ADAPTIVE DRIVER LANE KEEPING ASSIST CONTROL

    公开(公告)号:US20250058830A1

    公开(公告)日:2025-02-20

    申请号:US18451278

    申请日:2023-08-17

    Abstract: A system includes a neural network module, a lane keeping assist (LKA) module, and a control module. The neural network module is configured to receive driver data, identify the driver, receive non-driver data, and generate a lane assist offset value specific to the identified driver based on the non-driver data and the driver data. The LKA module is configured to receive the lane assist offset value, receive vehicle data associated with one or more parameters of the vehicle while the vehicle is moving, the one or more parameters including a steering angle, a velocity, and a vehicle position between lane markings, and generate a steering angle control signal based on the received lane assist offset value and vehicle data. The control module is configured to control steering of the vehicle based on the generated steering angle control signal. Other example systems and methods are also disclosed.

    BEHAVIOR VERIFICATION FOR FINITE STATE MACHINE-MODELED SYSTEMS

    公开(公告)号:US20240427689A1

    公开(公告)日:2024-12-26

    申请号:US18339768

    申请日:2023-06-22

    Abstract: A method for verifying system behavior and correcting design flaws in a finite state machine (FSM)-modeled system or any other representational method that includes receiving from a user device via a model verification platform, data associated with the system design. The data describes states, state transitions, events, and outputs of the FSM-modeled system. The method includes searching the data for predetermined behavior of the FSM-modeled system, including predetermined state(s) and/or mode changes. The method includes flagging the predetermined behavior as a verified behavior and performing a control action in response to the verified behavior, including transmitting a notification to the user device that is indicative of the verified behavior, and a design recommendation where applicable. Instructions for the method may be recorded in a computer readable storage medium and executed by a processor to cause the model verification platform to perform the method.

    Externally illuminated steering wheel for vehicle mode indication

    公开(公告)号:US11654825B1

    公开(公告)日:2023-05-23

    申请号:US17979138

    申请日:2022-11-02

    CPC classification number: B60Q3/283 B62D1/04

    Abstract: A system for indicating an operating mode of a motor vehicle having a vehicle interior and an operator seat arranged therein includes a rotatable steering wheel arranged inside the vehicle interior relative to the operator seat. The steering wheel includes a front side facing the operator seat and an opposing back side. The system additionally includes a light source configured to project a beam of light onto the back side of the steering wheel. The back side of the steering wheel is configured to capture the light beam and illuminate therewith the front side of the steering wheel to thereby generate a sensory signal indicative of the operating mode to a vehicle operator positioned in the operator seat. A motor vehicle employing the system for generating a sensory signal to a vehicle operator for indicating an operating mode of the vehicle is also disclosed.

    DESIGN OPTIMIZATION FOR FINITE STATE MACHINE MODELED SYSTEMS

    公开(公告)号:US20250013878A1

    公开(公告)日:2025-01-09

    申请号:US18347841

    申请日:2023-07-06

    Abstract: A supportive software-based “toolbox” for optimizing finite state machine (FSM)-modeled systems. The optimization may include defining a plurality of alternative models for the FSM-modeled system and iterating one or more of the domain alternative into iterated alternatives. The optimization may include generating a plurality of stateflow representations for the FSM-modeled system according to the iterated alternatives, and based thereon, generating a model score for each of the stateflow representations predictively ranking the stateflow representations based at least in part on one or more of user experience, usability, correctness, transformability, effectiveness, and readiness.

Patent Agency Ranking