A traveling control apparatus of vehicle includes a lane change controller, a position detector, and a lane detector. The lane change controller includes first and second course generators that respectively generate first and second courses as target courses of a vehicle in first and second lanes. The first and the second course generators respectively calculate first and second target movement amounts, in width directions of the first and the second lanes, of the vehicle when the vehicle is moved along the first and the second courses, and respectively generate the first and the second courses on a basis of the first and the second target movement amounts and first and second jerks. The first and the second jerks are each a rate of change of acceleration of the vehicle in the width direction of the first lane in the first course or the second lane in the second course.

A lane information detection unit detects the shape and the road width of a traveling lane of a vehicle. A present transverse position detection unit detects a present transverse position indicating a present traveling position of the vehicle in the width direction of the traveling lane. A driver-corresponding transverse position setting unit sets a driver-corresponding transverse position corresponding to a driving tendency of a driver. An upper/lower limit value setting unit sets upper/lower limit values that the driver-corresponding transverse position can take, in accordance with the road width. Then, when change in the road width is detected, a transverse position control amount calculation unit sets, as a target transverse position, the driver-corresponding transverse position within the upper/lower limit values in which the change is reflected, and calculates a transverse position control amount for the vehicle from the present transverse position of the vehicle.

A method for partially or fully autonomously guiding a motor vehicle includes setting a target steering angle for guiding along a target trajectory. It is checked whether a zero point shift exists between a current position of the motor vehicle with respect to the target trajectory. The set target steering angle is adjusted on the basis of a correction constant in the event that a determined zero point shift exceeds a predefined threshold.

An automatic steering control apparatus includes a target-path acquisition unit that acquires a target path that is to be a traveling path of the vehicle, a target-rudder-angle acquisition unit that acquires a target rudder angle that is to be a rudder angle in the vehicle, on the basis of the target path, a sideslip-angle estimation unit that estimates a sideslip angle in the vehicle that is traveling at the target rudder angle, on the basis of the target rudder angle and a vehicle condition of the vehicle, and an automatic steering control unit. The automatic steering control unit performs at least one of stopping of automatic steering control and controlling of a steering-quantity regulation gain for regulating the target rudder angle, when the estimated sideslip angle is equal to or greater than a predetermined value.

The present disclosure relates to an unmanned lane keeping method and device, a computer device, and a storage medium. The method includes that: a vehicle road image collected by a data collector of the vehicle is received; the vehicle road image is transmitted to a preset DNN model of the vehicle for processing to obtain a steering wheel angle corresponding to the vehicle road image, wherein the DNN model of the vehicle is established by deep learning, and is used for characterizing a correspondence between the vehicle road image and the steering wheel angle; and the vehicle is controlled to keep driving in a corresponding lane according to the steering wheel angle.

A method for estimating a longitudinal force difference ΔFx acting on steered axle wheels of a vehicle, the method comprising obtaining data from the vehicle related to an applied steering torque M.sub.steer associated with the steered axle wheels, obtaining a scrub radius value r.sub.s associated with the steered axle wheels, and estimating the longitudinal force difference ΔFx, based on the obtained data and on the scrub radius r.sub.s, as proportional to the applied steering torque M.sub.steer and as inversely proportional to the scrub radius r.sub.s.

Methods, apparatus, systems and articles of manufacture are disclosed for vehicle steering to follow a curved path. An example apparatus includes interface circuitry to determine vehicle data of a vehicle, navigation manager circuitry to determine navigation data of the vehicle, and tracking mode controller circuitry to: determine the vehicle is approaching a curve based on the navigation data, in response to determining the vehicle is approaching a curve: determine a wheel steering angle utilizing the navigation data and the vehicle data, the wheel steering angle corresponding to the curve, determine a heading error offset adjustment utilizing the navigation data and the vehicle data, and generate steering commands based on the wheel steering angle and the heading error offset, the steering commands to control the vehicle to reduce control errors and follow the wheel steering angle.

A driving support device that controls a steering unit such that a hitch angle between a tow vehicle, which tows a towed vehicle, and the towed vehicle becomes a target angle set as a target includes: an image control unit that causes a display unit to perform display of a captured image obtained by an imaging unit provided in the tow vehicle or the towed vehicle in a mirror image state and display of a setting image including a slider indicating the target angle input through an input unit; an acquisition unit that acquires input of the target angle at the time of backward movement of the tow vehicle from the input unit, in a state where the setting image is displayed; and a setting unit that sets the target angle based on the input.

Systems and methods are provided for navigating a host vehicle. In one implementation, a system may include at least one processor configured to receive at least one image acquired by an image capture device, the at least one image being representative of an environment of the host vehicle; analyze the at least one image to identify at least one characteristic associated with the environment of the host vehicle; determine a navigational action for the host vehicle based on: the at least one characteristic associated with the environment of the host vehicle, and a steering limit corresponding to a maximum allowable lateral acceleration for the host vehicle; and cause one or more actuators associated with the host vehicle to implement the determined navigational action.

Techniques are described herein for generating trajectories for autonomous vehicles using velocity-based steering limits. A planning component of an autonomous vehicle can receive steering limits determined based on safety requirements and/or kinematic models of the vehicle. Discontinuous and discrete steering limit values may be converted into a continuous steering limit function for use during on-vehicle trajectory generation and/or optimization operations. When the vehicle is traversing a driving environment, the planning component may use steering limit functions to determine a set of situation-specific steering limits associated with the particular vehicle state and/or driving conditions. The planning component may execute loss functions, including steering angle and/or steering rate costs, to determine a vehicle trajectory based on the steering limits applicable to the current vehicle state.