Abstract: A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. One general aspect includes sends video data and light detecting and ranging (LIDAR) data to a recurrent neural network (rnn) that includes feedback elements to identify a roadway feature. The system also sends the data to a dynamic convolutional neural network (dcnn) to identify the feature. Output values are sent to a softmax decision network to aggregate the rnn and the dcnn output values and determine a vehicle positional location on the roadway.

Abstract: A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. One general aspect includes sends video data and light detecting and ranging (LIDAR) data to a recurrent neural network (rnn) that includes feedback elements to identify a roadway feature. The system also sends the data to a dynamic convolutional neural network (dcnn) to identify the feature. Output values are sent to a softmax decision network to aggregate the rnn and the dcnn output values and determine a vehicle positional location on the roadway.

Abstract: A user gesture is detected based on received data from one or more motion sensors. User gesture attributes are identified including at least one of hand vectoring, wrist articulation, and finger articulation from the gesture including respective movements of each of a plurality of a user's fingers. Based on the gesture attributes, a user and an action to be performed in a vehicle are identified. The action is performed in the vehicle to control at least one vehicle component based on the gesture.

Abstract: A vehicle system includes a driver identification fusion module programmed to receive a confidence level from a plurality of identification modules. Each confidence level indicates the likelihood that a driver of a vehicle is a particular person. The driver identification fusion module is programmed to aggregate the confidences levels received from the plurality of identification modules and output an aggregated confidence level signal representing an identity of the driver based at least in part on the confidence levels received from the plurality of identification modules.

Abstract: A system for generating power for an electric sub-assembly of a motor vehicle may include at least one reverse electrowetting energy harvesting element coupled to a tire of the motor vehicle. The system may further include at least one controller configured to accumulate electric energy generated by the at least one reverse electrowetting energy harvesting element and supply the accumulated electric energy to at least one sub-assembly mounted on the tire.

Abstract: An aluminum welding system includes a welding machine configured to weld a workpiece with an aluminum nugget and a measurement device configured to measure an attribute of at least one of the aluminum nugget and a welding process. The system further includes a processing device configured to output a weld quality signal representing a quality of an aluminum weld based at least in part on the attribute measured. A method includes measuring an attribute of at least one of an aluminum nugget forming a joint of a workpiece and a welding process, determining a quality of an aluminum weld based at least in part on the attribute measured, and outputting a weld quality signal representing the determined quality.

Abstract: A vehicle system includes a driver identification fusion module programmed to receive a confidence level from a plurality of identification modules. Each confidence level indicates the likelihood that a driver of a vehicle is a particular person. The driver identification fusion module is programmed to aggregate the confidences levels received from the plurality of identification modules and output an aggregated confidence level signal representing an identity of the driver based at least in part on the confidence levels received from the plurality of identification modules.

Abstract: A user gesture is detected based on received data from one or more motion sensors. User gesture attributes are identified including at least one of hand vectoring, wrist articulation, and finger articulation from the gesture including respective movements of each of a plurality of a user's fingers. Based on the gesture attributes, a user and an action to be performed in a vehicle are identified. The action is performed in the vehicle to control at least one vehicle component based on the gesture.

Abstract: A system and methods for inferring a local engine temperature based on various engine conditions input to a dynamic model are disclosed. In the example system provided, an inferential temperature sensor uses a trainable model to estimate a local metal temperature in an exhaust valve bridge of a cylinder head which thereby allows closed loop control of a coolant flow device independent from engine speed, engine state, coolant flow state or system temperature. In response to estimated local metal temperatures, the methods described further allow thermal management of the engine system to be optimized.

Abstract: A system for generating power for an electric sub-assembly of a motor vehicle may include at least one reverse electrowetting energy harvesting element coupled to a tire of the motor vehicle. The system may further include at least one controller configured to accumulate electric energy generated by the at least one reverse electrowetting energy harvesting element and supply the accumulated electric energy to at least one sub-assembly mounted on the tire.

Abstract: An aluminum welding system includes a welding machine configured to weld a workpiece with an aluminum nugget and a measurement device configured to measure an attribute of at least one of the aluminum nugget and a welding process. The system further includes a processing device configured to output a weld quality signal representing a quality of an aluminum weld based at least in part on the attribute measured. A method includes measuring an attribute of at least one of an aluminum nugget forming a joint of a workpiece and a welding process, determining a quality of an aluminum weld based at least in part on the attribute measured, and outputting a weld quality signal representing the determined quality.

Abstract: Road grade is modeled over a region in which a vehicle is driven on roadways having a grade that varies over a plurality of predetermined grade ranges. A succession of grade values are generated while operating the vehicle at a predetermined rate, wherein each grade value identifies a respective grade range then being encountered. A Markov chain road-grade model is updated in response to the succession of grade values, wherein the model represents respective elements of probability in a matrix of transition events from each predetermined grade range to a respective next-in-succession grade range. Each element of the matrix has a value ?i,j representing a weighted frequency of transition events from a first respective grade value to a second respective grade value divided by a weighted frequency of transition events initiating from the first respective grade value, so that the matrix successively approximates the road grade of the region.

Abstract: Vehicle apparatus adjusts a vehicle powertrain of the vehicle in response to a speed setpoint. An optimizer selects a control policy to periodically generate speed adjustments for applying to the speed setpoint to operate at increased efficiency. The control policy is based on a value function providing an optimized solution for a cost model and a transition probability model. The transition probability model corresponds to a driving state defined according to a plurality of dimensions including a time-of-day dimension and a geographic region dimension. The transition probability model and the control policy have inputs based on road grade and speed. The optimizer collects road grade data during routine driving of the vehicle to construct a observed transition probability model and uses divergence between the observed transition probability model and a set of predetermined transition probability models to identify a control policy for use during the routine driving.

Abstract: A system and methods for inferring a local engine temperature based on various engine conditions input to a dynamic model are disclosed. In the example system provided, an inferential temperature sensor uses a trainable model to estimate a local metal temperature in an exhaust valve bridge of a cylinder head which thereby allows closed loop control of a coolant flow device independent from engine speed, engine state, coolant flow state or system temperature. In response to estimated local metal temperatures, the methods described further allow thermal management of the engine system to be optimized.

Abstract: Vehicle apparatus adjusts a vehicle powertrain of the vehicle in response to a speed setpoint. An optimizer selects a control policy to periodically generate speed adjustments for applying to the speed setpoint to operate at increased efficiency. The control policy is based on a value function providing an optimized solution for a cost model and a transition probability model. The transition probability model corresponds to a driving state defined according to a plurality of dimensions including a time-of-day dimension and a geographic region dimension. The transition probability model and the control policy have inputs based on road grade and speed. The optimizer collects road grade data during routine driving of the vehicle to construct a observed transition probability model and uses divergence between the observed transition probability model and a set of predetermined transition probability models to identify a control policy for use during the routine driving.

Abstract: Road grade is modeled over a region in which a vehicle is driven on roadways having a grade that varies over a plurality of predetermined grade ranges. A succession of grade values are generated while operating the vehicle at a predetermined rate, wherein each grade value identifies a respective grade range then being encountered. A Markov chain road-grade model is updated in response to the succession of grade values, wherein the model represents respective elements of probability in a matrix of transition events from each predetermined grade range to a respective next-in-succession grade range. Each element of the matrix has a value ?i,j representing a weighted frequency of transition events from a first respective grade value to a second respective grade value divided by a weighted frequency of transition events initiating from the first respective grade value, so that the matrix successively approximates the road grade of the region.