公开(公告)号：US11367215B2

公开(公告)日：2022-06-21

申请号：US17057915

申请日：2019-05-29

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Jiwen Cao ,  Peizhou Ni ,  Kun Wei

IPC: G06T7/70 ,  G06T7/73 ,  B60R11/04 ,  B62D15/02 ,  G06K9/62 ,  G06T5/00 ,  G06V10/25 ,  B60R11/00 ,  G06V20/62 ,  G06V30/10

Abstract: The present invention discloses a positive azimuth towing guidance method for road rescue equipment based on license plate corner features. The method combines a structure of the road rescue equipment and characteristics of a positive azimuth towing operation. First, an image of an operation area is collected by installing a camera, and grayscale processing and Gaussian smooth filtering are performed on the image; corner detection is performed on the smoothed grayscale image, and preference is implemented according to corner strengths; hierarchical clustering is performed on the preferred corners; an effective corner set of license plate characters is sorted out to implement license plate locating; and then towing guidance is implemented according to a license plate locating result, to improve the rescue efficiency of the road rescue equipment. The guidance method provided in the present invention has good real-time performance, environmental adaptability and anti-interference ability, thereby effectively improving the rescue efficiency of the road rescue equipment.

公开(公告)号：US20210303911A1

公开(公告)日：2021-09-30

申请号：US17267493

申请日：2019-05-16

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu LI ,  Zhiyong Zheng ,  Kun Wei

IPC: G06K9/62 ,  G06K9/00 ,  G06T7/11 ,  G06N3/04

Abstract: The present invention discloses a roadside image pedestrian segmentation method based on a variable-scale multi-feature fusion convolutional network. For scenes where the pedestrian scale changes significantly in the intelligent roadside terminal image, this method designs two parallel convolutional neural networks to extract the local and global features of pedestrians at different scales in the image, and then fuses the local features and global features extracted by the first network with the local features and global features extracted by the second network at the same level, and then fuse the fused local features and global features for the second time to obtain a variable-scale multi-feature fusion convolutional neural network, and then train the network and input roadside pedestrian images to realize pedestrian segmentation. The present invention effectively solves the problems that most current pedestrian segmentation methods based on a single network structure are prone to segmentation boundary fuzziness and missing segmentation.

公开(公告)号：US11783594B2

公开(公告)日：2023-10-10

申请号：US17267493

申请日：2019-05-16

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Zhiyong Zheng ,  Kun Wei

IPC: G06V20/58 ,  G06T7/11 ,  G06V20/56 ,  G06V40/10 ,  G06F18/25 ,  G06N3/045 ,  G06V10/764 ,  G06V10/80 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06V20/58 ,  G06F18/253 ,  G06N3/045 ,  G06T7/11 ,  G06V10/454 ,  G06V10/764 ,  G06V10/806 ,  G06V10/82 ,  G06V20/56 ,  G06V40/10

Abstract: The present invention discloses a method for segmenting pedestrians in roadside images using a variable-scale multi-feature fusion convolutional network. It addresses the challenge of significant changes in pedestrian scale by using two parallel convolutional neural networks to extract the local and global features at different scales, and then fusing them to obtain a variable-scale multi-feature fusion convolutional neural network, and this network is trained using roadside pedestrian images to realize accurate pedestrian segmentation, avoiding issues with boundary fuzziness and missing segments commonly found in single-network methods.

公开(公告)号：US11648946B2

公开(公告)日：2023-05-16

申请号：US17768765

申请日：2021-04-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Weiming Hu ,  Qimin Xu ,  Kun Wei

IPC: B60W30/18 ,  B60W30/165 ,  B60W40/072 ,  B60W40/114 ,  B60W40/13 ,  B60W50/00 ,  G05D1/02 ,  G08G1/00

CPC classification number: B60W30/18163 ,  B60W30/165 ,  B60W30/18145 ,  B60W40/072 ,  B60W40/114 ,  B60W40/13 ,  B60W50/0098 ,  G05D1/0293 ,  G05D1/0295 ,  G08G1/22 ,  B60W2040/1323 ,  B60W2050/0028 ,  B60W2050/0052 ,  B60W2552/30 ,  B60W2556/60 ,  B60W2710/207 ,  G05D2201/0213

Abstract: The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.

公开(公告)号：US11603081B2

公开(公告)日：2023-03-14

申请号：US17764871

申请日：2021-04-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Kun Wei ,  Qimin Xu

IPC: B60T8/1755

Abstract: For a tank truck using an EBS, the present invention provides a tank truck rollover relieved control method based on electronic braking deceleration. Firstly, a tank truck rollover scene applicable to the relieved control method is defined; then, a least square method is adopted to establish a characterization function of tank truck braking deceleration; and finally, tank truck rollover relieved control is achieved on the basis of the characterization function of the braking deceleration and the EBS. The method fits out a function expression of the tank truck braking deceleration and can automatically select a proper braking deceleration under different rollover scenes according to kinematics information of the tank truck and vehicle body information; during tank truck braking deceleration, an operation of a driver is considered, so that man-machine effective combination is achieved; and relieved braking deceleration is conducted when the tank truck is in a potential rollover risk state, a situation that emergency braking is conducted when the tank truck has high rollover risk is avoided, and tank truck rollover control stability and effectiveness are improved.