Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

A method for controlling vehicle travelling includes: detecting a plurality of travelling states of a vehicle, the plurality of travelling states includes a plurality of travelling directions; respectively previewing the vehicle travelling along the plurality of travelling directions from an original position in a lane to obtain a plurality of previewing paths; fitting a plurality of turning paths of the vehicle travelling from the original position to a target path in the lane according to the plurality of previewing paths; using the plurality of turning paths to calculate change information of a plurality of steering wheel angles; and adjusting the plurality of travelling directions according to the change information of the steering wheel angles, so as to control the vehicle to travel from the original position to the target path along the turning path.

A computer includes a processor and a memory storing instructions executable by the processor to receive data indicating a lane change by a first vehicle that is towing a second vehicle, the data including data indicating a direction that first wheels of the first vehicle are turning while the first vehicle is performing the lane change; and during the lane change, instruct a steering system of the second vehicle to turn second wheels of the second vehicle in a same direction as the first wheels.

Among other things, we describe techniques for operation of a vehicle based on measured load characteristics and/or passenger comfort. One or more sensors of the vehicle can measure passenger data and/or load data of the vehicle. The passenger data and/or load data of the vehicle can be used by the vehicle to determine how to navigate within the surrounding environment.

A method for monitoring vehicle inertia parameters in real-time includes receiving at least one lateral dynamic value. The method also includes calculating at least one vehicle inertia parameter value using the at least one lateral dynamic value. The method also include determining a difference between the calculated at least one vehicle inertia parameter value and a corresponding baseline vehicle inertia parameter value. The method also includes, based on a comparison between the difference between the calculated at least one vehicle inertia parameter value and the corresponding baseline vehicle inertia parameter value and a threshold, selectively controlling at least one vehicle operation based on the calculated at least one vehicle inertia parameter value.

A method for updating a localization of an autonomous vehicle includes receiving perception input data from a sensor of the autonomous vehicle and receiving map data including road lane information in a vicinity of the autonomous vehicle. The method includes processing the perception input data to extract perceived road lane information including a perceived x position, a perceived y position, a perceived z position, a perceived lane type, a perceived lane color, and a perceived lane curvature and processing the map data to extract map road lane information including a map x position, a map y position, a map z position, a map lane type, a map lane color, and a map lane curvature. The method includes calculating a transformation matrix from the perceived road lane information and the map road lane information and updating the map data and a localization of the vehicle based on the transformation matrix.

Controlling the speed of a motor vehicle with an adaptive cruise control system in a curve can include dynamically adjusting the speed of the motor vehicle depending on the planned exit from the roundabout and the current position of the motor vehicle.

Systems and methods for general driving behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes a trailer, at least one perception sensor, a non-transitory computer readable medium, and a processor. The processor is configured to estimate a grade of the roadway based on the perception data, provide a first control input to the autonomous vehicle based on the grade of the roadway, determine a response of the autonomous vehicle to the first control input based on the perception data, estimate a trailer load of the trailer based on the response of the autonomous vehicle to the first control input, and provide a second control input to the autonomous vehicle based on the grade of the roadway and the trailer load.

A high precision digital map is pre-developed and stored in a memory of an in-vehicle control computer on an autonomous vehicle. The digital map is updated by the in-vehicle control computer with detected roadway data that is a fusion of roadway perception data from at least one perception sensor on the autonomous vehicle and real time GPS signal from at least one GPS receiving devices on the autonomous vehicle. The updated digital map is transferred to a remote oversight system via a network communication subsystem, and the oversight system distributes the updated digital map to other autonomous vehicles connected over the network communication subsystem.

Systems and methods for detecting physical infrastructure related to navigation of an autonomous vehicle are disclosed. In one aspect, the autonomous vehicle includes a perception sensor configured to generate perception data, a non-transitory computer readable medium, and a processor. The processor is configured to determine a minimal risk condition (MRC) maneuver for the autonomous vehicle to execute, identify a safe zone in which the autonomous vehicle is able to execute the MRC maneuver by coming to a stop based on the perception data, identify one or more exclusion zones within the safe zone based on the perception data, and control the autonomous vehicle to execute the MRC maneuver including stopping outside of the exclusion zone.