Abstract: A system includes at least one processor configured to detect, based on point cloud information, portions of a particular object, and determine, based on the detected portions, at least a first portion having a first reflectivity corresponding to a license plate, and at least two additional spaced-apart portions corresponding to locations on the particular object other than a location of the first portion. The at least two additional portions have reflectivity substantially lower than the first reflectivity. The at least one processor is further configured to classify the particular object as a vehicle, based on a spatial relationship and a reflectivity relationship between the first portion and the at least two additional portions.

Abstract: A vehicle-assistance system for classifying objects in a vehicle's surroundings. The system includes: at least one memory configured to store classification information for classifying a plurality of objects; and at least one processor configured to receive a plurality of detection results associated with light detection and ranging system (LIDAR) detection results, each detection result including location information, and further information indicative of at least two of the following detection characteristics: object surface reflectivity; temporal spreading of signal reflected from the object; object surface physical composition; ambient illumination measured at a LIDAR dead time; difference in detection information from a previous frame; and confidence level associated with another detection characteristic.

Abstract: A LIDAR system includes at least one processor configured to control at least one light source for projecting light toward a field of view and receive from at least one first sensor first signals associated with light projected by the at least one light source and reflected from an object in the field of view, wherein the light impinging on the at least one first sensor is in a form of a light spot having an outer boundary. The processor may further be configured to receive from at least one second sensor second signals associated with light noise, wherein the at least one second sensor is located outside the outer boundary; determine, based on the second signals received from the at least one second sensor, an indicator of a magnitude of the light noise; and determine, based on the indicator the first signals received from the at least one first sensor and, a distance to the object.

Abstract: A system includes at least one processor configured to detect, based on point cloud information, portions of a particular object, and determine, based on the detected portions, at least a first portion having a first reflectivity corresponding to a license plate, and at least two additional spaced-apart portions corresponding to locations on the particular object other than a location of the first portion. The at least two additional portions have reflectivity substantially lower than the first reflectivity. The at least one processor is further configured to classify the particular object as a vehicle, based on a spatial relationship and a reflectivity relationship between the first portion and the at least two additional portions.

Abstract: A method of processing of LIDAR measurement data including: receiving successive LIDAR 3D data sets over a time from a LIDAR system moving, during the time, through space, each LIDAR 3D data set corresponding to a measurement field of view (FOV) of the LIDAR system; identifying a plurality of objects in the LIDAR 3D data sets; designating at least one of the plurality of objects as at least one potential aggressor object; tracking position of the one or more potential aggressor objects relative to the LIDAR system as the one or more potential aggressor objects move outside of the measurement FOV of the LIDAR system; and characterizing one or more of the plurality of objects as one or more multi-path object using tracked position of the one or more potential aggressor objects.

Abstract: A vehicle-assistance system for classifying objects in a vehicle's surroundings. The system includes: at least one memory configured to store classification information for classifying a plurality of objects; and at least one processor configured to receive a plurality of detection results associated with light detection and ranging system (LIDAR) detection results, each detection result including location information, and further information indicative of at least two of the following detection characteristics: object surface reflectivity; temporal spreading of signal reflected from the object; object surface physical composition; ambient illumination measured at a LIDAR dead time; difference in detection information from a previous frame; and confidence level associated with another detection characteristic.

Abstract: A LIDAR system for use in a vehicle is provided. The LIDAR system may include at least one processor configured to control at least one light source for illuminating a field of view and scan a field of view by controlling movement of at least one deflector at which the at least one light source is directed. The at least one processor may also be configured to receive, from at least one sensor, reflections signals indicative of light reflected from an object in the field of view. The at least one processor may further be configured to detect at least one temporal distortion in the reflections signals, and determine from the at least one temporal distortion an angular orientation of at least a portion of the object.

Abstract: A vehicle-assistance system for classifying objects in a vehicle's surroundings is provided. The system may include at least one memory configured to store classification information for classifying a plurality of objects and at least one processor configured to receive, on a pixel-by-pixel basis, a plurality of measurements associated with LIDAR detection results. The measurements may include at least one of: a presence indication, a surface angle, object surface physical composition, and a reflectivity level. The at least one processor may also be configured to receive, on the pixel-by-pixel basis, at least one confidence level associated with each received measurement, and access the classification information. The at least one processor may further be configured to, based on the classification information and the received measurements with the at least one associated confidence level plurality, identify a of pixels as being associated with a particular object.

Abstract: A vehicle-assistance system for classifying objects in a vehicle's surroundings is provided. The system may include at least one memory configured to store classification information for classifying a plurality of objects and at least one processor configured to receive, on a pixel-by-pixel basis, a plurality of measurements associated with LIDAR detection results. The measurements may include at least one of: a presence indication, a surface angle, object surface physical composition, and a reflectivity level. The at least one processor may also be configured to receive, on the pixel-by-pixel basis, at least one confidence level associated with each received measurement, and access the classification information. The at least one processor may further be configured to, based on the classification information and the received measurements with the at least one associated confidence level plurality, identify a of pixels as being associated with a particular object.

Abstract: A LIDAR system for use in a vehicle is provided. The LIDAR system may include at least one processor configured to control at least one light source for illuminating a field of view and scan a field of view by controlling movement of at least one deflector at which the at least one light source is directed. The at least one processor may also be configured to receive, from at least one sensor, reflections signals indicative of light reflected from an object in the field of view. The at least one processor may further be configured to detect at least one temporal distortion in the reflections signals, and determine from the at least one temporal distortion an angular orientation of at least a portion of the object.

Abstract: A vehicle-assistance system for classifying objects in a vehicle's surroundings is provided. The system may include at least one memory configured to store classification information for classifying a plurality of objects and at least one processor configured to receive, on a pixel-by-pixel basis, a plurality of measurements associated with LIDAR detection results. The measurements may include at least one of: a presence indication, a surface angle, object surface physical composition, and a reflectivity level. The at least one processor may also be configured to receive, on the pixel-by-pixel basis, at least one confidence level associated with each received measurement, and access the classification information. The at least one processor may further be configured to, based on the classification information and the received measurements with the at least one associated confidence level plurality, identify a of pixels as being associated with a particular object.

Abstract: A LIDAR system is provided. The LIDAR system comprises at least one processor configured to: control at least one light source in a manner enabling light flux to vary over a scan of a field of view, the field of view including a first portion and a second portion; receive on a pixel-by-pixel basis, signals from at least one sensor; estimate noise in at least some of the signals associated with the first portion of the field of view; alter a sensor sensitivity for reflections associated with the first portion of the field of view; estimate noise in at least some of the signals associated with the second portion of the field of view; and alter a sensor sensitivity for reflections associated with the second portion of the field of view based on the estimation of noise in the second portion of the field of view.

Abstract: A LIDAR system is provided. The LIDAR system comprises at least one processor configured to: control at least one light source in a manner enabling light flux to vary over scans of a field of view using light from the at least one light source; control at least one light deflector to deflect light from the at least one light source; receive from at least one sensor, reflections signals indicative of light reflected from objects in the field of view; determine, based on the reflections signals of an initial light emission, whether an object is located in an immediate area of the LIDAR system and within a threshold distance from the at least one light deflector, and when no object is detected in the immediate area, control the at least one light source such that an additional light emission is projected toward the immediate area.

Abstract: A LIDAR system is provided. The LIDAR system comprises at least one processor configured to: control at least one light source in a manner enabling light flux to vary over scans of a field of view using light from the at least one light source; control at least one light deflector to deflect light from the at least one light source; receive from at least one sensor, reflections signals indicative of light reflected from objects in the field of view; determine, based on the reflections signals of an initial light emission, whether an object is located in an immediate area of the LIDAR system and within a threshold distance from the at least one light deflector, and when no object is detected in the immediate area, control the at least one light source such that an additional light emission is projected toward the immediate area.

Abstract: A LIDAR system is provided. The LIDAR system comprises at least one processor configured to: control at least one light source in a manner enabling light flux to vary over a scan of a field of view, the field of view including a first portion and a second portion; receive on a pixel-by-pixel basis, signals from at least one sensor; estimate noise in at least some of the signals associated with the first portion of the field of view; alter a sensor sensitivity for reflections associated with the first portion of the field of view; estimate noise in at least some of the signals associated with the second portion of the field of view; and alter a sensor sensitivity for reflections associated with the second portion of the field of view based on the estimation of noise in the second portion of the field of view.