Abstract: An autonomous vehicle configured to perform a lane change maneuver is described herein. The autonomous vehicle includes several different types of sensor systems, such as image, lidar, radar, sonar, infrared, and GPS. The autonomous vehicle additionally includes a computing system that executes instructions on a lane change detection system and a control system. The lane change detection system includes a region of interest module and an object trajectory module for determining whether the autonomous vehicle will collide with another object if the autonomous vehicle maneuvers into an adjacent lane. An instruction module of the lane change detection system is further used to facilitate operational control of a mechanical system of the autonomous vehicle, such as an engine or a steering system.

Abstract: An autonomous vehicle configured to perform a lane change maneuver is described herein. The autonomous vehicle includes several different types of sensor systems, such as image, lidar, radar, sonar, infrared, and GPS. The autonomous vehicle additionally includes a computing system that executes instructions on a lane change detection system and a control system. The lane change detection system includes a region of interest module and an object trajectory module for determining whether the autonomous vehicle will collide with another object if the autonomous vehicle maneuvers into an adjacent lane. An instruction module of the lane change detection system is further used to facilitate operational control of a mechanical system of the autonomous vehicle, such as an engine or a steering system.

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 method are provided for controlling a vehicle. In one embodiment, a method includes: receiving, by a processor, a lane plan; determining, by a processor, from the lane plan an upcoming turn; determining, by a processor, if the upcoming turn is at least one of an unprotected left turn, an inside right turn, and an inside left turn; when at least one of an unprotected left turn, an inside right turn, and an inside left turn is determined, modifying, by a processor, a lane boundary; and controlling the vehicle based on the modified lane boundary.

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: An autonomous vehicle configured to perform a lane change maneuver is described herein. The autonomous vehicle includes several different types of sensor systems, such as image, lidar, radar, sonar, infrared, and GPS. The autonomous vehicle additionally includes a computing system that executes instructions on a lane change detection system and a control system. The lane change detection system includes a region of interest module and an object trajectory module for determining whether the autonomous vehicle will collide with another object if the autonomous vehicle maneuvers into an adjacent lane. An instruction module of the lane change detection system is further used to facilitate operational control of a mechanical system of the autonomous vehicle, such as an engine or a steering 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 and second boundaries, thereby generating the corridor of travel for the vehicle along the roadway.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: obtaining ride preference information associated with a user, identifying a current vehicle pose, determining a motion plan for the vehicle along a route based at least in part on the ride preference information, the current vehicle pose, and vehicle kinematic and dynamic constraints associated with the route, and operating one or more actuators onboard the vehicle in accordance with the motion plan. The user-specific ride preference information influences a rate of vehicle movement resulting from the motion plan.

Abstract: A method controls an operation of a laser processing machine with redundant actuators including a first actuator and a second actuator. The method determines a feasible region for states of the first actuator and states of a reference trajectory of the first actuator defined by constraints of the laser processing machine, constraints on the reference trajectory and constraints on a range of motion of the second actuator. The method selects a subset of the feasible region, such that for any state of the first actuator and any state of the reference trajectory within the subset, there is an admissible control maintaining the state of the first actuator within the subset of the feasible region for admissible future states of the reference trajectory, and selects an admissible control action for controlling the operation such that the state of the first actuator remains in the subset of the feasible region.

Abstract: In one embodiment, a method for selecting a parking location for an autonomous vehicle includes: obtaining data pertaining to a current ride of the autonomous vehicle during operation of the autonomous vehicle; determining, by a processor using the data, when the autonomous vehicle is proximate a destination; and, when the autonomous vehicle is proximate the destination: identifying, by the processor using the data, a plurality of potential parking locations proximate the destination; calculating, by the processor using the data, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: obtaining ride preference information associated with a user, identifying a current vehicle pose, determining a motion plan for the vehicle along a route based at least in part on the ride preference information, the current vehicle pose, and vehicle kinematic and dynamic constraints associated with the route, and operating one or more actuators onboard the vehicle in accordance with the motion plan. The user-specific ride preference information influences a rate of vehicle movement resulting from the motion plan.

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: In one embodiment, a method for selecting a parking location for an autonomous vehicle includes: obtaining data pertaining to a current ride of the autonomous vehicle during operation of the autonomous vehicle; determining, by a processor using the data, when the autonomous vehicle is proximate a destination; and, when the autonomous vehicle is proximate the destination: identifying, by the processor using the data, a plurality of potential parking locations proximate the destination; calculating, by the processor using the data, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations.

Abstract: A system and method for autonomous vehicle driving behavior modification include: receiving passenger driving behavior preferences for setting a driving behavior of an autonomous vehicle; generating driving behaviors controls based on the passenger driving behavior preferences; setting an initial driving behavior of the autonomous vehicle using the driving behavior controls, wherein setting the initial driving behavior comprises providing the driving behavior controls to be implemented by the autonomous vehicle during one or more routes involving the passenger; aggregating vehicle behavior feedback relating to a driving behavior of the autonomous vehicle during the one or more routes; and modifying the driving behavior of the autonomous vehicle based on the vehicle behavior feedback.

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 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 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 method are provided for controlling a vehicle. In one embodiment, a method includes: receiving, by a processor, a lane plan; determining, by a processor, from the lane plan an upcoming turn; determining, by a processor, if the upcoming turn is at least one of an unprotected left turn, an inside right turn, and an inside left turn; when at least one of an unprotected left turn, an inside right turn, and an inside left turn is determined, modifying, by a processor, a lane boundary; and controlling the vehicle based on the modified lane boundary.

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 method controls a movement of a train to a stop at a stopping position between a first position and a second position. The method determines constraints of a velocity of the train with respect to a position of the train forming a feasible area for a state of the train during the movement, such that an upper curve bounding the feasible area has a zero velocity only at the second position, and a lower curve bounding the feasible region has a zero velocity only at the first position. Next, the method controls the movement of the train subject to the constraints.