Abstract: A system that classifies driver driving skill based on on-ramp or off-ramp maneuvers. The system reads sensor signals for vehicle speed and vehicle yaw rate. The system determines that the vehicle has made an on-ramp or off-ramp maneuver using the vehicle speed signal and the yaw-rate signal and then classifies the driver's driving skill using selected discriminant features obtained or derived from the on-ramp or off-ramp maneuver.

Abstract: A system and method that classify a driver's driving skill based on a characteristic passing maneuver. The system reads vehicle speed and vehicle yaw rate signals and the maneuver identification processor determines whether the vehicle has made a characteristic passing maneuver. The skill characterization processor then uses the sensor information and the passing information to characterize the driver's driving skill based on the passing maneuver.

Abstract: A skill characterization processor classifies driver skill based stop and go maneuvers. A maneuver identification processor determines whether the vehicle is in a braking maneuver, and the system determines the vehicle longitudinal deceleration, the brake pedal position and the brake pedal rate from the brake pedal position. The skill characterization processor then classifies the driver's driving skill based on the brake pedal rate, the brake pedal position and the vehicle longitudinal deceleration generally under normal driving conditions. In one embodiment, the processor classifies driver skill by performing frequency analysis on the brake pedal rate using a discrete Fourier transform to find a frequency component of the brake pedal rate to obtain a power spectrum density.

Abstract: A method for determining a driver's driving skill of a vehicle based on straight-line driving behavior. The method can classify driver skill based on three straight-line approaches, namely, a lane-position approach, a steering characteristic approach and a traffic-environment reaction approach.

Abstract: A system that classifies driver driving skill based on U-turn maneuvers. The system reads sensor signals for vehicle speed and vehicle yaw rate. The system determining that the vehicle has made a U-turn maneuver using the vehicle speed signal and the yaw-rate signal and then classifies the driver's driving skill using selected discriminant features obtained or derived from the U-turn maneuver.

Abstract: A system that classifies driver driving skill based on lane-change maneuvers. The system reads vehicle sensor signals. The system determining that the vehicle has made a lane-change maneuver using the vehicle sensor signals and then classifies the driver's driving skill using selected discriminant features obtained or derived from the lane-change maneuver.

Abstract: A system and method that classifies a driver's driving skill based on curve-handling maneuvers. The curve-handling maneuvers can be identified based on the drivers steering activity, vehicle yaw motion and a change in the vehicle heading direction.

Abstract: A system for classifying a driver's driving skill of a vehicle based on behavioral diagnosis. A plurality of vehicle sensors providing vehicle measurement signals. A maneuver qualification and identification processor qualifies and identifies characteristic maneuver identifying signals and a maneuver index and parameter processor creates a maneuver index and identifies relevant vehicle parameters. A path reconstruction processor reproduces an intended vehicle path for each characteristic maneuver identified by the maneuver characteristic processor. A maneuver model processor models the characteristic maneuvers and a driving skill diagnosis processor provides driving skill signals based on the maneuver model and driver input data. The driving skill diagnosis processor converts the maneuver model signals and the driver command input signal to the frequency domain to provide frequency content discrepancy analysis.

Abstract: A method for determining a driver's driving skill of a vehicle using transmission shift information. The method includes providing an ideal transmission shift map based on throttle position and vehicle speed. The method also includes monitoring an actual transmission shift point performed by the driver and comparing an actual transmission shift point to the transmission shift map to identify a shift-error distance on the map. The method also includes comparing the shift-error distance to a predetermined threshold and classifying the driver's driving skill based on the comparison of the shift-error distance to the threshold.

Abstract: A system and method for providing integrated driver skill recognition. The system includes an input switch that receives maneuver identifier signals that identify a plurality of different vehicle maneuvers and data that represents the identified maneuvers. The system also includes a plurality of skill classification processors that selectively receive the data from the input switch depending on the maneuver identifier signals, where a separate skill classification processor is provided for each separate type of maneuver. The skill classification processors classifying the maneuver to determine the driver's driving skill based on the data and provide skill classification signals. An output switch responsive to the skill classification signals from the skill classification processors.

Abstract: A system and method that classify driver driving skill based on multiple types of maneuvers. An original features generation processor receives signals identifying driving characteristics of the driver of the vehicle and outputs original features from the signals. A features extraction processor extracts certain features from the original features and outputs transformed features. A features selection processor selects certain ones of the transformed features and outputs final features and a classifier classifies the final features to determine the skill level of the vehicle driver.

Abstract: A system and method that classifies driver driving skill based on backup maneuvers. The system determines a vehicle speed signal and a vehicle backup gear position. The system determines that the vehicle has made a backup maneuver using the vehicle speed signal and the backup gear position and then classifies the driver's driving skill using selected discriminant features obtained or derived from the backup maneuver.

Abstract: A vehicle stability enhancement system that is adapted for an estimated driver workload. The system includes a driver workload estimation processor that estimates the driver workload based on certain factors, such as the vehicle speed or driver-behavior factors. The driver workload estimation is used to adjust the damping ratio and natural frequency in dynamic filters in a command interpreter to adjust a desired yaw rate signal and a desired side-slip signal. The driver workload estimation is also used to generate a yaw rate multiplication factor and a side-slip multiplication factor that modify a yaw rate stability signal and a side-slip stability signal in a feedback control processor that generates a stability control signal.

Abstract: An integrated diagnosis and prognosis system that collects vehicle information over the life of a vehicle and its development. The system provides the collected vehicle information to supplier management, product development management, service/dealership management, customer relations departments and production facilities, which use the information to take certain action for existing vehicles, fleets of vehicles or future vehicles to improve vehicle reliability and quality.

Abstract: A system and method for providing autonomous and remote vehicle maintenance and repair. The system employs an on-board diagnosis and prognosis module that monitors one or more vehicle buses to identify trouble codes and other information indicating a vehicle problem. The on-board module causes a telematic device on the vehicle to broadcast a message including a problem code that identifies the problem the vehicle is having. A remote repair center may receive the message and may identify a software upgrade patch associated with the problem that can be transmitted to the vehicle to upgrade its software to correct the problem. Also, the message may be received by another vehicle that is part of a broadcast network that has previously received the software upgrade patch to fix a problem on that vehicle, where the receiving vehicle may transmit the software upgrade patch to the vehicle having the problem.

Abstract: Information associated with vehicle components and sub-systems is monitored by an on-board module, and associated data, either processed or raw, is telematically transmitted to a remote data center by wireless communications. The remote data center archives the received data in a database for each separate vehicle that is part of the system. The remote data center analyzes the data to ascertain whether the data indicates a usage pattern and/or vehicle condition that may have a detrimental effect on certain vehicle components, sub-systems and systems, such as excessive component wear. For example, the data center runs pattern detection algorithms on the data to identify known usage patterns that may potentially impact normal vehicle operation. If such a usage pattern is detected, the remote data center may issue a warning to the vehicle operator, or other designated person, that such usage may have a detrimental effect on the vehicle or vehicle components.

Abstract: A vehicle stability enhancement system that is adapted for an estimated driver workload. The system includes a driver workload estimation processor that estimates the driver workload based on certain factors, such as the vehicle speed or driver-behavior factors. The driver workload estimation is used to adjust the damping ratio and natural frequency in dynamic filters in a command interpreter to adjust a desired yaw rate signal and a desired side-slip signal. The driver workload estimation is also used to generate a yaw rate multiplication factor and a side-slip multiplication factor that modify a yaw rate stability signal and a side-slip stability signal in a feedback control processor that generates a stability control signal.

Abstract: An adaptive vehicle control system that classifies a driver's driving style based on vehicle stopping maneuvers. The system reads sensor signals to provide a vehicle speed and determines whether the vehicle is currently in straight line driving or curve driving. If the vehicle is in straight line or curve driving and the vehicle speed is less than a speed threshold, the system determines that the vehicle is in an accelerating or decelerating maneuver. The system then determines that the accelerating and decelerating maneuver has ended if the vehicle is not in straight line or curve driving or the vehicle speed signal is less than the speed threshold. The system can then classify the vehicle accelerating and decelerating maneuver using select discriminate features.

Abstract: An adaptive vehicle control system that classifies a driver's driving style based on vehicle stopping maneuvers. The system reads sensor signals to provide a vehicle speed and a vehicle longitudinal deceleration. The system determines whether an average of the vehicle longitudinal deceleration during a time window is greater than a longitudinal deceleration threshold and, if not, determines that the vehicle is in the stopping maneuver. The system then determines that the stopping maneuver has ended if the vehicle speed signal during another time window is less than a speed threshold. The style characterization processor can then classify the vehicle stopping maneuver using selected discriminant features.

Abstract: A method for providing an estimate of brake pad thickness. The method employs fusion of sensors, if used, and driver brake modeling to predict the vehicle brake pad life. An algorithm is employed that uses various inputs, such as brake pad friction material properties, brake pad cooling rate, brake temperature, vehicle mass, road grade, weight distribution, brake pressure, brake energy, braking power, etc. to provide the estimation. The method calculates brake work using total work minus losses, such as aerodynamic drag resistance, engine braking and/or braking power as braking torque times velocity divided by rolling resistance to determine the brake rotor and lining temperature. The method then uses the brake temperature to determine the brake pad wear, where the wear is accumulated for each braking event. A brake pad sensor can be included to provide one or more indications of brake pad thickness from which the estimation can be revised.