A computer implemented method for lateral control of a vehicle comprises the following steps carried out by computer hardware components: determining a location error of the vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally.

Techniques for determining a degraded state associated with a sensor are discussed herein. For example, a sensor associated with vehicle may captured data of an environment. A portion of the data may represent a portion of the vehicle. Data associated with a region of interest can be determined based on a calibration associated with the sensor. For example, in the context of image data, image coordinates may be used to determine a region of interest, while in the context of lidar data, a beam and/or azimuth can be used to determine a region of interest. A data metric can be determined for data in the region of interest, and an action can be determined based on the data metric. For example, the action can include cleaning a sensor, scheduling maintenance, reducing a confidence associated with the data, or slowing or stopping the vehicle.

A system and method including receiving a plurality of messages generated by a vehicle, each of the messages being associated with an indicated topic; initializing one or more state machines, each state machine preconfigured with a one or more specified state parameters to define a specific scenario, the initializing commencing an execution of the one or more state machines; querying the plurality of messages by the one or more state machines, each state machine querying for messages having an indicated topic associated with the querying state machine; updating, at one or more of a sequence of time intervals of a time period, the one or more state machines based on state transitions determined for each state machine; updating, based on each of the one or more state machines, a scenario record for each of the one or more state machines; and storing the updated scenario record in a data store.

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.

Techniques for a pose component that may determine a pose are described herein. A pose may refer to the inertial pose or position of a vehicle which may be updated in real-time or near real-time. For example, the techniques may include receiving a plurality of input signals at a pose component and monitoring the plurality of input signals. The pose component may determine, based on the monitoring of the plurality of input signals, a particular pose update algorithm of a plurality of pose update algorithms for determining the pose and determine, using the particular pose update algorithm, the pose based the plurality of input signals and IMU measurements associated with a primary IMU.

In case a vehicle speed control is performed in response to a failure in a steer-by-wire steering system, the vehicle is prevented from accelerating following a speed reduction caused by a braking operation of the vehicle operator. The speed limit control limits a traveling speed of the vehicle below an upper limit speed upon detecting a fault in the steering system, and is configured to set a target deceleration of the vehicle according to the limited traveling speed, perform a deceleration control to bring an actual deceleration of the vehicle to become near the target deceleration, and restrict the actual deceleration from changing to an acceleration side in the deceleration control.

Performance anomalies in autonomous vehicle can be difficult to identify, and the impact of such anomalies on systems within the autonomous vehicle may be difficult to understand. In examples, systems of the autonomous vehicle are modeled as nodes in a probabilistic graphical network. Probabilities of data generated at each of the nodes is determined. The probabilities are used to determine capabilities associated with higher level functions of the autonomous vehicle.

A vehicle corner module (VCM) is provided for regulating motion of a host vehicle which comprises a vehicle-on-board vehicle-controller. The VCM comprises a sub-frame mountable to a reference frame of the host vehicle; a wheel-hub assembly comprising a wheel-hub; VCM-sub-systems mediating between the sub-frame and the wheel-hub assembly, e.g., a drive subsystem, a steering subsystem, a suspension subsystem and/or a braking subsystem; and an VCM-onboard VCM-controller, comprising one or more processors and a computer-readable medium storing program instructions that, when executed by the one or more processors, cause the one or more processors to establish a communication link with a vehicle-controller, including electronically transferring information about the VCM from the VCM-controller to the vehicle-controller, and to perform, in response to an installation of the VCM on a vehicle, a post-installation validation-process that includes validating the VCM-subsystems and communicating a result of the validating to the vehicle-controller.

In a vehicle control device, a reference route generator obtains point-series information including information on sets of coordinates through which a subject vehicle needs to travel, and approximates, by polynomials each being a function of a route length from a preset reference point, a longitudinal position and a lateral position of the subject vehicle based on the sets of coordinates to generate a reference route represented by the polynomials. A planned traveling distance computing unit calculates a planned traveling distance being a distance that the subject vehicle needs to travel in a unit time of a predefined length. A target value computing unit calculates a target position being a target value of a position of the subject vehicle after the unit time, based on the polynomials of the longitudinal position and the lateral position of the subject vehicle, and the planned traveling distance.

An electronic control device provided in a vehicle that mounts an in-vehicle system is provided. The electronic control device may detect an abnormality that occurs in the in-vehicle system. The electronic control device may detect an operation related to a lane change. The electronic control device may store a travel plan for performing an autonomous driving of the vehicle. The electronic control device may acquire at least one of a subject vehicle information item on the vehicle, a surrounding information item on a surrounding environment of the vehicle, and a driver information item on a driver.