DRIVING ASSISTANCE DEVICE AND DRIVING ASSISTANCE METHOD

    公开(公告)号:US20240273920A1

    公开(公告)日:2024-08-15

    申请号:US18562754

    申请日:2022-02-04

    Abstract: A driving assistance device that recognizes a lane marking around an own vehicle with at least one sensor includes a lane marking detection unit that detects lane marking information from data acquired by the sensor, a lane marking type candidate estimation unit that recognizes a lane marking type from the detected lane marking information and calculates a likelihood of each lane marking type, a lane marking type branch point estimation unit that detects a lane marking type branch point that is a point at which a likelihood of the lane marking type changes with respect to an advancing direction of the own vehicle, and distinguishes regions before and after the lane marking type branch point as a first region and a second region, and a lane marking information integration unit that, in a case where a lane marking of the first region and a lane marking of the second region have the same lane marking type, integrates the lane marking of the first region and the lane marking of the second region into a continuously recognizable lane marking.

    DIVIDING LINE RECOGNITION DEVICE
    3.
    发明公开

    公开(公告)号:US20240005673A1

    公开(公告)日:2024-01-04

    申请号:US18254637

    申请日:2021-09-21

    Abstract: An object of the present invention is to provide a dividing line recognition device capable of generating dividing line information including a dividing line of a portion that cannot be detected by a sensor in a form in which reliability is added to each portion of the dividing line. A dividing line recognition device (100) of the present invention includes: a dividing line information acquisition unit (101) configured to acquire dividing line information around an own vehicle; a target information acquisition unit (103) configured to acquire target information around the own vehicle; an other vehicle state estimation unit (104) configured to estimate a state of another vehicle on the basis of the target information; a first dividing line generation unit (102) configured to generate a first dividing line (30B) from the dividing line information; a second dividing line generation unit (108) configured to extend the first dividing line to generate a second dividing line (40); a third dividing line generation unit (110) configured to generate a third dividing line (60) on the basis of a positional relationship between a traveling trajectory of the other vehicle and the first dividing line; and an output dividing line construction unit (111) configured to construct an output dividing line to be output as a dividing line using at least one of the first dividing line, the second dividing line, or the third dividing line.

    TRAVEL ASSISTANCE DEVICE AND TRAVEL ASSISTANCE METHOD

    公开(公告)号:US20250128738A1

    公开(公告)日:2025-04-24

    申请号:US18834178

    申请日:2022-02-24

    Abstract: A travel assistance device includes: a detection result storage unit that stores a detection result of an external sensor installed in a host vehicle; a moving object recognition unit that recognizes a surrounding moving object based on a detection result of the external sensor; a route storage unit that stores a route along which the host vehicle has moved based on vehicle information acquired by a vehicle sensor installed in the host vehicle; an initial stop position determination unit that determines an initial position at which the host vehicle has stopped before starting, based on the detection result stored in the detection result storage unit; and a vehicle control unit that stops the host vehicle based on a recognition result of the moving object recognition unit after the host vehicle starts from the initial position. The detection result storage unit stores at least the initial position and the detection result on the route. The vehicle control unit controls movement on the route from a stop position where the host vehicle is stopped to the initial position based on a detection result of the external sensor at a current position of the host vehicle and a detection result of the external sensor stored in the detection result storage unit.

    TARGET CALCULATION METHOD AND COMPUTING DEVICE

    公开(公告)号:US20250061724A1

    公开(公告)日:2025-02-20

    申请号:US18723730

    申请日:2022-08-24

    Abstract: A target calculation method is a target calculation method executed by a computing device including an acquisition unit that acquires a sensor output that is an output of a sensor that acquires information on a surrounding environment, target calculation method including: detection processing of detecting a target by a plurality of techniques using the sensor output and detecting a target state including at least a position and a type of the target; same target determination processing of determining a same target from a plurality of the targets detected by each of the plurality of techniques in the detection processing; and merging processing of merging the target states of the target determined to be the same target in the same target determination processing and outputting the merged target states as a merged target.

    Sensor Information Processing Device

    公开(公告)号:US20220254170A1

    公开(公告)日:2022-08-11

    申请号:US17629442

    申请日:2020-07-21

    Abstract: Provided is a sensor information processing device that processes the detection results of the plurality of external-environment sensors that recognize the lane marker that divides the lane and can identify the lane marker more accurately than before. A sensor information processing device 100 includes a storage device 102 that stores a past detection result De of an external-environment sensor 200 as time-series data, and a central processing unit 101 that identifies a lane marker on the basis of the time-series data. The central processing unit 101 determines that the new detection result De belongs to the existing lane marker or the new lane marker on the basis of the comparison between the new detection result De not included in the time-series data and the time-series data.

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