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Car-following behavior generation method based on timed automaton

A time automaton and behavioral technology, applied in computer parts, instruments, character and pattern recognition, etc., can solve the problem of inability to recognize surrounding vehicles, and achieve the effect of improving the level of anthropomorphism and intelligence

Active Publication Date: 2017-08-15
TONGJI UNIV
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Problems solved by technology

This type of model can only roughly represent the driver's car-following behavior. For unmanned vehicles, this model cannot reflect the specific car-following behavior and cannot be well recognized by surrounding vehicles. Therefore, it is necessary to further refine the car-following behavior Improve the anthropomorphic intelligence level of unmanned vehicles

Method used

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  • Car-following behavior generation method based on timed automaton
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  • Car-following behavior generation method based on timed automaton

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Embodiment

[0032] A timed automata-based car-following behavior generation method, first extracting vehicle-following data from a public traffic dataset (NextGeneration SIMulation, NGSIM). Based on the k-means clustering algorithm, the input parameters of the car-following model (relative distance, relative speed, and the speed of the following vehicle) are symbolized, and the timed automata learning algorithm (RTI+Learning Algorithm) is used to train the car-following model, and the following car-following model is obtained. Car model automaton. The state sequence is clustered by hierarchical clustering method, and a series of sub-behavior patterns in car-following behavior are obtained. Using the automaton model to generate the follow-up behavior trajectory of the unmanned vehicle, and display the corresponding sub-behavior patterns, the follow-up trajectory that is closer to the driving trajectory of the human driver can be obtained.

[0033] Method flow chart as figure 1 . Specifi...

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Abstract

The invention relates to a car-following behavior generation method based on a timed automaton. The car-following behavior generation method comprises the steps of: S1, extracting car-following data from a traffic data set, regarding a rear car speed, a relative distance and a relative speed between a rear car and a front car as input parameters of a car-following model, and symbolizing the input parameters; S2, training the car-following model by utilizing a timed automaton learning algorithm to obtain a car-following model automaton; S3, regarding a hidden state of the car-following model automaton as substates of following cars, clustering the substates for representing car-following sub-behaviors; S4, establishing a Helly car-following model for each car-following sub-behavior, and carrying out parameter calibration on each Helly car-following model to obtain rear car acceleration under the corresponding sub-behavior, thereby acquiring a car-following trajectory. Compared with the prior art, the car-following behavior generation method is used for learning symbols by means of the timed automaton to obtain the hidden state, clustering the substates to represent the sub-behaviors of the following cars better, shows the human car-following behavior trajectory precisely, and improves the intelligent level of unmanned vehicles.

Description

technical field [0001] The invention relates to a method for generating car-following behavior, in particular to a method for generating car-following behavior based on time automata. Background technique [0002] With the development of computer technology and artificial intelligence, unmanned vehicles (hereinafter referred to as unmanned vehicles) have shown great application prospects in military, transportation, industrial production, logistics and warehousing, and daily life. In terms of national defense and military affairs, unmanned vehicles are mostly used to perform military tasks in dangerous scenarios, such as military rescue and material delivery. In terms of traffic safety, unmanned driving technology is an effective means to promote the development of intelligent transportation systems. Unmanned driving technology based on artificial intelligence can improve the active safety of vehicles, and can effectively reduce traffic accidents caused by driver misuse, the...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/231G06F18/22G06F18/214
Inventor 郭亚锋王峻张怡欢王亮
Owner TONGJI UNIV
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