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Short-time traffic flow prediction method and device

A technology of traffic flow and prediction method, applied in the field of transportation, can solve the problems of complex training process, difficult to achieve online adjustment, slow convergence speed, etc., to achieve the effect of improving prediction accuracy, easy promotion, and realizing online adjustment.

Active Publication Date: 2018-09-14
THE HONG KONG POLYTECHNIC UNIV SHENZHEN RES INST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, although the historical average model is simple in operation and fast in speed, its accuracy is poor, and static prediction has its inherent shortcomings; the training process of the prediction model based on neural network is too complicated, and its training process can only be achieved by adjusting the weight of neurons. This deficiency leads to problems such as local minima, slow convergence speed, poor generalization ability, and difficulty in online adjustment of this type of network.

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  • Short-time traffic flow prediction method and device

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Embodiment 1

[0029] figure 1 It is the realization flowchart of the short-term traffic flow forecasting method that the embodiment of the present invention provides, is described in detail as follows:

[0030] In step S101, a macroscopic traffic flow model is obtained;

[0031] In step S102, determine state vector, state equation, observation vector and observation equation;

[0032] In step S103, a data assimilation system framework for traffic flow forecasting is constructed;

[0033] In step S104, the observation data of different observation period types are classified and sampled; in step S105, the historical observation data is fused, and based on the data assimilation method of the adjusted ensemble Kalman filter, the observation value missing at the current moment is completed;

[0034] In step S106, based on the data assimilation method, the model parameters of the macro traffic flow model are corrected and adjusted;

[0035] In step S107, the traffic flow at the future moment ...

Embodiment 2

[0038] The embodiment of the present invention describes the macroscopic traffic flow model, and the macroscopic traffic flow model is specifically:

[0039]

[0040]

[0041] q i (t)=β(v i (t)·ρ i (t))+(1-β)(v i+1 (t)·ρ i+1 (t)) (3)

[0042]

[0043] where: ρ i (t) is the traffic density at time t on road section i;

[0044] v i (t) is the average speed of the vehicle at time t on road section i;

[0045] q i (t) is the traffic flow at the boundary point between road section i and road section i+1 at time t;

[0046] r i (t),s i (t) are respectively the inflow and outflow flow values ​​on road segment i at time t;

[0047] Δt is the time gain;

[0048] lambda i is the number of lanes on road segment i;

[0049] v e (·) is the velocity at the equilibrium state, which can be obtained by formula (4), where:

[0050] v f ,ρ cr , α are the free speed, the critical traffic density, and the exponent of the speed equation when the road is clear, respective...

Embodiment 3

[0054] The embodiment of the present invention describes the determination of the state part and the observation part, and the details are as follows:

[0055] We take the traffic density and average speed as the state vector X(t), that is, X(t)=(ρ,v) t ;Take the traffic flow as the observation vector Y(t), that is, Y(t)=(q) t ; Formula (1) and formula (2) in the macro-traffic flow model are used as the state equation; formula (3) is used as the observation equation.

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Abstract

The invention is suitable for the traffic field and provides a short-time traffic flow prediction method and device. The short-time traffic flow prediction method comprises steps that a macro trafficflow model is acquired; a state vector, a state equation, an observation vector and an observation equation are determined; a data assimilation system framework for traffic flow prediction is constructed; observation data of different observation period types are classified and sampled; historical observation data are fused, and missing observation values at the present time period are completed based on the adjusted data assimilation method of set Kalman filtering; based on the data assimilation method, model parameters of a macroscopic traffic flow model are corrected and adjusted; the macroscopic traffic flow model after model parameter adjustment is utilized to predict the traffic flow in the future. The short-time traffic flow prediction method is advantaged in that the traffic flow in the future can be predicted, moreover, online adjustment is realized, and the short-time traffic flow prediction method is easy to promote.

Description

technical field [0001] The invention belongs to the traffic field, and mainly relates to a short-term traffic flow prediction method and device. Background technique [0002] With the development of the traffic industry, many traffic problems such as traffic congestion and traffic accidents are becoming more and more obvious. Only the traffic control and guidance system has become a hot core topic in ITS research, and the key issue in realizing the traffic flow guidance system is accurate short-term Real-time traffic flow forecasting, that is, how to effectively use real-time traffic data information to rollingly predict traffic conditions in the next few minutes, provide travelers with real-time and effective route selection information, shorten travel time, and reduce traffic congestion. The short-term forecast is in the micro sense, which is fundamentally different from the strategic forecast based on traffic planning calculated in hours, days, months or even years in the...

Claims

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0129
Inventor 史文中王闰杰
Owner THE HONG KONG POLYTECHNIC UNIV SHENZHEN RES INST
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