A system for determining vehicle direction includes an active wheel speed sensor (aWSS), an exciter ring for inducing a change in a signal from the aWSS and a controller. The controller receives a first series of signals from the aWSS, compares them to an array of predefined signals and determines the direction of travel based on the first series of signals matching the array. The controller receives a second series of signals and determines the exciter ring has an anomaly in response to at least one signal in the second series of signals having a first variance. The controller updates the array of predefined signals to include a representation of the first variance to create an array of updated signals. The controller determines the direction of travel based on a subsequent series of signals matching one of the array of predefined signals and the array of updated signals.

A redundant sensor system includes first and second sensors of the same type. The first and second sensors are configured to sense and measure a parameter, such as torque, applied to an object, such as a shaft. A preselected measurement value difference is provided between the first and second sensors. The preselected measurement value difference, such as an offset or a difference in sensor gain, can be utilized by the redundant sensor system or an associated control system to detect a failure of one of the sensors. Output signals of the first and second signals that do not reflect the preselected measurement value difference within given tolerance indicate that one of the sensors has failed, and a determination that an associated system is untrustworthy can be obtained.

An automotive sensor integration module including a plurality of sensors configured to detect an object outside a vehicle, and a signal processing unit configured to output, as sensing data, a plurality of pieces of detection data output from the plurality of sensors according to any one among the plurality of pieces of detection data at a substantially same timing based on a priority signal, or output, as the sensing data, the plurality of pieces detection data according to an external pulse at a substantially same timing.

A method for determining kinematics of a target includes generating a measured trace of a target position, speed, and angle of a target relative to an ego vehicle. The radius of the curve that the target is taking is calculated, using the generated trace. A number of paths possible to be followed by the target are projected, expressed as abstract movement functions of a polynomial degree and using as input the calculated radius. At each further cycle, higher probabilities are added to the paths projected in a previous measuring cycle which are equal with the newly projected ones. The projected paths are kept if the radius remains the same as in the previous measuring cycle. The current kinematics values are computed by smoothing filtering as predicted kinematics values, which are compared with the kinematics values resulted from the projected paths, to determine the final kinematics values.

A method for quantifying road user behavior, the method comprising; obtaining samples of road user behavior selecting a subset of the road user behavior samples such that the selected samples follow a pre-determined statistical extreme value distribution, parameterizing the pre-determined statistical extreme value distribution based on the selected samples of road user behavior, and quantifying road user behavior based on the parameterized statistical extreme value distribution.

A method for autonomously operating a vehicle includes capturing environmental data of a front area by a front sensor mounted to the vehicle, capturing environmental data of a rear area by a rear sensor, capturing a position of the vehicle by a position sensor, assigning the position of the vehicle to a location in an topographic map containing slope information, retrieving slope information from the topographic map for a predetermined range in front of and behind of the location of the vehicle, determining a maximum detection distance of the front and rear sensors for detecting an object having a specific vertical height based on the slope information, front and rear sensor positions, and a vertical opening angle of a field of view of the front sensors, determining a minimum detection distance of the front and the rear sensor required for a planned driving maneuver or a current driving state of the vehicle, and actuating the vehicle such that the required minimum detection distance is equal or smaller than the maximum detection distance of the front and rear sensors.

A method, apparatus and system for generating sensor data comprising a subset of tagged sensor data. The method includes: sensing, using a sensing element, ambient data, wherein the ambient data characterises a condition of an environment proximate to the sensing element; identifying, using a data identification engine, at least a first subset of the ambient data comprising a representation of, or identifying information related to, personally relevant information obtained by the sensing element; tagging, using a data tagging engine, the first subset of the ambient data with at least one data tag; and outputting, via the communication interface, at least a second subset of the ambient data comprising ambient data that has not been tagged by the data tagging engine.

Each of three or more computation units supplies a first control signal showing a target output of an actuator to an output unit. A determination unit assigns the target output shown by the first control signal supplied from each of the computation units with a weight based on the degree of reliability of the first control signal, and performs a majority vote of the target outputs. The output unit outputs a second control signal for controlling the actuator based on first control signals supplied from the computation units and a result of the majority vote of the target outputs by the determination unit.

The ADAS monitoring event system of the present invention has the advantages of checking whether an advanced driver assistance system (ADAS) is operating appropriately and a state during driving based on vehicle-related data, increasing the safety of autonomous driving, and resolving disputes in the event of a traffic accident.

A system or method implemented by an autonomous vehicle involves determining a path plan to reach a destination from an origin. The path plan includes two or more path steps indicating tasks to be completed to reach the destination. The method includes, during traversal of the path plan by the autonomous vehicle, evaluating one or more of the two or more path steps of a planning horizon to determine a behavior plan for the planning horizon. The planning horizon is based on a current position of the autonomous vehicle, the behavior plan includes a speed and a trajectory, and the evaluating includes performing a cost analysis using a parallelized tree-based decision scheme at each of two or more simulation intervals within the planning horizon. The evaluating and the determining the behavior plan is repeated at two or more positions of the autonomous vehicle from the origin to the destination.