A tire wear estimation system is provided. The system includes at least one tire that supports a vehicle. At least one sensor is affixed to the tire to generate a first predictor. A lookup table or a database stores data for a second predictor. One of the predictors includes at least one vehicle effect. A model receives the predictors and generates an estimated wear rate for the at least one tire.

A tire wear estimation system is provided. The system includes at least one tire that supports a vehicle. At least one sensor is affixed to the tire to generate a first predictor. A lookup table or a database stores data for a second predictor. One of the predictors includes at least one vehicle effect. A model receives the predictors and generates an estimated wear rate for the at least one tire.

A system includes a computer including a processor and a memory, the memory storing instructions executable by the processor to generate a synthetic image by adjusting respective color values of one or more pixels of a reference image based on a specified meteorological optical range from a vehicle sensor to simulated fog, and input the synthetic image to a machine learning program to train the machine learning program to identify a meteorological optical range from the vehicle sensor to actual fog.

A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: process vehicle sensor data with a deep neural network to generate a prediction indicative of one or more objects based on the data and determine an object uncertainty corresponding to the prediction and when the object uncertainty is greater than an uncertainty threshold, segment the vehicle sensor data into a foreground portion and a background portion. Classify the foreground portion as including an unseen object class when a foreground uncertainty is greater than a foreground uncertainty threshold; classify the background portion as including unseen background when a background uncertainty is greater than a background uncertainty threshold; and transmit the data and a data classification to a server.

Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.

Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.

Motion control systems and methods are provided in a vehicle. In one embodiment, a motion control system includes a controller. The controller is configured to: receive target trajectory data associated with an upcoming trajectory of the autonomous vehicle; determine a yaw rate reference and a relative heading reference associated with the upcoming target trajectory based on a numerical integration of the target trajectory data; and control a trajectory of the autonomous vehicle based on the yaw rate reference and the relative heading reference.

An automatic driving system includes an electronic control device configured to: detect a driving operation input amount during an automatic driving control for a vehicle; determine whether the driver is able to start manual driving during the automatic driving control for the vehicle; output a signal for performing switching from automatic driving to the manual driving based on a result of a comparison between the driving operation input amount and a driving switching threshold that is a threshold for the switching from the automatic driving to the manual driving; set the driving switching threshold to a first driving switching threshold when it is determined that the driver is able to start the manual driving; and set the driving switching threshold to a second driving switching threshold exceeding the first driving switching threshold when it is determined that the driver is not able to start the manual driving.

An automatic driving system includes an electronic control device configured to: detect a driving operation input amount during an automatic driving control for a vehicle; determine whether the driver is able to start manual driving during the automatic driving control for the vehicle; output a signal for performing switching from automatic driving to the manual driving based on a result of a comparison between the driving operation input amount and a driving switching threshold that is a threshold for the switching from the automatic driving to the manual driving; set the driving switching threshold to a first driving switching threshold when it is determined that the driver is able to start the manual driving; and set the driving switching threshold to a second driving switching threshold exceeding the first driving switching threshold when it is determined that the driver is not able to start the manual driving.

Systems and methods for detecting electromagnetic emissions to monitor and manage road traffic. In one implementation, a system is provided for determining at least one of location, speed, and direction of vehicles on a roadway. The system comprising at least one receiver configured for placement at one or more fixed locations along the roadway to detect a plurality of non-reflected electromagnetic emissions originating from a plurality of vehicles. The system further comprise at least one processor configured to receive signal information from the at least one receiver and to identify in the plurality of non-reflected electromagnetic emissions an electromagnetic waveform of a vehicle. The at least one processor may calculate at least one of a Doppler effect, a phase difference, or a time difference of non-reflected electromagnetic emissions associated with the identified electromagnetic waveform, and determine at least one of a location, speed, and direction of the vehicle.