Abstract: An object of the present invention is to provide a method capable of calibrating a sensor function required in a safety design of a radar safety sensor in real time. A calibration station (11) is provided on a traveling route of an unmanned vehicle (1) on which a safety sensor (3) for detecting an obstacle (2) ahead is mounted, and a standard reflection is provided at a position of a maximum measurement distance (L) of the safety sensor (3) at the calibration station (11). Prior to normal traveling of the unmanned trolley 1, the unmanned trolley 1 is moved to the calibration station 11 in advance, and the reference value obtained by measuring the standard reflector 12 with the safety sensor 3 is taught, During normal operation of the unmanned trolley 1, every time the unmanned trolley 1 reaches the calibration station 11, the measured value obtained by measuring the standard reflector 12 by the safety sensor 3 is compared with a reference value. Calibrate the sensor function of FIG. 1.

Abstract: A method and a system for generating a mesh representation of a surface. The method includes receiving a three-dimensional (3D) point cloud representing the surface, generating a reconstruction dataset having a higher resolution than the 3D point cloud in one or more regions corresponding to the surface from the 3D point cloud, and generate a polygon mesh representation of the surface by using a fine-to-coarse hash map for building polygons at a highest resolution first followed by progressively coarser resolution polygons, using the reconstruction dataset.

Abstract: This document describes methods by which an autonomous vehicle deploys a simulation scenario while operating in a real-world environment. The vehicle's sensors collect perception data. During a run of the vehicle in a real-world environment, the vehicle's on-board computing system will: (i) receive the perception data; (ii) publish the perception data to a muxing tool of the on-board computing system; (iii) generate simulation data that identifies and labels one or more simulated objects in the environment; (iv) publish the simulation data to the muxing tool; (v) use the muxing tool to add at least a portion of the simulation data to the perception data to yield augmented perception data; and (v) use at least a portion of the augmented perception data to make one or more navigation decisions based for the autonomous vehicle.

Abstract: Disclosed herein are system, method, and computer program product embodiments for localizing three-dimensional objects relative to a vehicle. The system includes: at least one sensor for generating two-dimensional (2D) data and a three-dimensional (3D) point cloud of an environment external to a vehicle. The 3D point cloud includes object points associated with a stationary traffic control object. The localization system also includes a memory and at least one processor coupled to the memory. The processor is programmed to: select a bounding box associated with the object from the memory based on the 2D data; arrange the bounding box proximate to the object points in the 3D point cloud; assign a weight to each point of the 3D point cloud based on a position of the point relative to the bounding box; filter the weighted points; and generate a 3D location of the object based on the filtered points.

Abstract: A system of creating a simulation scenario definition to simulate behavior of an autonomous vehicle includes a computing device and a computer-readable storage medium having one or more programming instructions. The system identifies an event on which a simulation scenario definition is to be based, identifies one or more log files associated with the event, parses the one or more log files in a time-sequential order and populates the simulation scenario definition with information from the identified log files until an event trigger is detected, identifies an actor from one or more of the log files, infer a shape of the actor, generates one or more simulated tracks that includes the inferred shape for the actor, and adds the simulated tracks to the simulation scenario definition.

Abstract: A system, method, and computer program for updating calibration lookup tables within an autonomous vehicle or transmitting roadway marking changes between online and offline mapping files is disclosed. A LIDAR sensor may be used for generating an online (rasterized) mapping file with online intensity values which are compared against a correlated offline (rasterized) mapping file having offline intensity values. The online intensity value may be used to acquire a lookup table having a normal distribution that is compared against the offline intensity value. The lookup table may be updated when the offline intensity value is within the normal distribution. Or the vehicle may transmit a roadway marking change when the offline intensity value is outside the normal distribution.

Abstract: Disclosed herein are system and method embodiments to implement a validation of an SfM map. An embodiment operates by receiving a motion-generated map corresponding to a digital image, generating a first depth map, wherein the first depth map comprises depth information for one or more triangulated points located within the motion generated image. The embodiment further receives a light detection and ranging (lidar) generated point cloud including at least a portion of the one or more triangulated points, splats the lidar point cloud proximate to the portion of the one or more triangulated points and generates a second depth map for the portion and identifies an incorrect triangulated point, of the one or more triangulated points, based on comparing the first depth information to the second depth information. The incorrect triangulated points may be removed from the SfM map or marked with a low degree of confidence.

Abstract: A kind of electromagnetic vehicle pulse effects various dimensions remote online monitoring system of the present invention belongs to technical field of electromagnetic compatibility measurement, its structure has CAN bus to diagnose subsystem (1), audio-video monitoring subsystem (2), induced voltage measurement subsystem (3), fiber distribution network (4) and remote control subsystem (5), wherein, remote control subsystem 5 is connected respectively to CAN bus by fiber distribution network (4) and diagnoses subsystem (1), audio-video monitoring subsystem (2) and induced voltage measurement subsystem (3).

Abstract: Systems and methods for operating an autonomous vehicle. The methods comprising: obtaining, by a computing device, a LiDAR dataset; plotting, by a computing device, the LiDAR dataset on a 3D graph to define a 3D point cloud; using, by a computing device, the LiDAR dataset and contents of a vector map to define a cuboid on the 3D graph that encompasses points of the 3D point cloud that are associated with an object in proximity to the vehicle, where the vector map comprises lane information; and using the cuboid to facilitate driving-related operations of the autonomous vehicle.

Abstract: Devices, systems, and methods are provided for mitigating vehicle power loss. A vehicle charging system may include a power supply, and a voltage control device associated with receiving first voltage from the power supply, providing the first voltage to a hybrid vehicle or a battery electric vehicle, and blocking a second voltage from the hybrid vehicle or the battery electric vehicle, wherein the vehicle charging system is external to the hybrid vehicle or the battery electric vehicle.

Abstract: Systems and methods are provided herein for improved short range object detection in LiDAR systems. The associated systems may include a first portion and a second portion configured to rotate relative to one another. The system may also include a first magnet located on the second portion and arranged with a north pole of the first magnet facing a first direction. The system may also include a second magnet located on the second portion and arranged with a south pole of the second magnet facing the first direction. The system may also include a first sensor located on the first portion, wherein the first sensor is further configured to measure a first magnetic field of the first magnet and a second magnetic field of the second magnet as the first portion and second portion rotate relative to one another.

Abstract: Systems, methods, and computer-readable media are disclosed for a systems and methods for intra-shot dynamic LIDAR detector gain. One example method my include receiving first image data associated with a first image of an object illuminated at a first wavelength and captured by a camera at the first wavelength, the first image data including first pixel data for a first pixel of the first image and second pixel data for a second pixel of the first image. The example method may also include calculating a first reflectance value for the first pixel using the first pixel data. The example method may also include calculating a second reflectance value for the second pixel using the second pixel data. The example method may also include generating, using first reflectance value and the second reflectance value, a first reflectance distribution of the object.

Abstract: A system includes one or more electronic devices of an autonomous vehicle and a computer-readable storage medium having one or more programming instructions. The system identifies an actor in an environment of the autonomous vehicle that is exhibiting unrecognized behavior or that has exhibited unrecognized behavior within a certain time period, and generates a circle associated with the actor, wherein the circle has a radius that is a function of a velocity of the actor. The system identifies one or more target points associated with the actor, where each target point represents a point along a possible route of the actor, and each target point is located along a circumference of the circle. The system assigns a score to each target point, selects the target point associated with the lowest score, and generates a reference path from the actor to the selected target point.

Abstract: Systems and methods are provided for detecting a flashing light on one or more traffic signal devices. The method includes capturing a series of images of one or more traffic signal elements in a traffic signal device over a length of time. The method further includes, for each traffic signal element, analyzing the series of images to determine one or more time periods at which the traffic signal element is in an on state or an off state, and analyzing the time periods to determine one or more distinct on states and one or more distinct off states. The method further includes identifying one or more cycles correlating to a distinct on state immediately followed by a distinct off state, or a distinct off state immediately followed by a distinct on state, and, upon identifying a threshold number adjacent cycles, classifying the traffic signal element as a flashing light.

Abstract: Systems and methods are described for measuring velocity of an object detected by a light detection and ranging (lidar) system. According to some aspects a method may include receiving a lidar dataset generated by the lidar system, transforming the lidar dataset into a first layer dataset and a second layer dataset, and converting the first layer dataset into a first image and the second layer dataset into a second image. The method may also include performing a feature detection operation that identifies at least one feature in the first image and the same feature in the second image, locating a first location of the feature in the first image and a second location of the feature in the second image, and generating a velocity estimate of the feature based on a difference between the first location and the second location and a difference between the different time intervals.

Abstract: A system and method for performing visual localization is disclosed. In aspects, the system implements methods to generate a global point cloud, the global point cloud representing a plurality of point clouds. The global point cloud can be mapped to a prior map information to locate a position of an autonomous vehicle, the prior map information representing pre-built geographic maps. The position of the autonomous vehicle can be estimated based on applying sensor information obtained from sensors and software of the autonomous vehicle to the mapped global point cloud.

Abstract: A system and method for transmitting data using an autonomous vehicle's LIDAR system. The autonomous vehicle may transmit the data by disengaging the LIDAR system's transmitters and receivers from operating to detect external objects. The autonomous vehicle may also rotate the LIDAR system to locate one of a plurality of receivers external to the autonomous vehicle. Data stored within the autonomous vehicle may then be transmitted to an external system using a light-based communication path established between at least one of the LIDAR system's transmitters and an external receiver. The LIDAR system's transmitters and receivers may then be re-engaged so as to be operable to detect external objects.

Abstract: Systems, methods, and computer-readable media are disclosed for a systems and methods for improved smart infrastructure data transfer. An example method may involve identifying that a software update is available for a smart infrastructure system. The example method may also involve determining, by a processor of the smart infrastructure system and using a signal strength between a first vehicle and the smart infrastructure system, that the first vehicle is within a threshold range of the smart infrastructure system. The example method may also involve establishing, by the smart infrastructure system, a first ad-hoc peer-to-peer communication link with the first vehicle. The example method may also involve sending, to the vehicle, a request for the software update. The example method may also involve receiving, from the vehicle, at least a first portion of the software update that is transferred using the first ad-hoc peer-to-peer communication link.

Abstract: A method for developing a map of objects in a region surrounding a location is disclosed. The method includes interrogating the region along a detection axis with a series of optical pulses and detecting reflections of the optical pulses that originate at objects located along the detection axis. A multi-dimensional map of the region is developed by scanning the detection axis about the location in at least one dimension. The reflections are detected via a single-photon detector that is armed using a sub-gating scheme such that the single-photon detector selectively detects photons of reflections that originate only within each of a plurality of zones that collectively define the detection field. In some embodiments, the optical pulses have a wavelength within the range of 1350 nm to 1390 nm, which is a spectral range having a relatively high eye-safety threshold and a relatively low solar background.

Abstract: Devices, systems, and methods are provided for classifying detected objects as static or dynamic. A device may determine first light detection and ranging (LIDAR) data associated with a convex hull of an object at a first time, and determine second LIDAR data associated with the convex hull at a second time after the first time. The device may generate, based on the first LIDAR data and the second LIDAR data, a vector including values of features associated with the first convex hull and the second convex hull. The device may determine, based on the vector, a probability that the object is static. The device may operate a machine based on the probability that the object is static.