Abstract: Methods and systems for multi-hypothesis object tracking for automated driving systems. One system includes an electronic processor configured to receive environment information and generate pseudo-measurement data associated with an object within an environment of the vehicle. The electronic processor is also configured to determine, based on the environment information and the pseudo-measurement data, a set of association hypotheses regarding the object. The electronic processor is also configured to determine, based on the set of association hypotheses, an object state of the object. The electronic processor is also configured to control the vehicle based on the determined object state.

Abstract: A system for a reliability of objects for a driver assistance or automated driving of a vehicle includes a plurality of sensors that include one or more sensor modalities for providing sensor data for the objects. An electronic tracking unit is configured to receive the sensor data to determine a detection probability (p_D) for each of the plurality of sensors for each of the objects, to determine an existence probability (p_ex) for each of the plurality of sensors for each of the objects, and to provide vectors for each of the objects based on the existence probability (p_ex) for each contributing one of the plurality of sensors for the specific object. The vectors are provided by the electronic tracking unit for display as an object interface on a display device. The vectors are independent from the sensor data from the plurality of sensors.

Abstract: A method for determining the reliability of detected and/or tracked objects for use in the driver assistance or the at least semiautomated driving of a vehicle. The method includes: a) receiving sensor data for the detected objects from a plurality of sensors, b) associating pieces of object existence information with each object, c) checking, considering, or representing redundancy of pieces of object existence information.

Abstract: Redundant environment perception tracking for automated driving systems. One example embodiment provides a surveillance system, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor of the first sensor type, and track the object based on the object state that is determined.

Abstract: Methods and systems for controlling an autonomous vehicle. The method includes receiving sensor data from a plurality of sensors, determining, a plurality of probability hypotheses based upon the sensor data, and receiving metadata from at least one sensor of the plurality of sensors. An integrity level of at least one of the plurality of probability hypotheses is determined based upon the received metadata and at least one action is determined based upon the determined integrity level and at least one probability hypothesis of the plurality of probability hypotheses. The at least one action is then initiated by an electronic controller for the vehicle.

Abstract: Systems and methods for controlling a vehicle. The system includes one or more sensors positioned on the vehicle and configured to sense an environment surrounding the vehicle, a collision mitigation subsystem configured to control a braking system of the vehicle, and an autonomous driving subsystem communicatively coupled to the one or more sensors and the collision mitigation subsystem. The autonomous driving subsystem is configured to receive sensor information from the one or more sensors and generate, based on the sensor information, a model of the environment surrounding the vehicle. The autonomous driving subsystem is configured to determine, based on the model of the environment surrounding the vehicle, a plurality of possible trajectories for the vehicle and to select, from the plurality of possible trajectories, a travel path for the vehicle. The autonomous driving subsystem is configured to transmit the travel path to the collision mitigation subsystem.

Abstract: A method and device are disclosed for improved object detection in an area surrounding a robot. In the method, first and second sensing data are obtained, which can be assigned to a first or second sensing means of the robot, respectively, and which contain at least one portion of the area surrounding the robot. An objection detection of an object in the area surrounding the robot is carried out using a fusion of at least the first and the second sensing data. An item of redundancy information is generated, which is assigned to the object detection and at least indicates whether the detected object has been detected using only the first or only the second sensing data or whether the detected object or at least one or more sections of same has been detected redundantly using both the first and the second sensing data.

Abstract: A system for a vehicle, which drives in an at least in-part-automated manner is configured to determine a control signal for a control system. The system includes a sensor, a planning module, and a monitoring module. The sensor is configured to detect an object in a surrounding area of the vehicle and store a corresponding object representation. The planning module is configured to determine, based to the stored object representation, a first trajectory and a first probability of collision of the first trajectory for the vehicle. The monitoring module is configured to perform one of following actions when the first probability of collision exceeds a predefined probability of collision: determine, using the planning module and based on the stored object representation, a further trajectory having a further probability of collision and a maximum deceleration of the further trajectory; or assess the stored object representation of the object using the sensor.

Abstract: Redundant environment perception tracking for automated driving systems. One example embodiment provides a surveillance system, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor of the first sensor type, and track the object based on the object state that is determined.

Abstract: A system and method for estimating an orientation of a traffic participant. In one example, the system includes a sensor configured to detect a traffic participant and an electronic controller configured to receive a signal from the sensor, compare a location of the vehicle to a map of expected orientation of traffic participants to estimate an orientation of the traffic participant, perform a calculation based upon the signal from the sensor to estimate an orientation of the traffic participant if an expected orientation is not determined by the comparison of the location of the vehicle to the map of expected orientation of traffic participants, and generate a notification based upon the estimated orientation of the traffic participant.

Abstract: Systems and methods for controlling a vehicle. The system includes one or more sensors positioned on the vehicle and configured to sense an environment surrounding the vehicle, a collision mitigation subsystem configured to control a braking system of the vehicle, and an autonomous driving subsystem communicatively coupled to the one or more sensors and the collision mitigation subsystem. The autonomous driving subsystem is configured to receive sensor information from the one or more sensors and generate, based on the sensor information, a model of the environment surrounding the vehicle. The autonomous driving subsystem is configured to determine, based on the model of the environment surrounding the vehicle, a plurality of possible trajectories for the vehicle and to select, from the plurality of possible trajectories, a travel path for the vehicle. The autonomous driving subsystem is configured to transmit the travel path to the collision mitigation subsystem.

Abstract: Redundant environment perception tracking for automated driving systems. One example embodiment provides an automated driving system for a vehicle, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor, and perform a vehicular maneuver based on the object state that is determined.

Abstract: Methods and systems for multi-hypothesis object tracking for automated driving systems. One system includes an electronic processor configured to receive environment information and generate pseudo-measurement data associated with an object within an environment of the vehicle. The electronic processor is also configured to determine, based on the environment information and the pseudo-measurement data, a set of association hypotheses regarding the object. The electronic processor is also configured to determine, based on the set of association hypotheses, an object state of the object. The electronic processor is also configured to control the vehicle based on the determined object state.

Abstract: Redundant environment perception tracking for automated driving systems. One example embodiment provides an automated driving system for a vehicle, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor, and perform a vehicular maneuver based on the object state that is determined.

Abstract: Methods and systems for controlling an autonomous vehicle. The method includes receiving sensor data from a plurality of sensors, determining, a plurality of probability hypotheses based upon the sensor data, and receiving metadata from at least one sensor of the plurality of sensors. An integrity level of at least one of the plurality of probability hypotheses is determined based upon the received metadata and at least one action is determined based upon the determined integrity level and at least one probability hypothesis of the plurality of probability hypotheses. The at least one action is then initiated by an electronic controller for the vehicle.

Abstract: A system for a reliability of objects for a driver assistance or automated driving of a vehicle includes a plurality of sensors that include one or more sensor modalities for providing sensor data for the objects. An electronic tracking unit is configured to receive the sensor data to determine a detection probability (p_D) for each of the plurality of sensors for each of the objects, to determine an existence probability (p_ex) for each of the plurality of sensors for each of the objects, and to provide vectors for each of the objects based on the existence probability (p_ex) for each contributing one of the plurality of sensors for the specific object. The vectors are provided by the electronic tracking unit for display as an object interface on a display device. The vectors are independent from the sensor data from the plurality of sensors.

Abstract: A system and method for estimating an orientation of a traffic participant. In one example, the system includes a sensor configured to detect a traffic participant and an electronic controller configured to receive a signal from the sensor, compare a location of the vehicle to a map of expected orientation of traffic participants to estimate an orientation of the traffic participant, perform a calculation based upon the signal from the sensor to estimate an orientation of the traffic participant if an expected orientation is not determined by the comparison of the location of the vehicle to the map of expected orientation of traffic participants, and generate a notification based upon the estimated orientation of the traffic participant.

Abstract: A system for a vehicle, which drives in an at least in-part-automated manner is configured to determine a control signal for a control system. The system includes a sensor, a planning module, and a monitoring module. The sensor is configured to detect an object in a surrounding area of the vehicle and store a corresponding object representation. The planning module is configured to determine, based to the stored object representation, a first trajectory and a first probability of collision of the first trajectory for the vehicle. The monitoring module is configured to perform one of following actions when the first probability of collision exceeds a predefined probability of collision: determine, using the planning module and based on the stored object representation, a further trajectory having a further probability of collision and a maximum deceleration of the further trajectory; or assess the stored object representation of the object using the sensor.

Abstract: A method and apparatus for determining misalignment of a radar sensor unit mounted to a vehicle includes providing targets on an alignment apparatus. A vehicle is located at predetermined location on a test station an exact given distance from the alignment apparatus. The actual locations and distances of the targets from each other and from radar sensor unit of the vehicle at the test station are known and pre-stored. At least one target is a greater distance from the vehicle than the other targets. The targets receive and return a radar wave from the radar sensor unit. The radar sensor unit determines locations and distances of the targets and compares with the given or actual locations and distances of the targets to determine misalignment of the radar sensor unit. A calibration program automatically calibrates azimuth and elevation to adjust for misalignment.

Abstract: A system and a corresponding method for sensing the driving environment of a vehicle, the system having a plurality of sensors for capturing objects in the area surrounding the vehicle. The system has a plurality of evaluation units, an evaluation unit being bijectively associated in each case with a specific sensor and being adapted for analyzing a measurement performed by the sensor using a sensor model and for creating a data object to describe a particular object captured by the sensor. In addition, at least one driving-environment modeling unit is provided that is linked to each evaluation unit and is adapted for computing a driving environment model to describe the environment of the vehicle on the basis of the data objects. An evaluation unit and the at least one driving-environment modeling unit are thereby designed in a way that makes the sensor model more complex than the driving environment model.