Autonomous vehicle user interface with predicted trajectories

    公开(公告)号:US11328593B2

    公开(公告)日:2022-05-10

    申请号:US16527495

    申请日:2019-07-31

    Abstract: Systems and methods are provided for generating trajectories for a vehicle user interface showing a driver's perspective view. Methods include generating an ego-vehicle predicted trajectory for an ego-vehicle; and generating at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. After the predicted trajectories are generated, the method continues by determining that at least two predicted trajectories overlap when displayed on the user interface showing a driver's perspective view, when displayed on the user interface showing a driver's perspective view. The method includes modifying the at least one road agent predicted trajectory to remove the overlap. The method then proceeds with updating a display of the user interface to include any modified road agent predicted trajectory. Systems include a trajectory-prediction module to execute the methods.

    Control device and computer readable storage medium

    公开(公告)号:US11322026B2

    公开(公告)日:2022-05-03

    申请号:US16544904

    申请日:2019-08-20

    Abstract: A control device is provided, including a request-information receiving section that receives request information being for requesting transmission of a captured image of an image-capturing target spot and including spot location information indicating the image-capturing target spot and transmitting source information indicating a transmitting source of the request information; a vehicle location information acquiring section that acquires vehicle location information indicating a location of the first vehicle; and a transmission control section that transmits, to the transmitting source indicated by the transmitting source information, a captured image of the image-capturing target spot captured by an image capturing section included in the first vehicle when the first vehicle is located within a predetermined range with the image-capturing target spot as a reference, and broadcasts the request information to a vehicle other than the first vehicle when the first vehicle is located outside the predetermined range, based on the vehicle location information.

    TRAFFIC MANAGEMENT SYSTEM, TRAFFIC MANAGEMENT METHOD, AND TRAFFIC MANAGEMENT PROGRAM

    公开(公告)号:US20220108612A1

    公开(公告)日:2022-04-07

    申请号:US17487160

    申请日:2021-09-28

    Abstract: The plurality of passage areas include a first passage area and a second passage area, the first passage area being a passage area for which a traveling condition for a transportation vehicle carrying an object to be transported is specified, and a second passage area being a passage area for which a traveling condition for restricting traveling of the transportation vehicle more strictly than in the first passage area is specified. The traffic management system includes a traffic management unit configured to change a regulation in at least a part of the second passage area in regard to the permission/prohibition of the traveling of the transportation vehicle based on at least one of information about a demand for the object to be transported and information about a traffic environment.

    Early warning and collision avoidance

    公开(公告)号:US11276311B2

    公开(公告)日:2022-03-15

    申请号:US17087192

    申请日:2020-11-02

    Applicant: DERQ Inc.

    Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

    Determining abnormal traffic conditions from a broadcast of telematics data originating from another vehicle

    公开(公告)号:US11276301B1

    公开(公告)日:2022-03-15

    申请号:US16560541

    申请日:2019-09-04

    Inventor: Gregory Hayward

    Abstract: A computer-implemented method of using telematics data at a destination device is provided. The destination device may be a mobile device associated with a driver, or a smart vehicle controller of a destination vehicle. The telematics data is generated by an originating mobile device (i) having a Telematics Application (or “App”), and (ii) associated with a second driver/vehicle, the telematics data including acceleration, braking, speed, heading, and location data associated with an originating vehicle. The telematics data may be broadcast from the originating mobile device to the destination device that (a) analyzes the telematics data received, (b) determines that an abnormal travel condition exists, and (c) automatically take corrective action that alleviates a negative impact of the abnormal travel condition on the destination vehicle to facilitate safer travel. A usage-based or other insurance discount may be provided based upon insured usage of the telematics data-based risk mitigation or prevention functionality.

    Early warning and collision avoidance

    公开(公告)号:US11257371B2

    公开(公告)日:2022-02-22

    申请号:US16879442

    申请日:2020-05-20

    Applicant: DERQ Inc.

    Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

    Early warning and collision avoidance

    公开(公告)号:US11257370B2

    公开(公告)日:2022-02-22

    申请号:US15994850

    申请日:2018-05-31

    Applicant: DERQ Inc.

    Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

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