Abstract: In one embodiment, a storage system includes one or more platforms to stow compute units of an autonomous or semi-autonomous vehicle in a storage compartment of the vehicle. The platform is configured to support a compute unit of the vehicle to avoid a crumple zone of the vehicle. The crumple zone of the vehicle is designed to crumple when colliding with an object. The storage system also includes one or more shear fasteners configured to fasten the compute unit to the platform. The one or more shear fasteners are configured to break in a predetermined direction in response to a predetermined amount of lateral force. The breakage of the one or more shear fasteners decouples the compute unit from the platform in a controlled direction.

Abstract: In one embodiment, a method includes receiving a request for evaluating driving data included in a data log, accessing, based on the request, an evaluation configuration file that includes a metric-calculation configuration specifying one or more metric calculators configured to generate one or more output metrics from the driving data and a validation configuration configured to validate the one or more output metrics, instantiating the one or more metric calculators specified by the metric-calculation configuration included in the evaluation configuration file, determining particular driving data from the driving data included in the data log based on the one or more instantiated metric calculators, and generating the one or more output metrics for the particular driving data by using the instantiated one or more metric calculators.

Abstract: Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to determine one or more images of a generated overhead view of a geographical area. The generated overhead view is generated from aggregated pixel values determined from correlated pixel values in images of the geographical area. The disclosed approaches identify semantic map features as being present in the images of the overhead perspective of the geographic area. The disclosed approaches extract the semantic map features of the geographical area from the images of the substantially overhead perspective of the geographical area. The disclosed approaches translate the extracted semantic map features to a semantic map layer of a geometric map associated with the geographical area.

Abstract: In one embodiment, a method includes, by a computing device of a first sensor receiving synchronization information from a controller. The synchronization information being generated based on a clock of the controller. The method also includes determining, based on the synchronization information, a first offset between a first clock of the first sensor and the clock of the controller; storing the first offset; and synchronizing, based on the stored first offset and the first clock of the first sensor, a first data capture by the first sensor with a second data capture by a second sensor. The first data capture and the second data capture being requested by the controller.

Abstract: Systems, methods, and non-transitory computer-readable media can determine first sensor data captured by a first sensor of a vehicle. Second sensor data captured by a second sensor of the vehicle can be determined. Information describing the first sensor data and the second sensor data can be provided to a machine learning model trained to predict whether a pair of sensors are calibrated or mis-calibrated based on sensor data captured by the pair of sensors. A determination is made whether the first sensor and the second sensor are calibrated or mis-calibrated based on an output from the machine learning model.

Abstract: The present invention relates to a method of generating an overhead view image of an area. More particularly, the present invention relates to a method of generating a contextual multi-image based overhead view image of an area using ground map data and field of view image data. Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to receive a plurality of images of the geographical area, determine a ground map of the geographical area, divide the ground map into a plurality of sampling points of the geographical area; and determine a color for each of the plurality of sampling points, wherein the color of each of the sampling points is determined by determining a correlation between the sampling points of the geographical area and color of the sampling points captured in at least one of the plurality of images.

Abstract: In one embodiment, an apparatus includes a first stage and a second stage. The first stage may include a micro light-directing unit that is operable to receive a light beam from a light source and direct the light beam along one dimension to discrete input locations of a second stage. The second stage may be operable to receive the light beam from the first stage at the discrete input locations along the one dimension and direct the light beam through two dimensions to discrete output locations of the second stage to scan a three-dimensional space.

Abstract: In one embodiment, a computing system receives sensor data from one or more sensors of a vehicle. The computing system determines a metric associated with the vehicle based on the received sensor data. The computing system determines, based on the metric, a length of a transmission cycle of a communication network of the vehicle. The transmission cycle comprises one or more scheduled time periods dedicated for transmitting data from respective first nodes in the communication network. The computing system configures the communication network of the vehicle based at least in part on the length of the transmission cycle to adjust respective occurrence frequencies of the scheduled time periods over multiple instances of the transmission cycle.

Abstract: Systems, methods, and non-transitory computer-readable media can receive sensor data providing information about an environment surrounding a vehicle to a first computing system and a second computing system associated with the vehicle, wherein the first computing system and the second computing system are each capable of generating navigation instructions for the vehicle based on the received sensor data. A first planned trajectory is determined based on the sensor data by the first computing system. The vehicle is navigated by the first computing system based on the first planned trajectory. Control of the vehicle is transitioned from the first computing system to the second computing system based on a failure associated with the first computing system. An emulated trajectory is determined based on data describing a current motion of the vehicle by the second computing system. The vehicle is navigated by the second computing system based on the emulated trajectory.

Abstract: Systems, methods, and non-transitory computer-readable media can determine mission data associated with a scenario encountered during operation of a vehicle. A first evaluation of the scenario can be determined by evaluating the mission data using a simulation behavior model based on simulated driving data. A second evaluation of the scenario can be determined by evaluating the mission data using an observed behavior model based on observed driving data. Vehicle performance of an autonomy system of the vehicle can be evaluated based on the first evaluation and the second evaluation.

Abstract: In one embodiment, a method includes determining an initial cost volume associated with a plurality of potential trajectories of a vehicle in an environment based on a set of movement restrictions of the vehicle, generating a delta cost volume using the initial cost volume and environment data associated with the environment, wherein the delta cost volume is generated by determining adjustments to the initial cost volume that incorporate observed driving behavior, and scoring a trajectory of the plurality of potential trajectories for the vehicle based on t the initial cost volume and the delta cost volume.

Abstract: Systems and methods are provided for vehicle processing component cooling. A vehicle may include a compartment, a computing system including one or more processing components located within the compartment, and a cooling system configured to cool the one or more processing components. The cooling system may include a heat exchanger defining a plurality of flow channels. Each flow channel may be defined by an outlet and may be configured to provide cooling fluid. Operation of the processing components may heat the surrounding cabin air within the compartment through an air cooling operation. The cabin air from within the compartment may be directed through the heat exchanger to cool the cooling fluid. The compartment may be a trunk of the vehicle, and the heat exchanger may be located within the trunk and near the processing components.

Abstract: In one embodiment, a computing system of a vehicle may receive vehicle driving data associated with a vehicle driving in an environment and detected environment data associated with the environment. The system may generate a reference trajectory of the vehicle driving in the environment based on the vehicle driving data. The system may determine driving constraints associated with the environment based on the detected environmental data. The system may generate a trajectory of the vehicle based on the driving constraints. The system may determine a difference in at least one parameter associated with the trajectory relative to at least one corresponding parameter associated with the reference trajectory. The system may adjust weight values associated with cost functions of the trajectory based on the difference between the at least one parameter associated with the trajectory and the corresponding parameter associated with the reference trajectory.

Abstract: A method includes receiving, by a computing system of a vehicle, a planned trajectory for the vehicle based on first sensor data associated with an external environment. The planned trajectory is generated by a primary computing system associated with a first sensor. The method further includes determining an environmental condition associated with the external environment. The environmental condition is included in second sensor data generated by a second sensor. The method further includes analyzing one or more parameters associated with the planned trajectory to determine whether the planned trajectory is based on the environmental condition, and, in response to determining that the primary computing system fails to base the planned trajectory upon the environmental condition, altering the one or more parameters associated with the planned trajectory to generate an altered planned trajectory. The method thus includes instructing the vehicle to execute the altered planned trajectory.

Abstract: Examples disclosed herein may involve a computing system that is operable to (i) present, via a visual interface, a virtual shape associated with a three-dimensional (3D) coordinate system, (ii) present, via the visual interface, a visual indicator positioned in proximity to the virtual shape and indicating that a specified spatial parameter of the virtual shape will be modified along a specified dimension of the 3D coordinate system in response to a given type of user input associated with the visual indicator, (iii) while presenting the visual indicator, detect an instance of the given type of user input associated with the visual indicator, and (iv) after detecting the instance of the given type of user input, update the virtual shape that is presented via the visual interface by modifying the specified spatial parameter of the virtual shape along the specified dimension.

Abstract: In one embodiment, a system includes an inertial measurement unit, a lidar sensor, and one or more processors configured to perform operations. The operations include receiving data from the lidar sensor. The operations include determining movement data based on the data received from the lidar sensor. The operations include receiving data from the inertial measurement unit. The operations include determining, based on the movement data and the data received from the inertial measurement unit, one or more calibration factors for the inertial measurement unit. The operations include applying the one or more calibration factors to a measurement received from the inertial measurement unit.

Abstract: In one embodiment, a computing system of a vehicle may receive perception data associated with a scenario encountered by a vehicle while operating in an autonomous driving mode. The system may identify the scenario based at least on the perception data. The system may generate a performance metric associated with a vehicle navigation plan to navigate the vehicle in accordance with the identified scenario. In response to a determination that the performance metric associated with the vehicle navigation plan fails to satisfy one or more criteria for navigating the vehicle in accordance with the identified scenario, the system may trigger a disengagement operation related to disengaging the vehicle from the autonomous driving mode. The system may generate a disengagement record associated with the triggered disengagement operation. The disengagement record may include information associated with the identified scenario encountered by the vehicle related to the disengagement operation.

Abstract: In one embodiment, a method includes providing instructions to broadcast a modulated radar chirp signal from a radar antenna of a vehicle. The modulated radar chirp signal includes data associated with the vehicle. The method includes receiving a first return signal whose waveform substantially matches the modulated chirp signal. The first return signal is the modulated radar chirp signal after reflecting off of an object in an environment surrounding the vehicle. The method includes calculating a location for the object using the first return signal, receiving, from a base station antenna, a second return signal that indicates the modulated chirp signal was received by the base station antenna, and providing instructions to establish a wireless communication session with the base station antenna.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a geometric map and a semantic map associated with a geographic area, the semantic map comprising semantic data associated with vehicle navigation. A first semantic position estimate associated with a first piece of semantic data contained in the semantic map is generated based on semantic data location information associated with the first piece of semantic data. A final position for the first semantic position estimate is received. One or more three-dimensional semantic labels are applied to the geometric map based on the final position of the first semantic position estimate. A warped semantic map is generated. Generating the warped semantic map comprises warping the semantic map based on the one or more three-dimensional semantic labels.

Abstract: In general, one or more loads on a vehicle can be connected to both a first voltage source on the vehicle and a backup vehicle power system on the vehicle. If the voltage provided by the first voltage source to the one or more loads satisfies a voltage threshold, the backup vehicle power system does not provide power to the one or more loads. However, if the voltage provided by the first voltage source to the one or more loads falls below the voltage threshold, the backup vehicle power system provides power to the one or more loads.