Ford Global Technolgoies, LLC

Argo Ai Gmbh

Scott Julian Varnhagen

Alice Kassar

Ramadev Burigsay Hukkeri

Ghassan Atmeh

Bibhrajit Halder

Neal Andrew Seegmiller

Ming Lang Kuang

Schuyler H Cohen

Colen McAlister

David Breeden

Johannes Strom

Pragati Satpute

Daniel Althoff

Bryan Salesky

Timothy Andrew Potts, Jr

Andreas Joachim Knoblach

Meal Seegmiller

Disclosed herein are systems, methods, and computer program products for generating a reference path for an autonomous vehicle. The methods comprising: receiving, by a computing device, a reference trajectory for the autonomous vehicle; generating, by the computing device, a first alternative trajectory for the autonomous vehicle based on an objective identified by the reference trajectory; comparing, by the computing device, the first alternative trajectory to the reference trajectory or a previously generated alternative trajectory; selecting, by the computing device, whether to generate a second alternative trajectory based on a result of said comparing; and generating, by the computing device, the second alternative trajectory for the autonomous vehicle in response to said selecting.

Methods and systems for performing inter-trajectory re-linearization about an evolving reference path for an autonomous vehicle

Systems and methods for generating a trajectory of a vehicle are disclosed. The methods include generating a spatial domain speed profile for a path represented as a sequence of poses of a vehicle between a first point and a second point. Generation of the spatial domain speed profile uses a longitudinal problem while excluding a derate interval on the path when speed of the vehicle cannot exceed a threshold. The methods further include generating a derate profile using the spatial domain speed profile and the derate interval, and transforming the derate interval to a temporal derate interval. The temporal derate interval may include time steps at which the speed of the vehicle cannot exceed the threshold while traversing the path, and may be used as an input to the longitudinal problem for generating a trajectory of the vehicle for navigating between the first point and the second point.

Systems and methods for controlling speed of an autonomous vehicle

Disclosed herein are systems, methods, and computer program products for vehicle path planning. The methods comprise: estimating a current state of a vehicle based on sensor data; generating a control error representing a difference between the estimated current state of the vehicle and a desired state of the vehicle as described by a previously published trajectory; comparing the control error to a threshold value; generating a first plan for the vehicle using an open-loop path planning approach when the control error is below the threshold value or a second plan for the vehicle using a closed-loop path planning approach when the control error is above the threshold value; and causing the vehicle to execute the first or second plan.

Systems and methods for hybrid open-loop and closed-loop path planning

Methods of refining a planned trajectory of an autonomous vehicle are disclose. For multiple cycles as the vehicle moves along the trajectory, the vehicle will perceive nearby objects. The vehicle will use the perceived object data to calculate a set of candidate updated trajectories. The motion planning system will measure a discrepancy between each candidate updated trajectory and the current trajectory by: (i) determining waypoints along each trajectory; (ii) determining distances between at least some of the waypoints; and (iii) using the distances to measure the discrepancy between the updated trajectory and the current trajectory. The system will use the discrepancy to select, from the set of candidate updated trajectories, a final updated trajectory for the vehicle to follow.

Trajectory consistency measurement for autonomous vehicle operation

A system of linearizing a trajectory of an autonomous vehicle about a reference path includes a computing device and a computer-readable storage medium. The computer-readable storage medium includes one or more programming instructions that, when executed, cause the computing device to receive a reference path for an autonomous vehicle, where the reference path defines a proposed trajectory for the autonomous vehicle in a Cartesian reference frame, identify an objective based on the received reference path, where the objective comprises a longitudinal component and a lateral component, project the objective into a curvilinear coordinate frame described by the received reference path, decouple the longitudinal component and the lateral component, linearize the lateral component about the reference path, generate a new reference path for the autonomous vehicle by fusing the linearized longitudinal component and the linearized lateral component, and map the new reference path back to the Cartesian reference frame.

An autonomous mode controller of an autonomous vehicle according to various rider-selectable comfort configurations. When the controller identifies a comfort configuration, it will access a configuration data set that corresponds to the selected comfort configuration. The controller also will receive sensor data from one or more autonomous driving sensors. In response to the received sensor data, the controller will generate an instruction for operation of a steering, braking, powertrain or other subsystem for operation of the autonomous vehicle. The instruction while includes values that correspond to the sensed data and to one or more parameters of the configuration data set. The subsystem will then cause the autonomous vehicle to move according to the instruction.

Rider selectable ride comfort system for autonomous vehicle

A computer that includes a processor and memory that stores instructions executable by the processor. The instructions may include generating, at a host vehicle, a roadway friction map by: detecting a velocity change of a target vehicle; calculating friction data based on the velocity change; and storing the friction data.

Determining friction data of a target vehicle

A computer is programmed to predict, based at least in part on a stored road topology for a predetermined vehicle route, a vehicle body orientation based on lateral, longitudinal, and vertical accelerations predicted for the route. The computer is programmed to, based on the predicted vehicle body orientation, adjust at least one of an orientation of the vehicle body and an orientation of an object in the vehicle as the vehicle traverses the route.

Controlling vehicle orientation

The present invention extends to methods, systems, and computer program products for tracking objects within a dynamic environment for improved localization. Sensing devices are utilized to gather data about a vehicle's environment. In cases where the sensor data has become degraded, such as data indicating that lane lines have become degraded, obscured, or nonexistent, the vehicle computer system uses previously detected sensor data to estimate the speed and direction of travel of moving objects. The computer system then estimates the location of the moving objects after a specified period of time based on the estimated speed and direction of the moving object. The computer system utilizes this information to localize the vehicle within the dynamic environment and to control the configuration of the vehicle.

Tracking objects within a dynamic environment for improved localization

A vehicle and associated method for calculating tire saturation is provided. The method may include the stability control computer calculating slip ratio and longitudinal force for the tire, calculating tire longitudinal stiffness by dividing longitudinal force by slip ratio, calculating tire saturation from tire longitudinal stiffness, and the stability control computer altering dynamic control of the vehicle based on calculated tire saturation. The stability control computer may calculate tire saturation from a tire saturation membership function which includes a first tire longitudinal stiffness value representing an unsaturated tire, a second tire longitudinal stiffness value representing a saturated tire, and a function line connecting the first tire longitudinal stiffness value to the second tire longitudinal stiffness value.

Growing community of inventors

Ann Arbor, MI, United States of America

Scott Julian Varnhagen