Abstract: A computing system includes one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations. The operations include determining that a portion of an existing map is to be updated; obtaining a point cloud acquired by one or more Lidar sensors corresponding to a location of the portion; converting the portion into an equivalent point cloud; performing a point cloud registration based on the equivalent point cloud and the point cloud; and updating the existing map based on the point cloud registration.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for collision prevention. In some embodiments, a trajectory of a vehicle with respect to an object can be determined using a trajectory prediction model and sensor data associated with the vehicle and the object. Based on the trajectory, a collision event involving the vehicle and the object can be determined and one or more collision protection devices can be activated.

Abstract: Provided herein is a system and method for determining whether a sensor is calibrated and error handling of an uncalibrated sensor. The system comprises a sensor system comprising a sensor and an analysis engine configured to determine whether the sensor is uncalibrated. The system further comprises an error handling system configured to perform an error handling in response to the sensor system determining that the sensor is uncalibrated. The method comprises determining, by a sensor system, whether the sensor is uncalibrated, and performing, by an error handling system, an error handling in response to the sensor system determining that the sensor is uncalibrated.

Abstract: Provided herein is a system and method for calibrating sensors. The system comprises a sensor to capture first data, an analysis engine to determine whether the sensor is to be calibrated, and a communication engine to transmit the first data from the sensor to the analysis engine and transmit information to an error handling module that the sensor is to be calibrated, in response to a determination that the sensor is to be calibrated. The determining is based on a result from a first validation of the first data, which is based on a known parameter of the sensor or historical data.

Abstract: Provided herein is a system and method for implementing one or more strategies in response to a condition inside a vehicle. The system comprises a sensor to capture data, one or more processors, and a memory storing instructions that cause the one or more processors to detect, based on the data, a condition in the vehicle, determine a level of severity of the condition, and determine one or more strategies in response to a determined level of severity of the condition. The system further implements the one or more strategies to resolve the condition.

Abstract: A method and a system for simulating driving operation of the autonomous vehicle are described. The method comprising initializing driving environment data using navigation information associated with the autonomous vehicle, and receiving control data from one or more sensors, wherein the control data affects driving operation of the autonomous vehicle. The method further comprises controlling the driving operation of the autonomous vehicle based on the driving environment data and the control data received, and directing movement of the movable platform on which the autonomous vehicle is placed, based on the driving operation of the vehicle controlled to emulate the movement of the autonomous vehicle.

Abstract: Provided herein is a system comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: identifying, in a map, one or more entities that change over time; predicting an amount of change of the identified one or more entities over time; and updating the map based on the predicted amount of change of the identified one or more entities over time.

Abstract: A computer-implemented method and a system for training a computer-based autonomous driving model used for an autonomous driving operation by an autonomous vehicle are described. The method includes: creating time-dependent three-dimensional (3D) traffic environment data using at least one of real traffic element data and simulated traffic element data; creating simulated time-dependent 3D traffic environmental data by applying a time-dependent 3D generic adversarial network (GAN) model to the created time-dependent 3D traffic environment data; and training a computer-based autonomous driving model using the simulated time-dependent 3D traffic environmental data.

Abstract: Provided herein is a system and method of a vehicle that detects a signal and reacts to the signal. The system comprises one or more sensors; one or more processors; a memory storing instructions that, when executed by the one or more processors, causes the system to perform detecting a signal from a source; determining an intended action of the vehicle based on the detected signal; sending, to the source, a response signal indicative of the intended action; determining whether the source has sent a response to the response signal; and in response to determining that the source has sent a response to the response signal, taking the intended action based on the response to the response signal.

Abstract: Provided herein is a system and method for providing a vehicle navigation in response to broken or uncalibrated vehicle sensors. The system comprises a sensor to capture data, one or more processors, and a memory storing instructions that cause the system to determine whether the sensor is broken or uncalibrated based on the data, and to limit a range of motion of the vehicle when the sensor is determined to be broken or uncalibrated. The limiting a range of motion of the vehicle includes limiting a number of driving options for the vehicle when the sensor is broken.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for determining a direction of movement of an authority vehicle in relation to another vehicle such as an autonomous vehicle and initiating or ceasing a vehicle response measure that may have previously been initiated based on the determined direction of movement. A signal source associated with the authority vehicle emits a periodic acoustic signal that is received at one or more audio capture devices, which may be provided at various locations on an exterior of a vehicle. One or more signal characteristics of the acoustic signal can be determined such as frequency, sound intensity, and/or phase. Detected signal characteristic(s) of the acoustic signal can be analyzed, and in some cases, compared against known information such as an expected frequency of the acoustic signal to determine the direction of movement of the authority vehicle in relation to the vehicle.

Abstract: A method comprises obtaining one or more parameters of an autonomous vehicle, the parameters including any of a position, path, and/or speed of the autonomous vehicle. The method further includes identifying, based on the one or more parameters of the autonomous vehicle, a region of interest from a plurality of regions surrounding the autonomous vehicle. The method further includes controlling, based on the region of interest, one or more sensors mounted on a surface of the autonomous vehicle to capture sensor data of the region of interest and not capture sensor data from the one or more other regions of the plurality of regions surrounding the autonomous vehicle. The method further includes providing the captured sensor data to a processor, the processor being capable of facilitating, based on the captured sensor data of the region of interest, one or more autonomous vehicle driving actions.

Abstract: A method comprises obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an autonomous vehicle in response to a user interacting with the tactile-sensitive surface material. Other sensor data is obtained from one or more other sensors disposed within the autonomous vehicle. The smart seat sensor data and the other sensor data are integrated. A behavior of the user is estimated based on the integrated data, and the autonomous vehicle is controlled based on the estimated behavior of the user.

Abstract: Provided herein is a system and method that acquires data and determines a driving action based on the data. The system comprises a sensor, one or more processors, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform, determining data of interest comprising an object, feature, or region of interest, determining whether a sharpness of the data of interest exceeds a threshold, in response to determining that the sharpness does not exceed a threshold, operating the sensor to increase the sharpness of the data of interest until the sharpness exceeds the threshold, in response to the sharpness exceeding the threshold, determining a driving action of a vehicle based on the data of interest, and performing the driving action.

Abstract: Provided herein is a system that comprises one or more sensors that capture data, one or more processors, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform functions that include identifying one or more locations within a distance of the vehicle, capturing current data of the identified one or more locations, determining one or more changes that exceed respective threshold amounts between the current data and historical data of the identified one or more locations, and updating the historical data of the identified one or more locations based on the determined one or more changes.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for predetermining adjustment objects and modifying vehicle lighting unit(s) accordingly. A vehicle lighting system can comprise an imaging device configured to image the surroundings of a vehicle and a data communications device configured to obtain vehicle route data. A controller element can be configured to predetermine presence of an adjustment object based on route data and imaging data. The system is configured to set the beam mode of at least one vehicle lighting unit based on the predetermination. A method can comprise the steps of (a) obtaining vehicle route data, (b) obtaining vehicle surroundings image data, (c) predetermining the occurrence of an adjustment object based on the route data and imaging data and (d) setting the vehicle beam mode based on the predetermination.

Abstract: An adaptive filter system and a method for controlling the adaptive filter system are described herein. The system can includes one or more filters to attenuate incoming light. The one or more filters can be moved by one or more actuators. The method can capture image data from an imaging device through the one or more filters. Information can be determined from the captured image data. The one or more filters can be moved to a position for capturing image data based on the information.

Abstract: Provided herein is a system comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: generating a projection of a map having an origin; determining distortion factors of the map relative to distances from the origin; determining a distance from a vehicle to the origin; determining a reading from a sensor of the vehicle; and adjusting the reading to coordinates of the map based on a distortion factor corresponding to the distance.

Abstract: A method comprises obtaining autonomous vehicle sensor data of an autonomous vehicle. One or more autonomous vehicle actions of the autonomous vehicle are predicted based on the autonomous vehicle sensor data. Interactive content is identified from a library of interactive content. The interactive content is adjusted based on the predicted one or more autonomous vehicle actions, and the adjusted interactive content is presented within the autonomous vehicle.

Abstract: An environmental safety system may comprise a plurality of first sensors each located at a predetermined physical location and with a predetermined orientation. The system may receive first sensor data captured at a plurality of time points and by the plurality of first sensors. The system may also determine values of one or more parameters of an object within a threshold distance of the physical location at a last time point of the plurality of time points using the first sensor data. The values of the one or more parameters of the object may comprise a stationary status of the object at the last time point. The values of the one or more parameters of the object may be transmitted to a vehicle approaching the physical location. The vehicle may receive second sensor data captured by a plurality of second sensors in the vehicle. An optimized navigation of the vehicle approaching the physical location may be determined based on stationary status of the object at the last time point and the second sensor data.