Vehicle trajectory network interactive predicting method for movement states of multiple vehicles

A motion state and prediction method technology, applied in the field of intelligent networked vehicle environment perception, can solve the problems of application limitations, not considering the influence of the prediction target, and not considering the independent prediction of a single vehicle.

Active Publication Date: 2019-06-21
TSINGHUA UNIV
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AI Technical Summary

Problems solved by technology

[0004] However, since the above-mentioned multi-vehicle input prediction algorithm only considers the influence of environmental vehicles on the predicted target when predicting the future driving state, but does not consider the impact of the predicted target

Method used

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  • Vehicle trajectory network interactive predicting method for movement states of multiple vehicles
  • Vehicle trajectory network interactive predicting method for movement states of multiple vehicles
  • Vehicle trajectory network interactive predicting method for movement states of multiple vehicles

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Embodiment Construction

[0060] The multi-vehicle motion state proposed by the present invention is a network-connected interactive prediction method for vehicle trajectories, the flow chart of which is as follows figure 1 shown, including the following steps:

[0061] (1) It is set that the predicted target vehicle and the environment vehicle are distributed in three adjacent lanes, and the target vehicle is in the middle lane. When the target vehicle crosses the middle lane line, the positional relationship between the target vehicle and the environment vehicle is replaced by the new The three adjacent lanes still keep the target vehicle in the middle lane, and the specific spatial position relationship is as follows figure 2 Shown:

[0062] (1-1) The target vehicle is located in the middle lane;

[0063] (1-2) The vehicle in front is located in the middle lane and in front of the target vehicle;

[0064] (1-3) The left front vehicle is located in the left lane and in front of the target vehicle...

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Abstract

The invention relates to a vehicle trajectory network interactive predicting method for the movement states of a plurality of vehicles, and belongs to the technical field of intelligent networking vehicle environment awareness. The method provided by the invention comprises the following steps: determining the relative position relationship of a plurality of networked vehicles; extracting the characteristics of the driving state of each vehicle, respectively inputting the characteristics of the driving states of the vehicles into short and long term memory units, and connecting and sharing hidden states of adjacent vehicles through a radial network so as to construct structured short and long time memory units and realize the modelling of an interaction relationship among the vehicles; then, establishing a multilayer encoder-decoder network to predict the future driving trajectories of the vehicles by utilizing the structured short and long time memory units; finally, transmitting thepredicted state obtained by the network to a decision making module to perform autonomous decision-making and path planning. According to the vehicle trajectory network interactive predicting method for the movement states of the vehicles, the driving states of the networked vehicles are shared in a hidden state layer by adopting the structured short and long time memory units so as to realize themodelling of the interaction relationship; by the method, synchronous long-time span prediction can be performed on the vehicles in a complex traffic environment to achieve high prediction accuracy.

Description

technical field [0001] The invention relates to a method for interactively predicting vehicle trajectories and networks in the motion state of multiple vehicles, and belongs to the technical field of intelligent and networked vehicle environment perception. Background technique [0002] Intelligentization and networking are the development trend of automobile technology. Intelligent networked vehicles have the potential advantages of enhancing safety, improving economy and increasing traffic volume, and have become a research hotspot at home and abroad. In order to ensure driving safety in complex traffic environments, ICVs need to predict changes in the traffic environment in the future and make reasonable responses. The driving state of surrounding cars is usually difficult to predict, mainly caused by the following uncertain factors: randomness of driver behavior, strong interaction with other traffic participants, spatial constraints of road structure, and noise perceive...

Claims

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Application Information

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IPC IPC(8): B60W50/00G08G1/01
Inventor 李升波成波侯廉忻隆王文军孙琪李克强
Owner TSINGHUA UNIV
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