1485results about "Steering parts" patented technology

The invention discloses a recirculating ball type electric power steering system fault self-checking method and system and a readable medium, and relates to the technical field of vehicles, and the method comprises the steps: storing a signal transmission path and each function node, determining the type of an influence factor which influences the instruction execution accuracy of the function node, and determining the instruction execution accuracy of the function node; analyzing and acquiring the relationship between the fluctuation amplitude of the data signal at each function node and the numerical value of the influence factor, storing the relationship as a correction model, and storing a first relationship model for reflecting the data association relationship among the function nodes on the same signal transmission path; acquiring real-time data and source data of various impact factors, and generating theoretical response data according to the first relation model, the real-time impact factor data and the correction model; the actual response data is collected, the deviation amplitude between the actual response data and the theoretical response data is calculated, whether the function node breaks down or has a potential fault is judged according to the deviation amplitude, early warning is output, and the fault detection accuracy and the potential fault pre-judgment capability are greatly improved through the technical scheme.

The application discloses an intelligent electric chassis configuration and a fault-tolerant control method of the intelligent electric chassis, and relates to the technical field of electric chassis. The chassis configuration comprises a front axle centralized motor drive assembly, a rear axle distributed motor drive assembly, a front axle electronic hydraulic brake system, a rear axle electronic mechanical brake system and a chassis domain controller. The front axle centralized motor drive assembly comprises a centralized drive motor, a front wheel speed reducer and a drive half shaft which are sequentially connected. The rear axle distributed motor drive assembly comprises a left rear wheel end drive motor and a left rear wheel speed reducer which are sequentially connected, and a right rear wheel end drive motor and a right rear wheel speed reducer which are sequentially connected. The front axle electronic hydraulic brake system comprises a first main brake unit and a redundant brake unit. The rear axle electronic mechanical brake system comprises a second main brake unit. The chassis domain controller is used for controlling the centralized drive motor, the left and right rear wheel end drive motors, the first main brake unit, the redundant brake unit, the second main brake unit, a front axle steer-by-wire system, an intelligent suspension system and an intelligent tire. The application can improve the chassis safety and fault-tolerant capability to support high-level automatic driving functions.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver- the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

In some embodiments, techniques are provided for autonomously backing a vehicle (such as a Class 8 truck) to a trailer. In some embodiments, environment sensors such as image sensors and range sensors mounted to the vehicle detect a trailer and determine distances between the trailer and the vehicle as well as relative angles of the trailer and the vehicle. In some embodiments, the vehicle determines a path to the trailer based on this information, and autonomously controls braking, torque, and / or steering of the vehicle to autonomously back the vehicle along the determined path.

Provided is a parking assistance device including a captured image acquisition unit imaging a road surface around a vehicle and an end detector detecting an end of a ground object on the road surface within a detection area in the captured image. A position calculator calculates position information indicating a positional relationship of the end of the ground object. A boundary line determiner determines whether or not a ground object having the end is a boundary line that defines a parking slot for the vehicle. A removal unit determines whether or not a rear end of a ground object determined as the boundary line by the boundary line determination unit is included in a removal range, determines that a ground object determined as the boundary line is not the boundary line when the rear end is included in the removal range, and excludes the ground object from boundary lines.

Techniques for determining drivable area(s), parking location(s), or other incident areas in an environment are discussed herein. The drivable area(s), parking location(s), and / or other incident areas can be determined by a machine learned model. Training of the machine learned model can be based on sensor data and map data. The sensor data and the map data can be utilized to determine a representation (e.g., a top-down representation) of an environment. The representation can include at least road marking and velocity information associated with a dynamic object in the environment. The sensor data can be utilized to determine the dynamic object. The machine learned model can generate outputs including probabilities that elements of the outputs represent a drivable area, non-drivable area, a parking location, and / or an incident area. The outputs can be utilized to generate a trajectory. The trajectory can be utilized to control a vehicle to traverse the environment.

A signal processing device and a vehicle control device including the same according to an embodiment of the present disclosure includes a processor configured to receive a vehicle internal image from an internal camera, wherein the processor is configured to calculate a forward attention level of a driver based on the vehicle internal image, calculate a time to forward collision or a time to avoid forward collision with an object in front of a vehicle, and change a control time point of forward collision avoidance based on the forward attention level and the time to forward collision or the time to avoid forward collision. Accordingly, adaptive vehicle control may be performed according to the forward attention level of the driver.

A method of autonomously maneuvering a vehicle using environment sensors comprises calculating first coordinate data based on information received from environment sensors mounted on a first portion of the vehicle; determining, based on the first coordinate data, a first target at a first location; determining a path to maneuver the vehicle to the first location; determining and transmitting commands to autonomously control the vehicle to maneuver to the first location; calculating second coordinate data based on information received from environment sensors mounted on a second portion of the vehicle; determining based on the second coordinate data, a second target at a second location, determining a path to maneuver the vehicle from the first location to the second location; and determining and transmitting commands to autonomously control the vehicle to maneuver from the first location to the second location. Suitably configured vehicles (e.g., tractor units) are also described.

This document describes techniques and systems for identifying and selecting a parking spot using radar-centric occupancy grid (RCOG) maps. An example system includes a processor that can identify available parking spots near a host vehicle using sensor data, including a radar occupancy grid (ROG) map. Parking-spot characteristics of each available parking spot are also determined using the sensor data. The processor can then determine a selected parking spot based on the parking-spot characteristics. The processor or another processor can then control operation of the host vehicle to park in the selected parking spot using an assisted-driving or autonomous-driving system and based on the parking-spot characteristics. In this way, the described system can identify, select, and navigate to a parking spot using a RCOG map without having to rely on infrastructure sensors or pass by open spots.

This vehicle includes a lane keeping assistance system and a control device which controls steering of the vehicle, wherein the control device divides a width of a lane in which the vehicle travels into a plurality of virtual lanes and controls the vehicle so that the vehicle travels in one virtual lane among the plurality of virtual lanes. The control device controls the vehicle so that a traveling position of the vehicle is returned to an inside of the one virtual lane when the vehicle traveling in the one virtual lane is about to deviate from the inside of the one virtual lane.

A vehicle auxiliary steering control method, which is applied to a vehicle having a controller, and comprises: in response to the vehicle satisfying a preset auxiliary steering condition, controlling the vehicle to execute an auxiliary steering operation, wherein the auxiliary steering operation comprises adjusting the braking force of an inner front wheel and controlling two rear wheels to slip.

An impairment analysis (“IA”) computer system for detecting an impairment is provided. The IA computer system is associated with a host vehicle, and includes at least one processor in communication with at least one memory device. The at least one processor is programmed to: (i) interrogate or otherwise scan a target vehicle by using a plurality of sensors included on a host vehicle to scan the target vehicle and a target driver; (ii) receive sensor data including target driver data and target vehicle condition data; (iii) analyze the sensor data by applying a baseline model to the sensor data; (iv) detect an impairment of the target driver or target vehicle based upon the analysis; and / or (v) output an alert signal to a host vehicle controller, or direct collision preventing actions (such as automatically engage vehicle safety systems), based upon the determination that the target driver or target vehicle is impaired.

A dual head-up display (HUD) system includes a plurality of on-board sensors, a wireless communication module, a driver monitoring system, and a system controller in electronic communication with the plurality of on-board sensors, the driver monitoring system and the wireless communication module, and adapted to identify parking spaces within proximity to the vehicle, display, with an augmented reality HUD, first information related to identified parking spaces, display, with a reflective HUD, second information related to the identified parking spaces, determine, if the vehicle is performing a parking maneuver, and when the vehicle is performing a parking maneuver into a selected parking space, to display, with the augmented reality HUD, first and second parking assist graphics adapted to provide guidance to a driver of the vehicle while parking the vehicle in the selected parking space.

The invention relates to a method comprising the steps of: providing (S1), from a scenario library, a data set containing information relating to a real traffic scenario from a traffic area such as a multi-storey car park with a central coordination unit for guiding automated vehicles and its own sensor network, carrying out (S2) a simulation with virtual counterparts of guided automated vehicles and non-coordinated road users with a simulated virtual test vehicle, determining (S3) a dissimilarity metric between the data set and trajectories determined in the simulation, and, if the dissimilarity metric is greater than a limit value: repeating (S4) the simulation while replacing the real movement data and / or behavioural models of non-coordinated road users with virtual agent models; adapting (S5), if necessary, the scenario library using synthetic sensor information from the repeated simulation.

A steering model controller in a chassis dynamometer of the disclosure executes a turning determination process of determining whether a driving state of a vehicle is a steering / turning state or a driving straight state based on comparison results between a turning radius for determination and turning radii for comparison calculated based on left steering angle information and right steering angle information. Then, the steering model controller executes a turning control process as a roller control process to be executed in determining that the vehicle is in the steering / turning state. The turning control process is a process of outputting, to a roller driving mechanism, four roller driving commands at which four rollers adapt to the steering / turning state of the vehicle and are rotationally driven.

An automated valet parking method includes: when charging of an electric vehicle is needed, performing: i) before providing a parking space to the electric vehicle, guiding, by a parking infrastructure, the electric vehicle to autonomously drive to a charging service zone, and ii) after charging of the electric vehicle is completed in the charging service zone, guiding, by the parking infrastructure, the electric vehicle to autonomously drive from the charging service zone to a first empty parking space in the parking lot. In particular, guiding the electric vehicle to the charging service zone before providing a parking space to the electric vehicle comprises: setting an empty space in the charging service zone as a first target position; and transmitting to the electric vehicle the first target position and a first guide route that guides the electric vehicle to the empty space in the charging service zone.

The invention relates to a method for path planning during driving maneuvers taking into account the kinematics of a vehicle (100), wherein a driving path Opt (108) runs from a starting point (104) to a destination point (106). First, a route is determined. Opt(108) between a current location (110) taking into account the size (112) of the vehicle (100), its position, its orientation (114) and obstacles (116) surrounding the vehicle (100) such that every possible location of the vehicle (100) is represented by a node (118) and within a graph (120). Each possible connection (122) of the node (118) to the neighboring node (124) represents a possible movement of the vehicle (100) at a current location (110) in the graph (120). Along the graph (120) a search path (128) which includes visited nodes (130) is reduced in terms of its size / length such that for each location a cost function c(n) is determined as a summation of g(n) + h(n) with g(n) = cost at the starting node (104), where h(n) is executed by a neural network (140) with a two-dimensional top-down view.

A parking assistance device for assisting automatic parking of a vehicle includes a determination unit, an obstacle acquisition unit, a prediction unit, and a notification unit. The determination unit determines a parking area for the automatic parking. The obstacle acquisition unit acquires an obstacle around the determined parking area before the automatic parking. The prediction unit predicts an openable amount, by which a door of the vehicle is openable, based on a detection result of the obstacle acquisition unit when the vehicle is to be automatically parked in the determined parking area. The notification unit notifies the openable amount predicted by the prediction unit.

A suspension knuckle includes an upper member including a first end and a second end. The upper member includes a first opening at the second end and a second opening arranged between the first end and the second end. A lower member includes a first end portion and a second end portion. The lower member includes a first passage arranged at the second end portion and a second passage arranged between the first end portion and the second end portion. A first fastener connects the upper member and the lower member and passes through the first passage and the second opening. The first fastener defines a pivot point of the suspension knuckle. A second fastener passes through the second passage and the first opening. The second fastener connects the upper member and the lower member and establishes an amount of pivot of the upper member relative to the lower member.

A method and system quantifies and manages a steering command response delay for an autonomous vehicle. The system enables the method to determine a lag time between issuing a control command and an angle at which the command is implemented for a plurality of predetermined vehicle speeds. For each of a plurality of predetermined vehicle speeds, a predetermined number of lag times is averaged. The average lag time is weighted, wherein a more current lag time has a higher weight than a less current lag time. The average time lag is used to improve the response of the vehicle and detect health issues of the vehicle steering system.

Techniques are described for determining a set of pose information for an object when multiple sets of pose information are determined for a same object from multiple images. An example driving operation method includes obtaining, by a computer located in a vehicle, at least two sets of pose information related to an object located on a road on which the vehicle is operating, where each set of pose information includes characteristic(s) about the object, and where each set of pose information is determined from an image obtained by a camera; determining at least two weighted output vectors; determining, for the object, a set of pose information that are based on a combined weighted output vector that is obtained by combining the at least two weighted output vectors; and causing the vehicle to perform a driving-related operation using the set of pose information for the object.

Embodiments of the present invention provide a control system (100). The control system (100) is for a host vehicle (10) operable in an autonomous mode and a non-autonomous mode. The control system (100) comprises one or more controllers (110). The control system (100) is configured to receive, when operating in a non-autonomous mode, a mode signal and environment data. The mode signal is indicative of the host vehicle (10) operating in a training mode. The environment data is indicative of a sensed environment of the host vehicle (10) during a first manoeuvre by the host vehicle (10) from a first location to a first navigation goal. In the training mode, the one or more controllers (110) identify a navigable area and output vehicle control data. The navigable area is in a vicinity of the first manoeuvre and is suitable to contain a plurality of possible navigation paths for subsequent navigation of the host vehicle (10), operating in an autonomous mode, to a second navigation goal within the navigable area. The second navigation goal is different to the first navigation goal. The navigable area is identified in dependence on the environment data. The vehicle control data is indicative of the navigable area. When subsequently navigating to the second navigation goal in the autonomous mode, the control system (100) utilises the vehicle control data to autonomously control the host vehicle (10).

A driving control method is performed to execute a lane-change control for controlling a host vehicle to autonomously change lanes from a first lane to an adjacent second lane using a processor of a driving control device that controls vehicle speed and steering of the host vehicle traveling in the first lane in an autonomous driving mode. The processor determines that the lane-change control can be executed upon determining that the other vehicle has been detected in a detection zone of the second lane, based on a detection result of a sensor. The processor determines that the lane-change control cannot be executed upon determining that the other has not been detected within the detection zone of the second lane. The processor outputs information regarding whether the lane-change control can be executed.

A sensor arrangement for acquiring a rotational movement of a body that can rotate about a rotational axis has at least three angle sensors and at least one evaluation and control unit. The at least three angle sensors each acquire the mechanical rotational movement of the rotatable body with a predefined transmission ratio and generate a corresponding electrical angle signal and output said angle signal to the at least one evaluation and control unit. The at least three angle sensors have different transmission ratios. The at least one evaluation and control unit are designed to determine a first angle of the rotatable body with a first uniqueness range by way of a first nonius calculation that is based on two electrical angle signals of the at least three electrical angle signals. The first uniqueness range of the determined first angle is greater than uniqueness ranges of the angle signals used for the calculation. The at least one evaluation and control unit is further designed to determine a second angle of the rotatable body with a second uniqueness range by way of a second nonius calculation that is based on the determined first angle and a further electrical angle signal of the at least three electrical angle signals. The second uniqueness range of the determined second angle is greater than the first uniqueness range of the determined first angle and a uniqueness range of the further electrical angle signal. Also disclosed is a method for acquiring a rotational movement of a body that can rotate about a rotational axis which can be carried out using such a sensor arrangement.

Systems and methods are provided for autonomous navigation based on user intervention. In one implementation, a navigation system for a vehicle may include least one processor. The at least one processor may be programmed to receive images acquired by a camera from an environment of a vehicle; determine a navigational maneuver for the vehicle based on analysis of one or more of the plurality of images; cause the vehicle to initiate the navigational maneuver; receive a user input causing an override to alter the initiated navigational maneuver; determine navigational situation information relating to the vehicle via analysis of the images; determine, based on the navigational situation information, whether the user input is associated with a transient condition; and when the user input is not associated with a transient condition, store the navigational situation information in association with information relating to the user input.

An electric boat running on land is similar to a boat in water in appearance, is an electric entertainment apparatus, is suitable for being used in occasions such as amusement parks and parks, and is characterized in that the electric boat running on land is realized by utilizing two universal wheels and two driving wheels at the bottom of the boat, and the electric boat is controlled to run in two ways, namely, paddle rowing and supporting rod supporting; according to paddle rowing, paddles on the boat are used for simulating the action of rowing in water to control the boat, the paddles do not make contact with the road surface, only the boat is controlled to go straight, stop, turn left and turn right, power is not provided for driving of the boat, and a gear speed increasing type power generation device is arranged in a paddle assembly. The supporting rod boat supporting means that a matched supporting rod is used for simulating the action of supporting the boat in water to control the boat, the probe end of the supporting rod makes contact with the road surface, the supporting rod boat supporting only controls the boat to go straight, stop, turn left and turn right instead of providing power for driving of the boat, and a resistance type pressure sensor is arranged in a supporting rod assembly.

A method for deactivating a remote automatic parking mode of a vehicle in a parking garage. The vehicle being equipped with a tire monitoring system, including wheel units mounted in each wheel of the vehicle and each being provided with an accelerometer measuring a radial component of an acceleration of the wheel and being dependent on a terrestrial gravitational field. The vehicle being provided with an automatic parking mode remotely controlled by portable equipment carried by a user. The method includes, if the conditions for activating the measurements of the wheel units are verified: each wheel unit measuring acceleration values over time; comparing said values with a threshold value, for each wheel unit; if the acceleration values of at least two wheel units exceed said threshold value, then: detecting any movement of said vehicle in a parking garage; and deactivating the remote automatic parking mode.

There is disclosed a control system and a method for a host vehicle operable in an autonomous mode. The control system comprises one or more controllers. The speed and / or path of the vehicle in the autonomous mode is appropriate to a driving context.