the existing computer computing capacity. Poor, it is difficult to apply to the actual control system

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  • An iterative method for traffic signal optimization based on message matrix gridding
  • An iterative method for traffic signal optimization based on message matrix gridding
  • An iterative method for traffic signal optimization based on message matrix gridding

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Embodiment Construction

[0044] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The size of the traffic network is N×M network, and only consider the optimal control of traffic flow in two directions from east to west and from north to south.

[0045] Such as figure 1 Shown is a schematic flow chart of the system of the present invention.

[0046] The step 1, according to the size of the traffic network is N * M, initialize the road length of the traffic network model, the road length distribution matrix between nodes in the network includes two groups of horizontal and vertical:

[0047]

[0048]

[0049] In the formula: △ E Represents the distribution of roads in the east-west direction; △ S Represents the distribution of roads in the north-south direction.

[0050] In the step 2, the data of the time of arrival of the traffic flow at the node and the length of the traffic flow are obtained by the microwave vehi...

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Abstract

The invention relates to a traffic signal optimization iteration method based on message matrix gridding. The method comprises the following steps of initializing a traffic network model related parameter matrix; initializing a traffic flow state matrix according to road traffic information obtained by a microwave vehicle detector and establishing a network node message function basis matrix; calculating a message function matrix of each iteration of this node; obtaining the message function matrix of the downstream node; calculating the optimal signal control quantity in the iteration; calculating the global optimization result; judging whether a system is stable; if the system is stable, stopping cyclic iteration; and otherwise, continuing the next cyclic iteration. The invention provides the signal optimization control method obtaining traffic flow information in real time in a traffic network and using the message function matrixes to realize stable optimization, rapid convergence and high real-time performance in a signal optimization iteration algorithm.

Description

technical field [0001] The invention relates to the field of intelligent traffic systems, in particular to an iterative method for traffic signal optimization based on message matrix gridding. Background technique [0002] In the urban traffic network system, the traffic capacity of the intersection directly affects the traffic capacity of the entire traffic network system. The quality of signal control at road intersections is of great significance to reduce vehicle delays and reduce the average road area occupied by road vehicles. [0003] Existing control systems, such as TRANSYT, SCOOT or SCATS, only optimize the green signal ratio, phase difference, phase and phase sequence independently, without considering the correlation between intersections, and it is difficult to ensure optimal network optimization parameter. Moreover, the transportation system is a nonlinear system with large randomness, and the system model is very complex. Scholars use different control metho...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/08
Inventor 杜劲松李东昇葛丽毕欣赵越南
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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