Abstract: Systems and methods are provided for generating a vehicle path to operate an autonomous vehicle. A method includes using a lateral re-entry planner system to correct for a lateral reentry error. A longitudinal re-entry planner system is used to correct a longitudinal reentry error. Path correction commands are generated based upon the corrections provided by the lateral re-entry planner system and the longitudinal re-entry planner system.

Abstract: Systems and methods are provided for controlling an autonomous vehicle. A method includes using a lateral controller system for determining a vehicle's curvature. A longitudinal controller system is used for determining desired vehicle acceleration. The longitudinal controller system uses a control loop with respect to a velocity error and a feedforward term. Commands are generated based on the output of the lateral controller system and the longitudinal controller system.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: receiving a current position of the vehicle along a determined path; retrieving map information that includes a pitch and a curvature of a roadway at or near the current position; determining, based on the map information, a planned pitch and a planned roll of the vehicle at or near the current position; determining, based on the planned pitch and the planned roll, a location of the field of view of the sensing device; determining, based on the location of the field of view and a location of an area of interest, an amount of movement of the sensing device to align the field of view with the area of interest; and generating, one or more control signals to one or more actuators associated with the sensing device based on the determined amount of movement.

Abstract: A method includes identifying a current position of the vehicle, using sensor data; generating, via a processor, an initial corridor seeding based upon the current position of the vehicle and physical characteristics of the road, without consideration of any other objects on the roadway; identifying a plurality of objects along a first side of the roadway, the first side including a side of the roadway in which the vehicle is traveling, using the sensor data; generating, via the processor, a target first boundary for the corridor based on the identified plurality of objects along the first side of the roadway; generating, via the processor, a target second boundary on a second side of the roadway, opposite the first side; and adjusting, via the processor, the initial corridor seeding based on the target first and second boundaries, thereby generating the corridor of travel for the vehicle along the roadway.

Abstract: A system and method for providing routing instructions to one or more autonomous vehicles includes identifying a destination of an autonomous vehicle; identifying a starting position or an initial location of the autonomous vehicle; receiving autonomous vehicle sensor data; receiving one or more routing goals for a routing plan for the autonomous vehicle; generating one or more route modification parameters; and generating a route plan for the autonomous vehicle based on (a) the destination, (b) the starting position or the initial location, (c) the one or more route modification parameters and (d) the one or more routing goals.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a controller onboard the vehicle, a lateral plan for the operating vehicle along a route; obtaining, by the controller, pitch data pertaining to the lateral plan; and determining, by the controller, a longitudinal plan for operating the vehicle along the route based on the pitch data and the lateral plan, wherein the pitch data influences a planned rate of longitudinal movement of the vehicle at one or more points along the lateral plan. In this regard, the planned vehicle velocity or acceleration at a point in the future may be constrained by pitch data corresponding to the expected vehicle location at that point in the future.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: receiving a current position of the vehicle along a determined path; retrieving map information that includes a pitch and a curvature of a roadway at or near the current position; determining, based on the map information, a planned pitch and a planned roll of the vehicle at or near the current position; determining, based on the planned pitch and the planned roll, a location of the field of view of the sensing device; determining, based on the location of the field of view and a location of an area of interest, an amount of movement of the sensing device to align the field of view with the area of interest; and generating, one or more control signals to one or more actuators associated with the sensing device based on the determined amount of movement.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: monitoring a health of the vehicle; generating a first driving plan; generating a second driving plan configured to bring the vehicle to a stop at a predetermined rate; commanding the vehicle to execute the first driving plan in response to the health of the vehicle staying above a predetermined health threshold; and commanding the vehicle to execute the second driving plan in response to the health of the vehicle falling below the predetermined health threshold.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a controller onboard the vehicle, a lateral plan for the operating vehicle along a route; obtaining, by the controller, pitch data pertaining to the lateral plan; and determining, by the controller, a longitudinal plan for operating the vehicle along the route based on the pitch data and the lateral plan, wherein the pitch data influences a planned rate of longitudinal movement of the vehicle at one or more points along the lateral plan. In this regard, the planned vehicle velocity or acceleration at a point in the future may be constrained by pitch data corresponding to the expected vehicle location at that point in the future.

Abstract: Systems and method are provided for controlling an autonomous vehicle. In one embodiment, a method includes: receiving sensor data from one or more sensors of the vehicle; processing, by a processor, the sensor data to determine a cyclist in proximity to the vehicle; in response to the determined cyclist, selecting, by the processor, a behavioral mode from a plurality of behavioral modes; adjusting, by the processor, at least one control parameter based on the selected behavioral mode; and controlling the autonomous vehicle and/or a notification light based on the at least one control parameter.

Abstract: Systems and methods are provided for generating a vehicle path to operate an autonomous vehicle. A method includes using a lateral re-entry planner system to correct for a lateral reentry error. A longitudinal re-entry planner system is used to correct a longitudinal reentry error. Path correction commands are generated based upon the corrections provided by the lateral re-entry planner system and the longitudinal re-entry planner system.

Abstract: Systems and methods are provided for generating a vehicle path to operate an autonomous vehicle. A method includes a lateral spatial plan being generated by applying a lateral-related optimization model to lateral pre-planning data. A longitudinal temporal plan is generated by applying a longitudinal-related optimization model to longitudinal pre-planning data. A vehicle path is created by fusing the lateral spatial plan with the longitudinal temporal plan.

Abstract: Systems and methods are provided for controlling an autonomous vehicle. A method includes using a lateral controller system for determining a vehicle's curvature. A longitudinal controller system is used for determining desired vehicle acceleration. The longitudinal controller system uses a control loop with respect to a velocity error and a feedforward term. Commands are generated based on the output of the lateral controller system and the longitudinal controller system.

Abstract: A method includes identifying a current position of the vehicle, using sensor data; generating, via a processor, an initial corridor seeding based upon the current position of the vehicle and physical characteristics of the road, without consideration of any other objects on the roadway; identifying a plurality of objects along a first side of the roadway, the first side including a side of the roadway in which the vehicle is traveling, using the sensor data; generating, via the processor, a target first boundary for the corridor based on the identified plurality of objects along the first side of the roadway; generating, via the processor, a target second boundary on a second side of the roadway, opposite the first side; and adjusting, via the processor, the initial corridor seeding based on the target first boundary and the target second boundary, thereby generating the corridor of travel for the vehicle along the roadway.

Abstract: A system and method for providing routing instructions to one or more autonomous vehicles includes identifying a destination of an autonomous vehicle; identifying a starting position or an initial location of the autonomous vehicle; receiving autonomous vehicle sensor data; receiving one or more routing goals for a routing plan for the autonomous vehicle; generating one or more route modification parameters; and generating a route plan for the autonomous vehicle based on (a) the destination, (b) the starting position or the initial location, (c) the one or more route modification parameters and (d) the one or more routing goals.

Abstract: A subsea vertical glider robot which supports deployment in subsea oilfield activities is disclosed. This vertical glider robot can also be used in oceanographic research exploration. One application of this vertical glider robot is the autonomous delivery of equipment and sensor systems to a precise predetermined location on the sea floor. The vertical glider robot is deployed from a surface ship or any other suitable sea surface platform and allowed to free fall to the bottom of the ocean. The traversal through the body of water is performed primarily by converting initial potential energy of the apparatus into kinetic energy, it does not use propellers. The traversing of the seafloor is controlled with a steering module that refines orientation while processing information about the vertical glider robot's current position and the target where it has to land.

Abstract: A subsea vertical glider robot which supports deployment in subsea oilfield activities is disclosed. This vertical glider robot can also be used in oceanographic research exploration. One application of this vertical glider robot is the autonomous delivery of equipment and sensor systems to a precise predetermined location on the sea floor. The vertical glider robot is deployed from a surface ship or any other suitable sea surface platform and allowed to free fall to the bottom of the ocean. The traversal through the body of water is performed primarily by converting initial potential energy of the apparatus into kinetic energy, it does not use propellers. The traversing of the seafloor is controlled with a steering module that refines orientation while processing information about the vertical glider robot's current position and the target where it has to land.

Abstract: A method for determining the actual frequency of an inaccurate clock signal then using the actual frequency to generate a compensation factor to correct calculations using the clock signal. The method includes counting the number of clock pulses in the clock signal over a predetermined and programmable period of time, and based on the clock pulse count, determining the actual frequency of the clock signal. Once the actual frequency of the clock signal is determined, this value is used to generate the compensation factor based on the expected or rated frequency of the clock signal to compensate for the calculations using the clock signal. The method has a particular application for use in a powertrain control module incorporating a low frequency resonator and a high frequency system clock, where the resonator generates an inaccurate clock signal which is highly stable for short periods of time and the system clock is relatively stable over long term but suffers from short term jitter.