Flow-speed matching model and travel time forecasting method and system

Abstract

The invention provides a flow-speed matching model and a travel time forecasting method and system. The method includes the steps of firstly, calculating theoretical travel time and traffic flow average speed of a road section; secondly, calculating the error between the theoretical travel time and actually-measured travel time, conducting feeding and adjusting on the traffic flow average speed according to the error, and renewing flow-speed data of the corresponding road section; thirdly, repeating the first step and the second step till the error is smaller than a preset threshold value, and storing the errors as a flow-speed matching model; fourthly, directly conducting matching in the flow-speed matching model through forecasted flow to obtain the average speed, and then calculating the travel time according to the average speed. According to the flow-speed matching model and the travel time forecasting method and system, the travel time is calculated according to the traffic wave principle, feeding and adjusting are conducted on the average speed, the calculation result is corrected unceasingly, and the flow-speed matching model is renewed; the travel time forecasting method is simple, and meanwhile the flow-speed matching model can be enriched and optimized in the travel time forecasting process so that the forecasting model can be higher in accuracy.

Description

technical field

[0001] The invention relates to a flow-speed matching model and a travel time prediction method and system, specifically a flow-speed matching model established by using a speed feedback adjustment method, and then using the flow-speed matching model to predict the travel time of intermittent traffic on urban roads Methods. It belongs to the technical field of traffic control. Background technique

[0002] Whether the urban traffic condition is good or not directly affects the development of the urban economy. How to deal with traffic congestion as soon as possible and effectively has become an urgent problem to be solved in many cities. The traffic flow guidance system is an important means to alleviate urban road traffic congestion and regulate the development of urban road network traffic flow towards a balanced distribution. driving time. Therefore, it is of great significance to study the travel time prediction method of urban traffic flows. [0003...

Examples

Embodiment 1

[0059] This embodiment provides a method for establishing a flow-speed matching model, the flow chart of which is as follows figure 1 As shown, the specific steps are as follows:

[0060] (1) Calculate the theoretical travel time and the average speed of the traffic flow of the road section, and store the travel time and the average speed of the traffic flow. The specific process of obtaining the travel time of the road section includes:

[0061] ① Collect the traffic flow, congestion density and saturated flow of the road section, which can be obtained by means of existing technologies well known in the art.

[0062] ② According to the traffic flow and density of the road section, the accumulation wave and dissipating wave are calculated. Such as image 3 As shown in Fig. 1, after a train team running on the road section encounters a red light at the intersection, the traffic density on the road section where the vehicles stop and line up gradually increases. In a traffic...

Embodiment 2

[0073] This embodiment implements a system for establishing a flow-speed matching model using a method for establishing a flow-speed matching model, including:

[0074] Modules for calculating the theoretical travel time and average speed of traffic on road sections;

[0075] It is used to calculate the error between the theoretical travel time and the measured travel time, perform feedback adjustment to the average speed of the traffic flow according to the error, and update the flow-speed data module corresponding to the road section;

[0076] For repeating the above steps until the error between the theoretical travel time and the measured travel time is less than a preset threshold, the flow-speed data is saved as a flow-speed matching model module.

[0077] The system for establishing a traffic-speed matching model provided in this embodiment uses the method for establishing a traffic-speed matching model to calculate the travel time by using the traffic wave principle, a...

Embodiment 3

[0079] This embodiment provides a travel time prediction method, the flow chart of which is as follows figure 2 As shown, it specifically includes the following steps:

[0080] (1) Predict the traffic flow of the road section to be tested. The prediction method can adopt one of the time series method, historical trend method, neural network, Kalman filter method and other methods well known to those skilled in the art, or use several methods to combine prediction, and choose according to the actual road section and demand .

[0081] (2) Match the traffic flow with the flow-speed matching model to obtain the average speed of the traffic flow on the road section to be tested. The matching process is: match the traffic flow with a preset flow interval , and obtain the corresponding average speed of the preset traffic interval as the average speed of the traffic flow of the road section to be tested. The matching process is simple and fast without classifying and refining the ...

technical field

[0001] The invention relates to a flow-speed matching model and a travel time prediction method and system, specifically a flow-speed matching model established by using a speed feedback adjustment method, and then using the flow-speed matching model to predict the travel time of intermittent traffic on urban roads Methods. It belongs to the technical field of traffic control. Background technique

[0002] Whether the urban traffic condition is good or not directly affects the development of the urban economy. How to deal with traffic congestion as soon as possible and effectively has become an urgent problem to be solved in many cities. The traffic flow guidance system is an important means to alleviate urban road traffic congestion and regulate the development of urban road network traffic flow towards a balanced distribution. driving time. Therefore, it is of great significance to study the travel time prediction method of urban traffic flows. [0003...

Examples

Embodiment 1

[0059] This embodiment provides a method for establishing a flow-speed matching model, the flow chart of which is as follows figure 1 As shown, the specific steps are as follows:

[0060] (1) Calculate the theoretical travel time and the average speed of the traffic flow of the road section, and store the travel time and the average speed of the traffic flow. The specific process of obtaining the travel time of the road section includes:

[0061] ① Collect the traffic flow, congestion density and saturated flow of the road section, which can be obtained by means of existing technologies well known in the art.

[0062] ② According to the traffic flow and density of the road section, the accumulation wave and dissipating wave are calculated. Such as image 3 As shown in Fig. 1, after a train team running on the road section encounters a red light at the intersection, the traffic density on the road section where the vehicles stop and line up gradually increases. In a traffic...

Embodiment 2

[0073] This embodiment implements a system for establishing a flow-speed matching model using a method for establishing a flow-speed matching model, including:

[0074] Modules for calculating the theoretical travel time and average speed of traffic on road sections;

[0075] It is used to calculate the error between the theoretical travel time and the measured travel time, perform feedback adjustment to the average speed of the traffic flow according to the error, and update the flow-speed data module corresponding to the road section;

[0076] For repeating the above steps until the error between the theoretical travel time and the measured travel time is less than a preset threshold, the flow-speed data is saved as a flow-speed matching model module.

[0077] The system for establishing a traffic-speed matching model provided in this embodiment uses the method for establishing a traffic-speed matching model to calculate the travel time by using the traffic wave principle, a...

Embodiment 3

[0079] This embodiment provides a travel time prediction method, the flow chart of which is as follows figure 2 As shown, it specifically includes the following steps:

[0080] (1) Predict the traffic flow of the road section to be tested. The prediction method can adopt one of the time series method, historical trend method, neural network, Kalman filter method and other methods well known to those skilled in the art, or use several methods to combine prediction, and choose according to the actual road section and demand .

[0081] (2) Match the traffic flow with the flow-speed matching model to obtain the average speed of the traffic flow on the road section to be tested. The matching process is: match the traffic flow with a preset flow interval , and obtain the corresponding average speed of the preset traffic interval as the average speed of the traffic flow of the road section to be tested. The matching process is simple and fast without classifying and refining the ...

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