Abstract: An auto-location system locates a position of a tire. A tire sensor unit is mounted on the tire and measures a length of a footprint of the tire, and electronic memory capacity stores identification information for the tire sensor unit. A vehicle sensor unit is mounted on the vehicle and measures a lateral acceleration and a longitudinal acceleration. A processor is in electronic communication with the tire sensor unit and the vehicle sensor unit, and receives the measured footprint length, the identification information, the lateral acceleration, and the longitudinal acceleration. A virtual footprint length estimator employs the lateral acceleration and the longitudinal acceleration to estimate a virtual footprint length of the tire. A correlation module receives the virtual footprint length and the measured footprint length to generate correlation values. A decision arbitrator applies a set of decision rules to the correlation values to generate a wheel position indication.

Abstract: An auto-location system includes a first tire sensor unit that measures a footprint length of a first tire. A second tire sensor unit measures a footprint length of a second tire. A vehicle status determination module receives the measured footprint lengths and determines when the vehicle is in a static or cruising state. A mean calculation module receives the measured footprint lengths when the vehicle is in a static or cruising state, and determines a first mean footprint length corresponding to the first sensor unit and a second mean footprint length corresponding to the second sensor unit. A comparison module receives the mean footprint lengths and determines a longest and a shortest of the mean footprint lengths. A position determination module generates a position determination of the first sensor unit and the second sensor unit based on the longest and the shortest of the mean footprint lengths.

Abstract: Aspects of tire sensor auto-location are described. A sensor position detection device receives tire sensor values from a tire sensor device. The tire sensor values are measured or calculated for tire footprint length, longitudinal acceleration, and lateral acceleration. The sensor position detection device generates a longitudinal acceleration coefficient and a lateral acceleration coefficient using these values, and assigns the tire sensor device to a particular tire position of a vehicle based on a sign of the longitudinal acceleration coefficient and a sign of the lateral acceleration coefficient.

Abstract: An auto-location system includes a first tire sensor unit that measures a footprint length of a first tire. A second tire sensor unit measures a footprint length of a second tire. A vehicle status determination module receives the measured footprint lengths and determines when the vehicle is in a static or cruising state. A mean calculation module receives the measured footprint lengths when the vehicle is in a static or cruising state, and determines a first mean footprint length corresponding to the first sensor unit and a second mean footprint length corresponding to the second sensor unit. A comparison module receives the mean footprint lengths and determines a longest and a shortest of the mean footprint lengths. A position determination module generates a position determination of the first sensor unit and the second sensor unit based on the longest and the shortest of the mean footprint lengths.

Abstract: A system for real-time determination of calibration of an inertial measurement unit includes an inertial measurement unit and a processor in electronic communication with the inertial measurement unit. A road mapping module receives a vehicle latitude and a vehicle longitude, and determines a virtual heading angle of a vehicle. A virtual acceleration module receives the virtual heading angle of the vehicle, and a measured vehicle speed and heading angle, and estimates a virtual lateral acceleration and a virtual longitudinal acceleration. A correlation module receives the virtual lateral acceleration, the virtual longitudinal acceleration, a calibrated measured lateral acceleration, and a calibrated measured longitudinal acceleration. The correlation module determines a correlation between the virtual lateral acceleration and the calibrated measured lateral acceleration, and between the virtual longitudinal acceleration and the calibrated measured longitudinal acceleration.

Abstract: An auto-location system locates a position of a tire. A tire sensor unit is mounted on the tire and measures a length of a footprint of the tire, and electronic memory capacity stores identification information for the tire sensor unit. A vehicle sensor unit is mounted on the vehicle and measures a lateral acceleration and a longitudinal acceleration. A processor is in electronic communication with the tire sensor unit and the vehicle sensor unit, and receives the measured footprint length, the identification information, the lateral acceleration, and the longitudinal acceleration. A virtual footprint length estimator employs the lateral acceleration and the longitudinal acceleration to estimate a virtual footprint length of the tire. A correlation module receives the virtual footprint length and the measured footprint length to generate correlation values. A decision arbitrator applies a set of decision rules to the correlation values to generate a wheel position indication.

Abstract: An apparatus for traversing a vehicle transportation network by an autonomous vehicle (AV) includes a human-autonomy teaming manager. The manager includes a first processor configured to initiate a dialogue associated with a predefined dynamic task sequence that is responsive to a condition experienced by the AV while traversing from a starting location to an ending location within the vehicle transportation network. The sequence is one of a plurality of predefined dynamic task sequences that uses multiple agents to resolve the condition. The manager receives, from an interface accessible to a human agent, an input responsive to the dialogue. The input confirms the sequence as a selected predefined dynamic task sequence or selects an other of the plurality of predefined dynamic task sequences as the selected predefined dynamic task sequence. The manager delegates tasks of the selected predefined dynamic task sequence to resolve the condition.

Abstract: A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Abstract: An auto-location system locates a position of a tire that supports a vehicle. The system includes a sensor unit that is mounted on the tire and includes a footprint length measurement sensor to measure a length of a footprint of the tire. A processor is in electronic communication with the sensor unit and receives the measured footprint length. A driving event classifier is executed on the processor and employs the measured footprint length to determine the position of the tire on the vehicle. An auto-location output block is executed on the processor and receives the determined position of the tire on the vehicle and generates a message correlating the sensor unit to the position of the tire on the vehicle.

Abstract: A tire wear state estimation system includes at least one tire that supports a vehicle. A sensor is mounted on the tire and measures tire parameters. At least one sensor is mounted on the vehicle and measures vehicle parameters. Each one of a plurality of sub-models receives selected tire parameters from the tire mounted sensor and selected vehicle parameters from the vehicle mounted sensor. Each one of the sub-models generates a sub-model wear state estimate, and a model reliability is determined for each one of the sub-models. A supervisory model receives the wear state estimate from each sub-model and the model reliability for each sub-model, and generates a combined wear state estimate for the tire.

Abstract: A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Abstract: An apparatus for traversing a vehicle transportation network by an autonomous vehicle (AV) includes a human-autonomy teaming manager. The manager includes a first processor configured to initiate a dialogue associated with a predefined dynamic task sequence that is responsive to a condition experienced by the AV while traversing from a starting location to an ending location within the vehicle transportation network. The sequence is one of a plurality of predefined dynamic task sequences that uses multiple agents to resolve the condition. The manager receives, from an interface accessible to a human agent, an input responsive to the dialogue. The input confirms the sequence as a selected predefined dynamic task sequence or selects an other of the plurality of predefined dynamic task sequences as the selected predefined dynamic task sequence. The manager delegates tasks of the selected predefined dynamic task sequence to resolve the condition.