Abstract: Embodiments and examples are disclosed for intelligent vehicle diagnostics using driving behavior modeling and monitoring. For one example, a data processing system for a vehicle includes a plurality of sensors and a vehicle control unit (VCU). The VCU may sample the output from each of the plurality of sensors and assemble a dataset which may be transmitted to a cloud computing center. The cloud computing center may apply statistical machine learning algorithms to the dataset and training data to develop a model of a user's expected driving behavior. The cloud computing center may transmit the model to the vehicle, wherein the VCU may utilize the model to monitor the user's driving behavior. In response to detecting driving behavior that is anomalous to the expected driving behavior, the VCU may diagnose the cause of the anomalous behavior and take one or more preventative actions based on the diagnosis.

Abstract: A vehicle includes a set of sound sensors coupled to one or more processing systems that process sound data from the set of sound sensors in order to provide assisted driving features or functionality such as an emergency vehicle avoidance.

Abstract: Vehicles, methods, machine readable media and processing systems are described in which assisted driving or autonomous driving use a first trained model to recognize moving objects, such as vehicles and pedestrians, and use a second trained model to recognize stationary road landmarks, such as road signs, and stationary road obstacles such as road barriers or abandoned car parts, etc. The trained models can be implemented through, in one embodiment, a single trained neural network or through, in another embodiment, two separate trained neural networks.

Abstract: Hybrid user recognition methods systems for vehicle access and control are disclosed. For one example, a hybrid user recognition system can capture at least two types of biometric data of a user. The user is recognized if at least two types of captured biometric data match with at least two types of registered biometric signatures of the user. If the user is recognized, the user is allowed access or control of at least part of the electronic or driving controls of the otherwise the user is prevented from access or control of the vehicle. Examples of user biometrics include facial, voice, iris, fingerprint and behavioral biometrics.

Abstract: Embodiments and examples are disclosed for intelligent vehicle diagnostics using driving behavior modeling and monitoring. For one example, a data processing system for a vehicle includes a plurality of sensors and a vehicle control unit (VCU). The VCU may sample the output from each of the plurality of sensors and assemble a dataset which may be transmitted to a cloud computing center. The cloud computing center may apply statistical machine learning algorithms to the dataset and training data to develop a model of a user's expected driving behavior. The cloud computing center may transmit the model to the vehicle, wherein the VCU may utilize the model to monitor the user's driving behavior. In response to detecting driving behavior that is anomalous to the expected driving behavior, the VCU may diagnose the cause of the anomalous behavior and take one or more preventative actions based on the diagnosis.

Abstract: A steering wheel assembly for a vehicle includes a steering wheel, a first conductive coil coupled to the steering wheel, a second conductive coil that magnetically interacts with the first conductive coil, and a detection circuit coupled to the second conductive coil. The detection circuit includes a first circuit to generate a first signal based on a change in inductance and a second circuit to generate a second signal based on the first signal, the second signal to allow detection of a hand on the steering wheel.

Abstract: Embodiments and examples are disclosed for intelligent detection of vehicle intrusion using command pattern modeling and analysis. For one example, a vehicle control unit (VCU) may monitor, using a model of a user's expected driving behavior, the user's current driving behavior and detect anomalous driving behavior based on the model. The VCU may determine that the anomalous driving behavior does not correspond to one or more commands on a network bus of the vehicle and analyze, using a command pattern model, a pattern among the one or more commands on the network bus. The VCU may then compare, using the command pattern model, the pattern among the one or more commands to a historical command pattern to determine if an intrusion (e.g., by a hacker) is taking place.

Abstract: Hybrid user recognition methods systems for vehicle access and control are disclosed. For one example, a hybrid user recognition system can capture at least two types of biometric data of a user. The user is recognized if at least two types of captured biometric data match with at least two types of registered biometric signatures of the user. If the user is recognized, the user is allowed access or control of at least part of the electronic or driving controls of the otherwise the user is prevented from access or control of the vehicle. Examples of user biometrics include facial, voice, iris, fingerprint and behavioral biometrics.

Abstract: A vehicle includes a set of sound sensors coupled to one or more processing systems that process sound data from the set of sound sensors in order to provide assisted driving features or functionality such as an emergency vehicle avoidance.