A method and apparatus for defining a model to determine a corrected trajectory of a mobile device or vehicle and a method and apparatus for determined a corrected trajectory using a defined model are provided. The model for determining a corrected trajectory includes accessing ground truth location data for a selected pathway, determining a GNSS pathway of a mobile device or vehicle, determining an IMU pathway of a mobile device or vehicle, and calculating an aggregated displacement trajectory. The apparatus for defining the model includes a communication interface configured to receive a first and second pathway, a memory configured to store a model and ground truth location data, and a processor to train the model.

An inertial measurement unit including a support structure having rectangular cuboid configuration, a first sensor configured to detect a first angular rate wherein the first sensor is affixed to a first side of the support structure, a second sensor configured to detect a second angular rate wherein the second sensor is affixed to a second side of the support structure, a third sensor configured to detect a third angular rate wherein the third sensor is affixed to a third side of the support structure, a processor configured to generate an aggregate angular rate in response to the first angular rate, the second angular rate and the third angular rate, and a vehicle controller configured to control a vehicle in response to the aggregate angular rate.

A method for detecting a standstill of a vehicle includes detecting the standstill of the vehicle using at least one sensor, and, when the standstill is detected using the at least one sensor, carrying out a test routine for checking the standstill of the vehicle. The test routine uses at least one signal from at least one rate-of-rotation sensor as an input value. The method further includes rejecting the detected standstill of the vehicle when the at least one signal from the at least one rate-of-rotation sensor indicates that there is no standstill of the vehicle.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

Particular embodiments may enable configuring settings of a vehicle in a designated mode. A signal to place the vehicle in a designated mode may be received. A roll angle and a pitch angle of the vehicle as parked may be assessed based on data received from a position sensor built into the vehicle. Signals to adjust an electronically controlled suspension of the vehicle to reduce the roll angle or the pitch angle so that the vehicle is level as parked may be sent based on the assessed roll angle and pitch angle exceeding a threshold value. One or more settings of the vehicle to change default operating characteristics by the vehicle while in the designated mode may be modified.

A vehicle control device controls travel of a vehicle by performing state transition for a plurality of control states having different driving assistance levels based on vehicle surrounding information. The vehicle control device comprises: an acquisition unit configured to acquire the vehicle surrounding information; and a control unit configured to control the state transition and braking operation of the vehicle based on the information acquired by the acquisition unit, wherein, based on the information, the control unit is configured to transition from a first control state set for travel of the vehicle to a second control state with a lower driving assistance level in a case where it is determined that another vehicle is crossing a lane line in front of the vehicle in a lane where the vehicle is traveling.

The braking control device includes a control amount derivation unit that derives a target vehicle braking force representing a target value of a vehicle braking force applied, and a braking control unit that controls a regenerative braking device and a frictional braking device based on the target vehicle braking force. When the target vehicle braking force is increased, the braking control unit executes a braking force application process of increasing the frictional braking force applied to the wheel so that such frictional braking force becomes larger than the regenerative braking force applied to the wheel. When the target vehicle braking force is increased, the braking control unit executes a switching process of switching at least a part of the frictional braking force applied to the wheel to the regenerative braking force to increase the regenerative braking force applied to the wheel after execution of the braking force application process.

A method of autonomous vehicle control, comprising: receiving an image of a lenticular human-imperceptible marker embedded in an element of an environment that an autonomous vehicle is moving in, the marker having a pattern usable for determining positional data of the moving vehicle, the image captured using human-invisible light, analyzing the received image of the human-imperceptible marker, and controlling the autonomous vehicle based on the analyzed image of the human-imperceptible marker.

A slope estimation device estimates a slope of a vehicle traveling road, and includes an input section that acquires a detected value of an acceleration sensor for detecting acceleration in a front-back direction of the vehicle, a centripetal force detecting section that detects centripetal force acting on the acceleration sensor due to a turning motion of the vehicle, and a slope computing section that computes the slope of the vehicle traveling road based on the detected value of the acceleration sensor. When the vehicle is in the turning motion, the slope computing section computes the slope of the traveling road by determining a component of the centripetal force superimposed on the detected value of the acceleration sensor based on a turning center position of the vehicle, a gravity center position of the vehicle, and an installation position of acceleration sensor, and subtracting the component of the centripetal force from the detected value of the acceleration sensor.

Methods and systems implemented in a vehicle involve obtaining a single camera image from a camera arranged on the vehicle. The image indicates a heading angle ψ.sub.0 between a vehicle heading x and a tangent line that is tangential to road curvature of a road on which the vehicle is traveling and also indicates a perpendicular distance y.sub.0 from a center of the vehicle to the tangent line. An exemplary method includes obtaining two or more inputs from two or more vehicle sensors, and estimating kinematic states of the vehicle based on applying a Kalman filter to the single camera image and the two or more inputs to solve kinematic equations. The kinematic states include roll angle and pitch angle of the vehicle.