公开(公告)号：US11852496B2

公开(公告)日：2023-12-26

申请号：US17144561

申请日：2021-01-08

Applicant: Toyota Motor Engineering & Manufacturing North America, Inc. ,  Toyota Motor Corporation

Inventor： Yusuke Hara ,  Kentaro Oguchi

IPC: G01C21/34 ,  H04W4/029 ,  G08G1/01 ,  G08G1/052 ,  G08G1/16 ,  B60W30/14 ,  B60W50/00 ,  B60W60/00 ,  B60W30/18 ,  G01C21/36

CPC classification number: G01C21/3492 ,  B60W30/143 ,  B60W30/18163 ,  B60W50/0097 ,  B60W60/0027 ,  G01C21/3691 ,  G08G1/0125 ,  G08G1/0133 ,  G08G1/052 ,  G08G1/167 ,  H04W4/029 ,  B60W2420/42 ,  B60W2420/52 ,  B60W2420/62 ,  B60W2554/408 ,  B60W2554/4041 ,  B60W2556/50 ,  B60W2556/65

Abstract: A method of operating a traffic management system comprises receiving data from a vehicle indicating a traffic state, estimating a future time at which the vehicle will receive driving instructions transmitted by the traffic management system, predicting a future traffic state at the estimated future time, determining the driving instructions for the vehicle based on the predicted future traffic state, and transmitting the driving instructions to the vehicle.

公开(公告)号：US20230391326A1

公开(公告)日：2023-12-07

申请号：US17829979

申请日：2022-06-01

Applicant: AUTOTALKS LTD.

Inventor： Onn Haran

IPC: B60W30/14 ,  B60W30/16 ,  B60W30/095 ,  B60W40/04 ,  B60W40/105 ,  B60W60/00 ,  H04W4/44

CPC classification number: B60W30/143 ,  B60W30/16 ,  B60W30/0956 ,  B60W40/04 ,  B60W40/105 ,  B60W60/001 ,  H04W4/44 ,  B60W2554/408 ,  B60W2554/80 ,  B60W2555/60 ,  B60W2556/45

Abstract: Method and apparatus for traffic-aware speed guidance to a self-vehicle acting as a following vehicle vs. a followed vehicle. In a traffic environment that includes a followed vehicle and a self-vehicle that acts as a following vehicle, the apparatus is used to analyze values and change patterns of a plurality of speed inputs to obtain analyzed values, wherein a speed input of the followed vehicle is received through vehicle-to-everything (V2X) communications; to calculate, for each analyzed value, a respective TTC adjustment, to calculate a combined TTC between the self-vehicle and the followed vehicle using the TTC adjustments, and, based on the combined TTC, to calculate a new speed guidance between the self-vehicle and the followed vehicle, thereby improving traffic behavior.

公开(公告)号：US20230256901A1

公开(公告)日：2023-08-17

申请号：US18016138

申请日：2021-07-02

Applicant: KNORR-BREMSE Systeme fuer Nutzfahrzeuge GmbH

Inventor： Csaba HORVATH ,  Huba NEMETH

IPC: B60Q1/52 ,  B60Q5/00 ,  H04W4/46 ,  H04W4/44 ,  G07C5/00 ,  B60W60/00 ,  G06V20/58 ,  G06V20/56

CPC classification number: B60Q1/52 ,  B60Q5/005 ,  H04W4/46 ,  H04W4/44 ,  G07C5/008 ,  B60W60/001 ,  G06V20/58 ,  G06V20/588 ,  B60W2554/408

Abstract: A security system is provided for an autonomous vehicle driving on a road. The autonomous vehicle has a sensor unit for collecting sensor information, and a planning unit for generating planning data for the autonomous vehicle. The security system is characterized by a reception module, configured to receive the sensor information and the planning data; a detection module, configured to detect, based on the sensor information, a driving situation of the autonomous vehicle in which one or more objects on the road cause the autonomous vehicle to slow down; an assessment module, configured to assess the driving situation based on the detection of the driving situation, the sensor information, and the planning data, as a potential plunder incident; and a reaction module, configured to execute, in case of the potential plunder incident, an emergency reaction of the autonomous vehicle.

公开(公告)号：US20240321099A1

公开(公告)日：2024-09-26

申请号：US18187148

申请日：2023-03-21

Applicant: Volvo Car Corporation

Inventor： Oswaldo Perez Barrera

IPC: G08G1/16 ,  B60W30/09 ,  B60W30/095 ,  B60W50/00 ,  B60W50/14 ,  B60W60/00

CPC classification number: G08G1/161 ,  B60W30/09 ,  B60W30/0953 ,  B60W30/0956 ,  B60W50/0097 ,  B60W50/14 ,  B60W60/0015 ,  G08G1/166 ,  B60W2540/221 ,  B60W2552/10 ,  B60W2554/4045 ,  B60W2554/408

Abstract: Various systems and methods are presented regarding utilizing technology onboard a first vehicle to prevent accidents within T-intersections between one or more other vehicles. Techniques are described for tracking vehicles and drivers to prevent accidents from occurring within T-intersections. In an example embodiment, a system, comprises a memory that stores computer executable components; and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise: a vehicle position component that can determine vehicle position data of a second vehicle and a third vehicle proximate a T-intersection; a sensor component that can capture facial profile data of a driver of the second vehicle; and a collision prediction component that can determine whether a collision will occur in the T-intersection between the second vehicle and the third vehicle.

公开(公告)号：US11919545B2

公开(公告)日：2024-03-05

申请号：US17321309

申请日：2021-05-14

Applicant: Perceptive Automata, Inc.

Inventor： Jeffrey D. Zaremba ,  Till S. Hartmann ,  Samuel English Anthony

IPC: B60W60/00 ,  G05D1/00 ,  G05D1/02 ,  G06F18/21 ,  G06F18/2113 ,  G06F18/214 ,  G06F18/40 ,  G06N3/08 ,  G06N5/04 ,  G06N20/00 ,  G06V10/764 ,  G06V10/82 ,  G06V20/40 ,  G06V20/56 ,  G06V20/58 ,  G06V40/20

CPC classification number: B60W60/00272 ,  B60W60/001 ,  G05D1/0221 ,  G05D1/0246 ,  G06F18/2113 ,  G06F18/214 ,  G06F18/217 ,  G06F18/40 ,  G06N3/08 ,  G06N5/04 ,  G06N20/00 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/56 ,  G06V20/58 ,  G06V40/23 ,  B60W2420/42 ,  B60W2420/52 ,  B60W2552/05 ,  B60W2554/4029 ,  B60W2554/4041 ,  B60W2554/4044 ,  B60W2554/4045 ,  B60W2554/4046 ,  B60W2554/408 ,  B60W2554/801 ,  G05D2201/0213

Abstract: A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a filter based on vehicle attributes, traffic attributes, and road attributes. The system identifies a set of video frames associated with ground truth scenarios for validating the accuracy of the machine learning based model and predicts attributes of traffic entities in the video frames. The system analyzes video frames captured after the set of video frames to determine actual attributes of the traffic entities. Based on a comparison of the predicted attributes and actual attributes, the system determines a likelihood of the machine learning based model making accurate predictions and uses the likelihood to generate a navigation action table for controlling the autonomous vehicle.

公开(公告)号：US20240059321A1

公开(公告)日：2024-02-22

申请号：US18446706

申请日：2023-08-09

Applicant: TOYOTA JIDOSHA KABUSHIKI KAISHA ,  DENSO CORPORATION

Inventor： Ryusuke Kuroda

IPC: B60W60/00 ,  B60W50/08 ,  B60W50/14 ,  B60W30/182 ,  B60W40/09 ,  B60W40/04 ,  G06V20/59 ,  G06V20/58

CPC classification number: B60W60/0015 ,  B60W60/0059 ,  B60W60/0053 ,  B60W50/082 ,  B60W50/14 ,  B60W30/182 ,  B60W40/09 ,  B60W40/04 ,  G06V20/597 ,  G06V20/58 ,  B60W2420/42 ,  B60W2540/221 ,  B60W2554/408 ,  B60W2556/40

Abstract: A travel controller autonomously controlling travel of a vehicle, estimating an estimated arrival timing at which the vehicle is expected to arrive at a predetermined location where autonomous control can no longer be continued, starting notification of a transition demand demanding a transition of operation from the autonomous control to manual control a predetermined time period before the estimated arrival timing, ending the transition demand and the autonomous control and starting acceptance of a driving operation when a responsive motion of the driver to the transition demand is detected before the vehicle reaches the predetermined location, and ending the transition demand and the autonomous control and performing safe stopping control of acceleration, deceleration, and steering so that the vehicle stops at a safe position when the vehicle reaches the predetermined location without a responsive motion being detected.

公开(公告)号：US20240025442A1

公开(公告)日：2024-01-25

申请号：US17814356

申请日：2022-07-22

Applicant: Baidu USA LLC

Inventor： Shu JIANG ,  Szu Hao WU ,  Hao LIU ,  Yu CAO ,  Weiman LIN ,  Helen K. PAN

IPC: B60W60/00 ,  B60W40/04 ,  G06N20/00

CPC classification number: B60W60/0011 ,  B60W60/0015 ,  B60W40/04 ,  G06N20/00 ,  B60W2554/4044 ,  B60W2554/408

Abstract: According to some embodiments, systems, methods and media for operating an autonomous driving vehicles (ADV) in an unforeseen scenario are disclosed. In one embodiment, an exemplary method includes determining that the ADV has entered an unforeseen scenario; and identifying one or more surrounding vehicles that are navigating the unforeseen scenario. The method further includes generating a trajectory by mimicking driving behaviors of one or more of the one or more surrounding vehicles; and operating the ADV to follow the trajectory to navigate the unforeseen scenario.

公开(公告)号：US20230278582A1

公开(公告)日：2023-09-07

申请号：US18179954

申请日：2023-03-07

Applicant: WAABI Innovation Inc.

Inventor： Chris Jia Han Zhang ,  Runsheng Guo ,  Wenyuan Zeng ,  Raquel Urtasun

IPC: B60W60/00 ,  G06T7/246 ,  G06T7/73 ,  G05B13/02 ,  B60W50/06

CPC classification number: B60W60/0011 ,  G06T7/246 ,  G06T7/73 ,  G05B13/027 ,  B60W50/06 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/30241 ,  B60W2420/42 ,  B60W2554/408

Abstract: Trajectory value learning for autonomous systems includes generating an environment image from sensor input and processing the environment image through an image neural network to obtain a feature map. Trajectory value learning further includes sampling possible trajectories to obtain a candidate trajectory for an autonomous system, extracting, from the feature map, feature vectors corresponding to the candidate trajectory, combining the feature vectors into the input vector, and processing, by a score neural network model, the input vector to obtain a projected score for the candidate trajectory. Trajectory value learning further includes selecting, from the candidate trajectories, the candidate trajectory as a selected trajectory based on the projected score, and implementing the selected trajectory.

公开(公告)号：US20230267828A1

公开(公告)日：2023-08-24

申请号：US18020522

申请日：2020-08-10

Applicant: Dr. Ing. h.c. F. Porsche Aktiengesellschaft

Inventor： Gabriel Berecz

IPC: G08G1/01 ,  B60W50/00 ,  G08G1/04

CPC classification number: G08G1/0112 ,  B60W50/0097 ,  G08G1/04 ,  B60W2554/4046 ,  B60W2554/408 ,  B60W2420/42 ,  B60W2420/52

Abstract: A method for predicting a trajectory (108) of a vehicle (102) uses first data captured by a first sensor of a first vehicle (101) to determine a first position, a first acceleration, a first velocity and a first yaw rate of a second vehicle (102) and uses second data captured by a second sensor of the first vehicle (101) to determine a second position, a second acceleration, a second velocity and a second yaw rate of the second vehicle (102). The method uses these first and second sets of information with a vehicle model to determine first and second lists of points for predicting the trajectory. One or more parameters of a model for the prediction of the trajectory (108) are determined depending on the first and second lists of points, and the prediction of the trajectory (108) is determined depending on the model defined by these parameters.

公开(公告)号：US11698640B2

公开(公告)日：2023-07-11

申请号：US16917191

申请日：2020-06-30

Applicant: APOLLO INTELLIGENT DRIVING TECHNOLOGY (BEIJING) CO., LTD.

Inventor： Ning Yu ,  Fan Zhu ,  Yongyi Sun

IPC: G05D1/02 ,  B60W30/045 ,  B60W40/04 ,  B60W40/06

CPC classification number: G05D1/0219 ,  B60W30/045 ,  B60W40/04 ,  B60W40/06 ,  G05D1/0221 ,  B60W2530/201 ,  B60W2552/20 ,  B60W2554/408

Abstract: A method and apparatus for determining a turn-round path of a vehicle, a device and a storage medium are provided. An embodiment of the method includes: determining a starting position and a target position for the vehicle to turn round on a road; determining, based at least partially on road information associated with the road and vehicle information associated with the vehicle, a candidate turn-round path between the starting position and the target position; evaluating the feasibility of the candidate turn-round path; and determining, based on the evaluation on the feasibility, a turn-round path by which the vehicle is to turn round on the road.