Patent classifications
G01S2013/93185
DEEP LEARNING FOR OBJECT DETECTION USING PILLARS
Among other things, we describe techniques for detecting objects in the environment surrounding a vehicle. A computer system is configured to receive a set of measurements from a sensor of a vehicle. The set of measurements includes a plurality of data points that represent a plurality of objects in a 3D space surrounding the vehicle. The system divides the 3D space into a plurality of pillars. The system then assigns each data point of the plurality of data points to a pillar in the plurality of pillars. The system generates a pseudo-image based on the plurality of pillars. The pseudo-image includes, for each pillar of the plurality of pillars, a corresponding feature representation of data points assigned to the pillar. The system detects the plurality of objects based on an analysis of the pseudo-image. The system then operates the vehicle based upon the detecting of the objects.
Vehicle control method and vehicle control device
A vehicle control method is provided such that when a host vehicle is stopped at a front of a vehicle line of vehicles in accordance with a stop signal of a traffic light at an intersection, the engine is stopped by using an idle stop control. When either a left-turn or a right-turn will be made after the traffic light changes to a go signal, a presence or an absence of a traveling body, which is stopped on a side of or behind the host vehicle in a direction from which the host vehicle is turning, is detected during the stop signal. Upon determining the traveling body is stopped on the side of host vehicle, restarting of the engine is placed on standby even when the traffic light turns to the go signal, and the engine is restarted in accordance with a behavior of the traveling body.
Split-Steer Amplifier with Invertible Output
A split-steer amplifier with an invertible phase output, includes a first transistor having its base coupled to a positive node of an input port, its emitter coupled to ground, and collector connected to a positive intermediate node; a second transistor having its base coupled to a negative node of the input port, its emitter coupled to ground, and collector connected to a negative intermediate node; and multiple output ports each having a transistor arrangement operable to couple a positive node of that output port to the positive intermediate node and a negative node of that output port to the negative intermediate node, operable to couple the positive node of that output port to the negative intermediate node and the negative node of that output port to the positive intermediate node, and operable to decouple the positive node and the negative node of that output port from the intermediate nodes.
FILTERING AND AGGREGATING DETECTION POINTS OF A RADAR POINT CLOUD FOR AN AUTONOMOUS VEHICLE
A scan aggregator and filter for an autonomous vehicle includes a plurality of radar sensors, where each radar sensor performs a plurality of individual scans of a surrounding environment to obtain data in the form of a radar point cloud including a plurality of detection points. The scan aggregator and filter also includes an automated driving controller in electronic communication with the plurality of radar sensors. The automated driving controller is instructed to filter each of the individual scans to define a spatial region of interest and to remove the detection points of the radar point cloud that represent moving objects based on a first outlier-robust model estimation algorithm. The automated driving controller aggregates a predefined number of individual scans together based on a motion compensated aggregation technique to create an aggregated data scan and applies a plurality of density-based clustering algorithms to filter the aggregated data scan.
Compensating for a sensor deficiency in a heterogeneous sensor array
Apparatuses, methods and storage medium associated with compensating for a sensor deficiency in a heterogeneous sensor array are disclosed herein. In embodiments, an apparatus may include a compute device to aggregate perception data from individual perception pipelines, each of which is associated with respective one of different types of sensors of a heterogeneous sensor set, to identify a characteristic associated with a space to be monitored by the heterogeneous sensor set; detect a sensor deficiency associated with a first sensor of the sensors; and in response to a detection of the sensor deficiency, derive next perception data for more than one of the individual perception pipelines from sensor data originating from at least one second sensor of the sensors. Other embodiments may be disclosed or claimed.
COMPENSATING FOR A SENSOR DEFICIENCY IN A HETEROGENEOUS SENSOR ARRAY
Apparatuses, methods and storage medium associated with compensating for a sensor deficiency in a heterogeneous sensor array are disclosed herein. In embodiments, an apparatus may include a compute device to aggregate perception data from individual perception pipelines, each of which is associated with respective one of different types of sensors of a heterogeneous sensor set, to identify a characteristic associated with a space to be monitored by the heterogeneous sensor set; detect a sensor deficiency associated with a first sensor of the sensors; and in response to a detection of the sensor deficiency, derive next perception data for more than one of the individual perception pipelines from sensor data originating from at least one second sensor of the sensors. Other embodiments may be disclosed or claimed.
SENSOR ASSEMBLY WITH LIDAR FOR AUTONOMOUS VEHICLES
A sensor assembly for autonomous vehicles includes a side mirror assembly configured to mount to a vehicle. The side mirror assembly includes a first camera having a field of view in a direction opposite a direction of forward travel of the vehicle; a second camera having a field of view in the direction of forward travel of the vehicle; and a third camera having a field of view in a direction substantially perpendicular to the direction of forward travel of the vehicle. The first camera, the second camera, and the third camera are oriented to provide, in combination with a fourth camera configured to be mounted on a roof of the vehicle, an uninterrupted camera field of view from the direction of forward travel of the vehicle to a direction opposite the direction of forward travel of the vehicle.
Lane Detection and Alert System
A lane detection system for a vehicle includes at least one sensor for sensing lane markers and objects in the vicinity of a host vehicle, a driver interface in the host vehicle, and a controller having control logic. The control logic receives signals from the at least one sensor, determines a present lane of travel based on the sensor signals received, determines that a time that the host vehicle has been in the present lane of travel meets or exceeds a predetermined time, and transmits an alert signal to the driver interface in response to the time meeting or exceeding the predetermined time.
Determining a motion state of a target object
Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.
Laser waveform embedding
A system includes a light detection and ranging device configured to generate, for each respective point of a plurality of points in an environment, a corresponding waveform that represents physical characteristics of the respective point. The system also includes a signal processor configured to determine, based on the corresponding waveform of each respective point, a map of the environment that includes a representation of a corresponding position of the respective point. The system additionally includes an embedding model configured to determine, for each respective point and based on the corresponding waveform, a corresponding vector comprising a plurality of values representative of the physical characteristics of the respective point. The system further includes a feature detector configured to detect or classify a physical feature based on (i) the corresponding positions of one or more points of the plurality of points and (ii) the corresponding vectors of the one or more points.