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Genetic-algorithm-optimization-based big data analysis system and method of urban regional traffic

A technology of urban area and genetic algorithm, which is applied in the field of urban smart transportation, can solve problems that restrict the application and development of models, complex models, and large amounts of calculations

Active Publication Date: 2018-08-31
TERMINUSBEIJING TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
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Problems solved by technology

Countries all over the world have invested a lot of research in the effective management of traffic flow, trying to apply the latest research results of natural science and engineering technology to solve the increasingly serious traffic problems. Specifically, a lot of research has been done on urban traffic analysis and optimization control, but due to Due to the complexity, randomness, and nonlinearity of urban traffic itself, the optimal control model for traffic analysis is often very complex. There are many algorithms for solving the optimal control model of traffic signals. The performance index falls into a local minimum, which seriously restricts the application and development of the model

Method used

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  • Genetic-algorithm-optimization-based big data analysis system and method of urban regional traffic
  • Genetic-algorithm-optimization-based big data analysis system and method of urban regional traffic
  • Genetic-algorithm-optimization-based big data analysis system and method of urban regional traffic

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Embodiment 1

[0190] like figure 1 As shown, a large data analysis system for urban regional traffic based on genetic algorithm optimization, including urban road network and pedestrian travel distribution analysis module, urban road network traffic flow analysis module, urban rail transit system analysis module, urban regional traffic system decision-making module module.

[0191]The described urban road network and pedestrian travel distribution analysis module includes a double-layer network formed by the interaction between the pedestrian travel network and the road network network. The upper layer network is the pedestrian travel network, and the nodes of the upper layer network are travel generation points. Connections are connected through lines; the lower network is a road network, the nodes of the lower network are intersections, and the lines between nodes represent road sections; each node of the upper network collects the passenger flow at the node and conducts flow analysis; ea...

Embodiment 2

[0280] The present invention also provides a method for analyzing urban regional traffic big data based on genetic algorithm optimization, such as figure 2 shown, including the following steps:

[0281] (1) Establish a double-layer network formed by the interaction between the pedestrian travel network and the road network network. The upper network is the pedestrian travel network, the nodes of the upper network are travel generation points, and the interconnection between nodes is connected by lines; the lower network is the road network. The nodes of the lower network are intersections, and the connections between nodes represent road sections; each node of the upper network collects the passenger flow at the node and conducts flow analysis; each node of the lower network collects the traffic flow at the node and conducts flow analysis. Analysis; collect the big data of the urban traffic system composed of passenger flow and traffic flow on all nodes of the upper network a...

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Abstract

The invention, which belongs to the field of urban traffic design, particularly relates to a genetic-algorithm-optimization-based big data analysis system and method of urban regional traffic. The system is composed of an urban road network and pedestrian travel distribution analysis module, an urban road network traffic flow analysis module, an urban rail transit system analysis module, and an urban regional transportation system decision module. According to the invention, with urban road network and resident travel distribution as an object, a genetic-algorithm-based urban-road-network optimized dual-layer planning model is established by using a dual-layer planning model in a continuous network design and introducing the urban road network and resident travel distribution index into urban road network optimization; an optimal solution is calculated by using a genetic algorithm; and the decision-making configuration of the transportation system is realized based on the optimal solution. Therefore, the data analysis ability and decision-making ability of the urban regional traffic are enhanced substantially.

Description

technical field [0001] The invention belongs to the field of urban intelligent transportation, and in particular relates to a system and method for analyzing urban regional traffic big data based on genetic algorithm optimization. Background technique [0002] Cities are the activity centers where human beings engage in various social, political, economic and cultural life, and play an extremely important role in social development. Urban traffic is closely related to the development of the city, and it is a symbol to measure the progress of a city's civilization. With the rapid development of social economy and the rapid advancement of urbanization, the traffic volume continues to increase significantly, the contradiction between traffic demand and road traffic facilities is becoming increasingly acute, and urban traffic problems are becoming more and more serious. Urban traffic congestion not only causes frequent traffic accidents and increased vehicle delays, but also fu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
CPCG08G1/0125G08G1/0137
Inventor 杨帆
Owner TERMINUSBEIJING TECH CO LTD
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