Intelligent vehicle traveling speed and time predication method based on macro city traffic flow

A technology of intelligent vehicle and driving speed, applied in the field of intelligent vehicle model research, can solve the problems of the impact of road traffic capacity and the accuracy of real-time distribution modeling analysis of traffic flow

Active Publication Date: 2015-08-05
BEIJING INSTITUTE OF TECHNOLOGYGY
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At the same time, these factors will also affect the traffic capacity of the road section, the

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  • Intelligent vehicle traveling speed and time predication method based on macro city traffic flow
  • Intelligent vehicle traveling speed and time predication method based on macro city traffic flow
  • Intelligent vehicle traveling speed and time predication method based on macro city traffic flow

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[0034] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0035] A smart vehicle speed and time model based on macroscopic urban traffic flow, the specific process is:

[0036] (1) Analyze and select the key road variables that have a relevant impact on the driving speed and travel time of the smart vehicle in each operating environment of the smart vehicle, and collect and measure the driving environment variable information;

[0037] ① Collect parameters such as highways and road linear design in the urban traffic network from the Urban Planning Bureau, Highway Design Institute and other units. The road conditions include the starting and ending nodes S_Node, E_Node; the length of the road section L i ;Radius of curvature R i ;Ramp length L S ;Segment gradient G S ;Number of lanes N i ; Lane width W L ;Shoulder width W S , W m and other road design attribute parameters.

[0038] ②On-site m...

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Abstract

The invention proposes an intelligent vehicle traveling speed and time predication method based on a macro city traffic flow. Firstly the road and environment related variables in a driving environment are selected and quantified, secondly a GIS database of intelligent vehicle autonomous driving is established, thirdly combined with a regression analysis method, the combination rule of the key variables in the driving environment is provided, and the multiple-element linear relationship of intelligent vehicle driving speed and road design parameter, traffic condition and real-time road condition in a city traffic network is obtained, fourthly, based on the VLM model of the macro city traffic flow theory of a trapezoid density-flow basic pattern, the dynamic and stable characteristics of the VLM model of a road are obtained, and the speed and time evaluation function of the macro city traffic flow is given, and finally combined with the multiple-element linear vehicle speed model of the road in different vehicle flow density and initial states, the driving speed constraint equation of an intelligent vehicle in a city road network is obtained, and the optimal driving speed and travel time which satisfy a target function are obtained.

Description

technical field [0001] The invention belongs to the research on intelligent vehicle models in urban traffic, and relates to a method for predicting the driving speed and time of intelligent vehicles based on macroscopic urban traffic flow. Background technique [0002] Traffic flow theory is to describe the movement rules of traffic vehicles in the studied road network, explain the formation mechanism of traffic phenomena, and provide theoretical guidance for the planning, design and operation management of urban roads and highways. In the study of Intelligent Transportation System (ITS), establishing a proper traffic flow model of urban traffic network is a crucial research content in traffic control. The macroscopic traffic flow model is an approximation after ignoring the details of individual vehicles and simplifying the real dynamic traffic. Carlos (2011) proposed a unit variable length model (VLM) under the variable speed limit framework for high-speed traffic network...

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Application Information

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IPC IPC(8): G08G1/01G08G1/052G06Q10/04
CPCG06Q10/04G08G1/0104G08G1/052
Inventor 王美玲张叶青潘允辉王新平
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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