Road network mixed flow diurnal variation prediction method considering unmanned vehicle
A technology of unmanned vehicles and mixed traffic, applied in the field of transportation, can solve problems affecting the stability and reliability of the transportation network, traffic supply and traffic demand fluctuations, etc.
Active Publication Date: 2020-03-31
SOUTH CHINA UNIV OF TECH
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Problems solved by technology
[0003] Existing studies mainly focus on the attractiveness of unmanned vehicles to travelers and the analysis of the impact on urban traffic congestion, but have not analyzed the dynamic impact of unmanned vehicles on the flow of traditional road networks after the launch of unmanned vehicles. Changes in traffic flow will cause fluctuations in traffic supply and traffic demand, thus affecting the stability and reliability of the entire transportation network
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[0077] Suppose the road network G=(N,A), where N represents the node set, A represents the road segment set, for any road segment a∈A. r and s represent the origin and destination points respectively, and R and S represent the origin and destination point sets respectively, and there is rs∈RS. k represents the path, K represents the path set, there is k∈K. K rs Indicates the set of all paths connecting OD pair rs. This chapter considers the multi-OD case. q rs Indicates the traffic demand between origin and destination within the study period. u and z denote travelers and unmanned vehicles, respectively.
[0078] Such as figure 1 As shown, a road network mixed flow forecasting method considering unmanned vehicles includes the following steps:
[0079] S1: Determination of link-path flow relationship in mixed flow daily variation model
[0080] The traffic in the road network is composed of two parts: unmanned driving traffic and traveler traffic. The evolution of the t...
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The invention discloses a road network mixed flow diurnal variation prediction method considering unmanned vehicles. The method comprises the following steps: S1, determining a road section-path flowrelationship of a mixed flow diurnal variation model; S2, determining a path-road section impedance function / travel time; S3, determining a traveler flow diurnal variation foreground value relationship; S4, updating the traveler flow day by day; and S5, determining optimal flow distribution of the unmanned driving flow diurnal variation model. The mixed flow diurnal variation model with travelersand unmanned vehicles is established, and the model is divided into two sub-models according to flow categories, namely a traveler flow diurnal variation model and an unmanned flow diurnal variation model; traveler flow evolves day by day by taking the maximum path foreground value as a target; the minimum path marginal impedance is taken as a target to evolve the driverless traffic day by day; and when the two types of flow evolve to respective equilibrium states day by day, the system flow is equalized.
Description
technical field [0001] The invention belongs to the field of transportation, and in particular relates to a method for predicting the daily change of road network mixed flow in consideration of unmanned vehicles. Background technique [0002] With the maturity of unmanned driving technology, unmanned vehicles will become an important way of travel, and combined with the characteristics of unmanned vehicles, it will inevitably have a major impact on the existing urban traffic system, changing the existing travel patterns and traffic flow patterns. Similar to traditional travelers (referring to non-autonomous driving vehicles), unmanned vehicles will gradually adjust their travel choices during day-to-day travel, but unlike traditional travelers, unmanned vehicles do not have the power of human beings. Preference attributes and risk attitudes do not produce subjective perception of path selection, but make path planning based on the results calculated by the computer. Theref...
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Login to View More IPC IPC(8): G08G1/01G08G1/065
CPCG08G1/0129G08G1/065
Inventor 田晟朱泽坤肖佳将冯宇鹏许凯
Owner SOUTH CHINA UNIV OF TECH