NAR neural network vehicle speed prediction method based on driving intention recognition
The invention discloses an NAR (Nonlinear Autoregressive Models) neural network vehicle speed prediction method based on driving intention recognition. The method comprises the following steps of driving intention classification and recognition parameter selection; fuzzy reasoning recognition of the...
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| creator | LIU SHUANG YUAN LUSHAN GUO LIE LIAN JING ZHOU YAFU SUN YANQIU |
| description | The invention discloses an NAR (Nonlinear Autoregressive Models) neural network vehicle speed prediction method based on driving intention recognition. The method comprises the following steps of driving intention classification and recognition parameter selection; fuzzy reasoning recognition of the driving intention; NAR neural network off-line training; and NAR neural network on-line vehicle speed prediction: firstly performing driving intention recognition, and then inputting the driving intention obtained through recognition and the vehicle speed time sequence into an NAR neural network together so as to realize the vehicle speed prediction of the vehicle in a period of time in future. The NAR neural network vehicle speed prediction method has the advantages that the NAR neural network is used for performing vehicle speed prediction; the neural network input includes the network output feedback; the method is suitable to be used for solving the nonlinear problem on the time sequence; and the multi-step pr |
| format | Patent |
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The method comprises the following steps of driving intention classification and recognition parameter selection; fuzzy reasoning recognition of the driving intention; NAR neural network off-line training; and NAR neural network on-line vehicle speed prediction: firstly performing driving intention recognition, and then inputting the driving intention obtained through recognition and the vehicle speed time sequence into an NAR neural network together so as to realize the vehicle speed prediction of the vehicle in a period of time in future. 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The method comprises the following steps of driving intention classification and recognition parameter selection; fuzzy reasoning recognition of the driving intention; NAR neural network off-line training; and NAR neural network on-line vehicle speed prediction: firstly performing driving intention recognition, and then inputting the driving intention obtained through recognition and the vehicle speed time sequence into an NAR neural network together so as to realize the vehicle speed prediction of the vehicle in a period of time in future. The NAR neural network vehicle speed prediction method has the advantages that the NAR neural network is used for performing vehicle speed prediction; the neural network input includes the network output feedback; the method is suitable to be used for solving the nonlinear problem on the time sequence; and the multi-step pr</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES PERFORMING OPERATIONS ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT TRANSPORTING VEHICLES IN GENERAL |
| title | NAR neural network vehicle speed prediction method based on driving intention recognition |
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