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公开(公告)号：US20240168478A1
公开(公告)日：2024-05-23
申请号：US18431194
申请日：2024-02-02
Applicant: TuSimple, Inc.
Inventor： Xiaomin ZHANG , Yilun CHEN , Guangyu LI , Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles is configured to: receive data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, generating a proposed trajectory for the host vehicle, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle based on the proposed host vehicle trajectory, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.
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公开(公告)号：US20190072966A1
公开(公告)日：2019-03-07
申请号：US15806013
申请日：2017-11-07
Applicant: TuSimple
Inventor： Xiaomin ZHANG , Yilun CHEN , Guangyu LI , Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment is configured to: receive training data and ground truth data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, generating a proposed trajectory for the host vehicle, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle based on the proposed host vehicle trajectory, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.
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公开(公告)号：US20190072965A1
公开(公告)日：2019-03-07
申请号：US15805983
申请日：2017-11-07
Applicant: TuSimple
Inventor： Xiaomin ZHANG , Yilun CHEN , Guangyu LI , Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment is configured to: receive training data and ground truth data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle, generating a proposed trajectory for the host vehicle, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.
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