LOW-SPEED, BACKWARD DRIVING VEHICLE CONTROLLER DESIGN
In one embodiment, a method of generating control effort to control an autonomous driving vehicle (ADV) includes determining a gear position (forward or reverse) in which the ADV is driving and selecting a driving model and a predictive model based upon the gear position. In a forward gear, the driv...
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Format | Patent |
Language | English |
Published |
13.05.2021
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Abstract | In one embodiment, a method of generating control effort to control an autonomous driving vehicle (ADV) includes determining a gear position (forward or reverse) in which the ADV is driving and selecting a driving model and a predictive model based upon the gear position. In a forward gear, the driving model is a dynamic model, such as a "bicycle model," and the predictive model is a look-ahead model. In a reverse gear, the driving model is a hybrid dynamic and kinematic model and the predictive model is a look-back model. A current and predicted lateral error and heading error are determined using the driving model and predictive model, respectively A linear quadratic regulator (LQR) uses the current and predicted lateral error and heading errors, to determine a first control effort, and an augmented control logic determines a second, additional, control effort, to determine a final control effort that is output to a control module of the ADV to drive the ADV. |
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AbstractList | In one embodiment, a method of generating control effort to control an autonomous driving vehicle (ADV) includes determining a gear position (forward or reverse) in which the ADV is driving and selecting a driving model and a predictive model based upon the gear position. In a forward gear, the driving model is a dynamic model, such as a "bicycle model," and the predictive model is a look-ahead model. In a reverse gear, the driving model is a hybrid dynamic and kinematic model and the predictive model is a look-back model. A current and predicted lateral error and heading error are determined using the driving model and predictive model, respectively A linear quadratic regulator (LQR) uses the current and predicted lateral error and heading errors, to determine a first control effort, and an augmented control logic determines a second, additional, control effort, to determine a final control effort that is output to a control module of the ADV to drive the ADV. |
Author | WANG, Yu LUO, Qi JIANG, Shu HU, Jiangtao WANG, Jingao HE, Runxin XU, Jiaxuan MIAO, Jinghao ZHOU, Jinyun |
Author_xml | – fullname: ZHOU, Jinyun – fullname: JIANG, Shu – fullname: MIAO, Jinghao – fullname: XU, Jiaxuan – fullname: LUO, Qi – fullname: WANG, Jingao – fullname: HU, Jiangtao – fullname: WANG, Yu – fullname: HE, Runxin |
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Snippet | In one embodiment, a method of generating control effort to control an autonomous driving vehicle (ADV) includes determining a gear position (forward or... |
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SubjectTerms | CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES CONTROLLING PERFORMING OPERATIONS PHYSICS REGULATING ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES TRANSPORTING VEHICLES IN GENERAL |
Title | LOW-SPEED, BACKWARD DRIVING VEHICLE CONTROLLER DESIGN |
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