Abstract: An illustrative example method is for estimating a friction characteristic of a surface beneath a vehicle that has a plurality of wheels contacting the surface. The method includes determining a wheel speed of at least one of the wheels, determining a velocity of the at least one of the wheels separately from determining the wheel speed, determining a wheel slip of the at least one of the wheels based on the determined wheel speed and the determined velocity, and determining the friction characteristic based on the determined wheel slip. Determining the velocity separately from the wheel speed is accomplished using at least one detector that provides an output corresponding to a range rate, such as a RADAR or LIDAR detector.

Abstract: An illustrative example method is for estimating a friction characteristic of a surface beneath a vehicle that has a plurality of wheels contacting the surface. The method includes determining a wheel speed of at least one of the wheels, determining a velocity of the at least one of the wheels separately from determining the wheel speed, determining a wheel slip of the at least one of the wheels based on the determined wheel speed and the determined velocity, and determining the friction characteristic based on the determined wheel slip. Determining the velocity separately from the wheel speed is accomplished using at least one detector that provides an output corresponding to a range rate, such as a RADAR or LIDAR detector.

Abstract: A method for estimating unknown parameters (pan angle (?), instantaneous tilt angle (?) and road geometry of an upcoming road segment) for a vehicle object detection system. The vehicle object detection system is preferably a forward looking, radar-cued vision system having a camera, a radar sensor and an processing unit. The method first estimates the pan angle (?), then corrects the coordinates from a radar track so that pan angle (?) can be treated as zero, and finally solves a least squares problem that determines best estimates for instantaneous tilt angle (?) and road geometry. Estimating these parameters enables the vehicle object detection system to identify, interpret and locate objects in a more accurate and efficient manner.

Abstract: A collision detection system and method of estimating a crossing location are provided. The system includes a first sensor for sensing an object in a field of view and sensing a first range defined as the distance between the object and the first sensor. The system also includes a second sensor for sensing the object in the field of view and sensing a second range defined by the distance between the object and the second sensor. The system further includes a controller for processing the first and second range measurements and estimating a crossing location of the object as a function of the first and second range measurements. The crossing location is estimated using range and range rate in a W-plane in one embodiment and using a time domain approach in another embodiment.

Abstract: A rollover detection apparatus and method are provided for anticipating a potential vehicle rollover event. The apparatus includes an input for receiving a plurality of input signals including sensed parameters of the vehicle. A first memory buffer stores data representative of one or more predetermined driving scenarios that represent possible rollover scenarios. A second memory buffer stores data representative of a history of recent conditions of the vehicle based on the plurality of sensed vehicle parameters. The apparatus further includes a processor for comparing the data representative of a history of recent driving events to the data representative of one or more predetermined driving scenarios. The processor further determines a possible rollover event of the vehicle based on the comparison and generates an output signal indicative thereof.