Abstract: In a method and a system for controlling a safety system for a vehicle, a sensor suite is provided to generate at least one yaw-acceleration signal. An evaluation circuit is used to sample the at least one yaw-acceleration signal with a sampling time of less than 10 ms, and to generate a control signal as a function of the at least one sampled yaw-acceleration signal.

Abstract: A control unit and a method for triggering a passenger protection arrangement are described, a first hardware path and a second hardware path together inducing the triggering on the basis of at least one accident signal from an accident sensor system. An analyzer circuit for processing the at least one accident signal is present in the first hardware path, and a plausibility circuit is present in the second hardware path. At least the plausibility circuit is additionally connected to an interface, the interface supplying a signal of at least one additional control unit. The plausibility circuit also enables the triggering as a function of this signal.

Abstract: In a method for triggering a passenger protection arrangement for a vehicle, a feature vector including at least two features is determined, the two features being derived from at least one signal of an accident sensor system. The feature vector is classified as a function of a comparison with at least one class boundary. The passenger protection arrangement is triggered as a function of the classification. A confidence measure is determined as a function of a position of the at least one feature vector in relation to the at least one class boundary. The triggering of passenger protection arrangement takes place as a function of this confidence measure.

Abstract: A system 10 for determining high accuracy gradient information includes linearization means 20, a sum unit 45, and state space model and observer means 50 for calculating a road gradient ?Road. The linearization means 20 includes an air resistance calculation unit 30 and a rolling resistance calculation unit 40. The means 50 includes a state space model 60 and a state space observer 70. The sum unit 45 determines a total sum wheel force ?FLij of wheel forces FLij. The linearization means 20 calculates an air resistance force FW and a rolling resistance force FR based on a vehicle velocity vCoG using approximation equations, calculates a linearized total sum force FSum by subtracting the air resistance force FW and the rolling resistance force FR from the wheel forces FLij, and inputs the linealized total sum force FSum to the state space model and observer means 50.

Abstract: In a method and a control unit for triggering passenger protection devices, at least one characteristic is extracted from at least one variable. A crash is classified on the basis of this at least one characteristic, and the crash classification results in the making of a triggering decision. The passenger protection devices are then triggered as a function of the triggering decision. The triggering decision is made by providing a sequence control which, as a function of at least one progression variable, activates or deactivates a plurality of functions for the crash classification and/or defines which at least one characteristic is used for the particular function.

Abstract: A driving situation detection system capable of detecting driving situations swiftly with high reliability is obtained. The driving situation detection system includes real curve arithmetic means reference vehicle model and observer means, a differentiator unit, a model curve radius arithmetic means, and an assessment unit. The arithmetic means generates real curve radius signals based on wheel speeds. The reference vehicle model and observer means processes input signals utilizing a linear reference model to generate a yaw rate signal and a vehicle body side slip angle signal. The unit differentiates the vehicle body side slip angle signal to generate a vehicle body side slip rate signal. The model curve radius arithmetic means generates a model curve radius signal based on the yaw rate signal and the vehicle body side slip rate signal. The assessment unit detects undesirable driving situations by comparing the real curve radius and the model curve radius.

Abstract: A system for analyzing vehicle and driver behavior includes: a data preprocessing unit that converts operation information of an in-vehicle electrical system, data available via an in-vehicle data network, and additional information available from an electrical device constituting a vehicle into a format capable of calculation therein; a vehicle model and estimation unit that estimates variables which can not be measured by means of in-vehicle sensors based on the preprocessed data; a model-based reconstruction unit that reconstructs an accident scenario by unifying the preprocessed data and the estimated variables from the vehicle model and estimation unit to a common time stamp; and an assessment unit that assesses vehicle and driver behavior based on the accident scenario reconstructed by the model-based reconstruction unit.

Abstract: A vehicle dynamics behavior reproduction system capable of describing accurately behavior of a motor vehicle in a lateral direction even for nonlinear driving situation includes a vertical wheel force arithmetic module (105), a lateral wheel force arithmetic module (110), a cornering stiffness adaptation module (115), a state space model/observer unit (120), a selector (130), a delay module (135), and a tire side slip angle arithmetic module (125). Vertical wheel forces (FZij) and tire side slip angles (?ij) are determined by using sensor information and estimated values while lateral wheel forces (FYij) are determined in accordance with a relatively simple nonlinear approximation equation. The lateral wheel force (FYij) and the tire side slip angle (?ij) provide bases for adaptation of cornering stiffnesses at individual wheels. Vehicle motion is accurately described to a marginal stability by using adapted cornering stiffnesses (Cij) and other information.

Abstract: To provide a vehicle accident analyzing apparatus in which reconstruction quality of low speed crashes is improved. An impact parameter determination apparatus 10 is provided with a triggering unit 20 which uses input signals from in-vehicle sensors, and an area determination unit 30, and a parameter calculation unit 50. The triggering unit 20 generates a trigger signal 21 based on the input signals for triggering the area determination unit 30 and the parameter calculation unit 50. The area determination unit 30 uses the input signals to calculate the most probable impact area 31. The parameter calculation unit 50 calculates the final desired crash parameters based on the input signals and the most probable impact area 31.

Abstract: A system 10 for determining high accuracy gradient information includes linearization means 20, a sum unit 45, and state space model and observer means 50 for calculating a road gradient ?Road. The linearization means 20 includes an air resistance calculation unit 30 and a rolling resistance calculation unit 40. The means 50 includes a state space model 60 and a state space observer 70. The sum unit 45 determines a total sum wheel force ?FLij of wheel forces FLij. The linearization means 20 calculates an air resistance force FW and a rolling resistance force FR based on a vehicle velocity vCoG using approximation equations, calculates a linearized total sum force FSum by subtracting the air resistance force FW and the rolling resistance force FR from the wheel forces FLij, and inputs the linealized total sum force FSum to the state space model and observer means 50.

Abstract: To provide a vehicle accident analyzing apparatus in which reconstruction quality of low speed crashes is improved. An impact parameter determination apparatus 10 is provided with a triggering unit 20 which uses input signals from in-vehicle sensors, and an area determination unit 30, and a parameter calculation unit 50. The triggering unit 20 generates a trigger signal 21 based on the input signals for triggering the area determination unit 30 and the parameter calculation unit 50. The area determination unit 30 uses the input signals to calculate the most probable impact area 31. The parameter calculation unit 50 calculates the final desired crash parameters based on the input signals and the most probable impact area 31.

Abstract: A driving situation detection system capable of detecting driving situations swiftly with high reliability is obtained. The driving situation detection system includes real curve arithmetic means reference vehicle model and observer means, a differentiator unit, a model curve radius arithmetic means, and an assessment unit. The arithmetic means generates real curve radius signals based on wheel speeds. The reference vehicle model and observer means processes input signals utilizing a linear reference model to generate a yaw rate signal and a vehicle body side slip angle signal. The unit differentiates the vehicle body side slip angle signal to generate a vehicle body side slip rate signal. The model curve radius arithmetic means generates a model curve radius signal based on the yaw rate signal and the vehicle body side slip rate signal. The assessment unit detects undesirable driving situations by comparing the real curve radius and the model curve radius.

Abstract: A vehicle dynamics behavior reproduction system capable of describing accurately behavior of a motor vehicle in a lateral direction even for nonlinear driving situation includes a vertical wheel force arithmetic means (105), a lateral wheel force arithmetic means (110), a cornering stiffness adaptation means (115), a state space model/observer unit (120), a selector (130), a delay means (135), and a tire side slip angle arithmetic means (125). Vertical wheel forces (FZij) and tire side slip angles (?ij) are determined by using sensor information and estimated values while lateral wheel forces (FYij) are determined in accordance with a relatively simple nonlinear approximation equation. The lateral wheel force (FYij) and the tire side slip angle (?ij) provide bases for adaptation of cornering stiffnesses at individual wheels. Vehicle motion is accurately described to a marginal stability by using adapted cornering stiffnesses (Cij) and other information.

Abstract: A system for analyzing vehicle and driver behavior includes: a data preprocessing unit that converts operation information of an in-vehicle electrical system, data available via an in-vehicle data network, and additional information available from an electrical device constituting a vehicle into a format capable of calculation therein; a vehicle model and estimation unit that estimates variables which can not be measured by means of in-vehicle sensors based on the preprocessed data; a model-based reconstruction unit that reconstructs an accident scenario by unifying the preprocessed data and the estimated variables from the vehicle model and estimation unit to a common time stamp; and an assessment unit that assesses vehicle and driver behavior based on the accident scenario reconstructed by the model-based reconstruction unit.