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公开(公告)号：US11964655B2
公开(公告)日：2024-04-23
申请号：US17766870
申请日：2021-04-12
Applicant: SOUTHEAST UNIVERSITY
Inventor： Xu Li , Weiming Hu , Jinchao Hu , Xuefen Zhu
IPC: B60W30/095 , G06N3/045 , G06N3/0464
CPC classification number: B60W30/0956 , G06N3/045 , G06N3/0464 , B60W2300/125 , B60W2420/408 , B60W2554/4041 , B60W2554/80
Abstract: The present invention discloses a backward anti-collision driving decision-making method for a heavy commercial vehicle. Firstly, a traffic environment model is established, and movement state information of a heavy commercial vehicle and a vehicle behind the heavy commercial vehicle is collected. Secondly, a backward collision risk assessment model based on backward distance collision time is established, and a backward collision risk is accurately quantified. Finally, a backward anti-collision driving decision-making problem is described as a Markov decision-making process under a certain reward function, a backward anti-collision driving decision-making model based on deep reinforcement learning is established, and an effective, reliable and adaptive backward anti-collision driving decision-making policy is obtained. The method provided by the present invention can overcome the defect of lack for research on the backward anti-collision driving decision-making policy for the heavy commercial vehicle in the existing method, can quantitatively output proper steering wheel angle and throttle opening control quantities, can provide effective and reliable backward anti-collision driving suggestions for a driver, and can reduce backward collision accidents.
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公开(公告)号：US11650077B2
公开(公告)日：2023-05-16
申请号：US17289737
申请日：2020-12-02
Applicant: SOUTHEAST UNIVERSITY
Inventor： Xiyuan Chen , Xin Shao , Xinhua Tang , Xuefen Zhu , Xiaosu Xu
CPC classification number: G01C25/005 , B60W30/18018 , G01C21/188 , G06F17/16 , G06F17/175
Abstract: A strict reverse navigation method for optimal estimation of fine alignment is provided. The strict reverse navigation method including: establishing an adaptive control function; performing a forward navigation calculation process; performing a reverse navigation calculation process; and performing the adaptive control for a number of forward and reverse calculations. The strict reverse navigation method shortens an alignment time for the optimal estimation of fine alignment while ensuring an alignment accuracy. The strict reverse navigation method provided effectively solves a problem that an error of an initial value of filtering in an initial stage of the optimal estimation of fine alignment affects convergence speeds of subsequent stages. In the initial stage, a larger number of the forward and reverse navigation calculations are adopted to reduce an error of the initial value as much as possible and increase a convergence speed of the filtering.
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公开(公告)号：US10663599B2
公开(公告)日：2020-05-26
申请号：US15511046
申请日：2016-06-27
Applicant: Southeast University
Inventor： Xiyuan Chen , Yang Yang , Xiying Wang , Bingbo Cui , Xinhua Tang , Xuefen Zhu
Abstract: The present invention discloses a joint non-coherent integral vector tracking method based on a spatial domain, which is used for further improving the performance of a vector tracking GPS (Global Positioning System) receiver. In a new vector tracking strategy design, a phase discriminator/a frequency discriminator in a traditional vector tracking loop is discarded, and baseband signals of visible satellites in each channel are taken as an observation value after performing non-coherent integration, and EKF (abbreviation of Extended Kalman Filter) is used to estimate directly and to solve the position, the velocity, a clock error, etc. of the GPS receiver. Because of the existence of non-coherent integral calculation, when GPS satellite signals are relatively weak, a carrier to noise ratio of an observation value may be effectively improved, and the tracking sensitivity is improved.
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