Abstract: At a first timestep, one or more first objects can be determined in a first fusion image based on determining one or more first radar clusters in first radar data and determining one or more first two-dimensional bounding boxes in first camera data. First detected objects and first undetected objects can be determined by inputting the first objects and the first radar clusters into a data association algorithm, which determines first probabilities and adds the first radar clusters and the first objects to one or more of first detected objects or first undetected objects by determining a cost function. The first detected objects and the first undetected objects can be input to a first Poisson multi-Bernoulli mixture (PMBM) filter to determine second detected objects, second undetected objects and second probabilities. The second detected objects and the second undetected objects can be reduced based on the second probabilities determined by the first PMBM filter and the second detected objects can be output.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect a plurality of data sets, each data set from a respective sensor in a plurality of sensors, and each data set including a range, an azimuth angle, and a range rate for a detection point of the respective one of the sensors on an object to determine, for each detection point, a radial component of a ground speed of the detection point based on the data set associated with the detection point and a speed of a vehicle, and to generate a plurality of clusters, each cluster including selected detection points within a distance threshold from each other and having respective radial components of ground speeds that are (1) above a first threshold and (2) within a second threshold of each other.

Abstract: Systems, methods, and devices for authenticating vehicle-to-vehicle communication are disclosed. A method includes receiving sensor data from a first vehicle and receiving secondary sensor data from a second vehicle. The method includes extracting, based on the sensor data and the secondary sensor data, an authentication comprising one or more of: a proximity of the second vehicle to the first vehicle or a common object identified by the sensor data and the secondary sensor data. The method includes determining whether the authentication satisfies a trust threshold of the first vehicle.

Abstract: A vehicle trailer detection system includes a radar system and a controller receiving object point location data from the radar system at an increased sensitivity level, storing sequential first and second object point location data sets, and applying a rotational point set registration to the first and second object point location data sets to achieve a match between a subset of persistent point locations within the first and second object point location data sets to output an estimated rotation angle. The persistent point locations in the first and second data sets are determined to correspond with detected points on a trailer coupled with the vehicle. The controller refines the estimated rotation angle by minimizing an error in matching between the persistent point locations in the first and second object point location data sets to output a determined hitch angle between the trailer and the vehicle about a coupling point.

Abstract: A trailer detection system for a vehicle includes a radar system outputting object point location data to a rear of the vehicle and a controller. The controller receives the object point location data and determines a position of an edge of the trailer relative to the vehicle by processing the object point location data from the radar system at a reduced threshold relative to use of the data in detecting a vehicle and filters out object point location data not correlated with the edge of the trailer based on object point location data persistence during driving of the vehicle. The controller further correlates the determined position of the edge of the trailer relative to the vehicle to determine an angle of the trailer relative to the vehicle about a coupling point.

Abstract: A vehicle trailer detection system includes a radar system and a controller receiving object point location data from the radar system at an increased sensitivity level, storing sequential first and second object point location data sets, and applying a rotational point set registration to the first and second object point location data sets to achieve a match between a subset of persistent point locations within the first and second object point location data sets to output an estimated rotation angle. The persistent point locations in the first and second data sets are determined to correspond with detected points on a trailer coupled with the vehicle. The controller refines the estimated rotation angle by minimizing an error in matching between the persistent point locations in the first and second object point location data sets to output a determined hitch angle between the trailer and the vehicle about a coupling point.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect at least one set of data with a first Doppler sensor, each set of data including a radial distance, an azimuth angle and a range rate between the first Doppler sensor and a target, collect at least one set of data with a second Doppler sensor, determine that the collected sets of data include a first, second, and third set, determine respective radial components of a ground velocity of the target based on the first, second and third sets of data a position on a host vehicle of the respective Doppler sensor that collected the sets of data, and determine a linear velocity of the target and a yaw rate of the target based on the radial components of the ground velocity of the target.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect a plurality of data sets, each data set from a respective sensor in a plurality of sensors, and each data set including a range, an azimuth angle, and a range rate for a detection point of the respective one of the sensors on an object to determine, for each detection point, a radial component of a ground speed of the detection point based on the data set associated with the detection point and a speed of a vehicle, and to generate a plurality of clusters, each cluster including selected detection points within a distance threshold from each other and having respective radial components of ground speeds that are (1) above a first threshold and (2) within a second threshold of each other.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect at least one set of data with a first Doppler sensor, each set of data including a radial distance, an azimuth angle and a range rate between the first Doppler sensor and a target, collect at least one set of data with a second Doppler sensor, determine that the collected sets of data include a first, second, and third set, determine respective radial components of a ground velocity of the target based on the first, second and third sets of data a position on a host vehicle of the respective Doppler sensor that collected the sets of data, and determine a linear velocity of the target and a yaw rate of the target based on the radial components of the ground velocity of the target.

Abstract: A trailer detection system for a vehicle includes a radar system outputting object point location data to a rear of the vehicle and a controller. The controller receives the object point location data and determines a position of an edge of the trailer relative to the vehicle by processing the object point location data from the radar system at a reduced threshold relative to use of the data in detecting a vehicle and filters out object point location data not correlated with the edge of the trailer based on object point location data persistence during driving of the vehicle. The controller further correlates the determined position of the edge of the trailer relative to the vehicle to determine an angle of the trailer relative to the vehicle about a coupling point.

Abstract: Systems, methods, and devices for authenticating vehicle-to-vehicle communication are disclosed. A method includes receiving sensor data from a first vehicle and receiving secondary sensor data from a second vehicle. The method includes extracting, based on the sensor data and the secondary sensor data, an authentication comprising one or more of: a proximity of the second vehicle to the first vehicle or a common object identified by the sensor data and the secondary sensor data. The method includes determining whether the authentication satisfies a trust threshold of the first vehicle.

Abstract: Systems, methods, and devices for authenticating vehicle-to-vehicle communication are disclosed. A method includes receiving sensor data from a first vehicle and receiving secondary sensor data from a second vehicle. The method includes extracting, based on the sensor data and the secondary sensor data, an authentication comprising one or more of: a proximity of the second vehicle to the first vehicle or a common object identified by the sensor data and the secondary sensor data. The method includes determining whether the authentication satisfies a trust threshold of the first vehicle.

Abstract: Systems, methods, and apparatuses are disclosed for providing routing and navigational information to users (e.g., visually handicapped users). Example methods may include determining, by one or more computer processors coupled to at least one memory, a first location of a user device and an orientation of a user device, and generating a first route based on the first location, the first orientation, and a destination location. Further, the method may include determining one or more obstacles on the first route using data corresponding to visual information and one or more artificial intelligence techniques; and generating a second route based on the one or more obstacles detected on the first route.

Abstract: Techniques and examples pertaining to vehicle odometry using one or more radars disposed on a vehicle are described. A method for radar odometry may involve receiving, by a processor from the radars, measurement data of stationary objects and moving objects that are located in an environment a vehicle is traversing. The method may also involve performing, by the processor, a random sample consensus (RANSAC) calculation to select the measurement data of the stationary objects and disregard the measurement data of the moving objects. The method may also involve calculating, by the processor, one or more dynamic variables of the vehicle based on the measurement data of the stationary objects. The proposed method processes the measurement data of the stationary objects with one single RANSAC calculation and one least squares problem solving, thereby greatly reducing computation cost and time as well as latency in operation for providing the vehicle odometry.

Abstract: Systems, methods, and apparatuses are disclosed for providing routing and navigational information to users (e.g., visually handicapped users). Example methods may include determining, by one or more computer processors coupled to at least one memory, a first location of a user device and an orientation of a user device, and generating a first route based on the first location, the first orientation, and a destination location. Further, the method may include determining one or more obstacles on the first route using data corresponding to visual information and one or more artificial intelligence techniques; and generating a second route based on the one or more obstacles detected on the first route.

Abstract: Techniques and examples pertaining to vehicle odometry using one or more radars disposed on a vehicle are described. A method for radar odometry may involve receiving, by a processor from the radars, measurement data of stationary objects and moving objects that are located in an environment a vehicle is traversing. The method may also involve performing, by the processor, a random sample consensus (RANSAC) calculation to select the measurement data of the stationary objects and disregard the measurement data of the moving objects. The method may also involve calculating, by the processor, one or more dynamic variables of the vehicle based on the measurement data of the stationary objects. The proposed method processes the measurement data of the stationary objects with one single RANSAC calculation and one least squares problem solving, thereby greatly reducing computation cost and time as well as latency in operation for providing the vehicle odometry.

Abstract: Systems, methods, and devices for authenticating vehicle-to-vehicle communication are disclosed. A method includes receiving sensor data from a first vehicle and receiving secondary sensor data from a second vehicle. The method includes extracting, based on the sensor data and the secondary sensor data, an authentication comprising one or more of: a proximity of the second vehicle to the first vehicle or a common object identified by the sensor data and the secondary sensor data. The method includes determining whether the authentication satisfies a trust threshold of the first vehicle.