Abstract: For some embodiments of the present disclosure, systems and methods for using computer vision to guide processing of receive responses of RADAR sensors of a vehicle are described. A computer implemented method comprises receiving, with one or more receivers of RADAR sensors, environment receive RF responses, receiving region of interest (ROI) information including segments of a tentative set of ROIs with free space area boundaries from an image processor of an image processing chain for the computer vision, dynamically determining a number of polyphase filters based on a number of ROIs having dynamic scenes that are provided by the image processing chain, and adjusting parameters of the polyphase filters of a RADAR processing chain based on the ROI information.

Abstract: There is disclosed a method of operating an autonomous vehicle (AV), including: detecting an alert condition within the AV via data from an electronic sensor suite of the AV; based at least in part on detecting the alert condition, automatically initiating a call with another party; and communicatively coupling a passenger of the AV to the conference call, whereby the passenger can communicate with the other party via the conference call.

Abstract: There is disclosed a method of operating an autonomous vehicle (AV), including: detecting an alert condition within the AV via data from an electronic sensor suite of the AV; based at least in part on detecting the alert condition, automatically initiating a call with another party; and communicatively coupling a passenger of the AV to the conference call, whereby the passenger can communicate with the other party via the conference call.

Abstract: An equipment inspection system receives data captured by a sensor of an autonomous vehicle (AV). The captured data describes a current state of equipment for servicing the AV. The equipment inspection system compares the captured data to a model describing an expected state of the equipment. The equipment inspection system determines, based on the comparison, that the equipment differs from the expected state. The equipment inspection system may transmit data describing the current state of the equipment to an equipment manager. The equipment manager may schedule maintenance for the equipment based on the current state of the equipment.

Abstract: By way of example, there is disclosed a method of a device communicating messages in a vehicle, such as an autonomous vehicle (AV), including: participating in mutual authentication with a key server located on the vehicle; receiving from the key server a cryptographic key; using the cryptographic key for symmetric cryptography, comprising signing messages sent to or verifying messages received from another device of the vehicle; and clearing the cryptographic key at reboot.

Abstract: A computing system that analyzes the network effects of avoidance areas on autonomous vehicle routing is described herein. The computing system includes a data store that comprises a set of avoidance areas through which the autonomous vehicle is prohibited from being routed. A grouping system identifies groups of avoidance areas. A graph construction system constructs a graph representation of the avoidance area groups. A ranking algorithm is evaluated over the graph representation to generate a ranking of the avoidance area groups by relative impact on routing metrics for routes through an operational area of the autonomous vehicle. A mapping vehicle can be dispatched to resolve avoidance areas in avoidance area groups indicating in the ranking as having a greater impact on routing metrics than other avoidance area groups.

Abstract: The present technology can detect potential labeling conflicts made during different labeling tasks when those tasks are checked in to ensure that a map database is free from conflicts that might interrupt publishing of a map. The present technology can determine whether a first labeled version of map portion is based on a most recent version for the map portion that is stored in the map database, and when it is determined that it is not, and there is an intervening version, the present technology can identify differences between the intervening version of the map portion and the first version of the map portion and identify differences between the second version of the map portion and the first version of the map portion. Based on the identified differences, the present technology can determine whether any of those differences are conflicting.

Abstract: Systems and methods are disclosed for detecting crosswalk locations. Crosswalk locations can be detected by determining at least two painted lines on a road surface, and then combining the at least two painted lines on the road surface into a grouping of related elements. The grouping of related elements can be classified into a crosswalk (or in some embodiments a type of crosswalk) based on attributes of the grouping of related elements, where the attributes of the grouping of the elements includes a distance between the at least two painted lines, and an orientation of the grouping of related elements on the road surface.

Abstract: A method of providing an onboard assistant for a vehicle, comprising: receiving sensor data from sensors of the vehicle; transforming the sensor data using a trained machine learning model to provide transformed sensor data; inferring from the transformed sensor data that a special condition for the vehicle requires intervention; and contacting an operator of the vehicle to inform the operator of the special condition and receive instructions for handling the special condition.

Abstract: Systems and methods for map simulation testing are provided. A method includes receiving, by a computer-implemented system, information associated with an operational design domain (ODD); generating, by the computer-implemented system based at least in part on the information associated with the ODD, a plurality of map test cases for a map representative of a geographical area in the ODD, where each map test case of the plurality of map test cases includes one of a plurality of paths in the geographical area; evaluating a vehicle planning process in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases; and determining a metric for the map based on the evaluating.

Abstract: A method of providing an onboard assistant for a vehicle, comprising: receiving sensor data from sensors of the vehicle; transforming the sensor data using a trained machine learning model to provide transformed sensor data; inferring from the transformed sensor data that a special condition for the vehicle requires intervention; and contacting an operator of the vehicle to inform the operator of the special condition and receive instructions for handling the special condition.

Abstract: A computer-implemented method is provided for training a machine-learning (ML) algorithm that contributes to piloting an autonomous vehicle using a velocity grid generated from a simulation. The method may include simulating a scene. The scene includes a simulated autonomous vehicle and at least one simulated object moving in the scene. The method may also include predicting a velocity of at least one point on the simulated object as it moves in the simulated scene using a ML algorithm. The method may also include comparing the predicted velocity of the at least one point on the simulated object with velocities in the velocity grid generated from a simulation. The method may further include adjusting the ML algorithm to more accurately predict velocity of at least one point on the simulated object as it moves in the scene based on a difference in the predicted velocity compared to the velocity grid, which yields a trained ML algorithm.

Abstract: A computing system with a data store including storage priorities each associated with a different predefined event type. The storage priority indicating a likelihood detection of the predefined event type by an autonomous vehicle causes the autonomous vehicle to store sensor system output from a sensor system in the autonomous vehicle. The computing system can receive a data storage request indicating a request for the autonomous vehicle to store sensor system output for a specific predefined event type. The computing system can further update the storage priorities. Updating the storage priorities includes updates a storage priority associated with the specific predefined event type based on a parameter of specific predefined event type. The computing yet further can transmit the updated storage priorities to the autonomous vehicle which causes the autonomous vehicle to change the amount of sensory system output stored by the autonomous vehicle.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination and selecting one of a plurality of possible routes between the origin and the destination. For each of a plurality of route segments of the selected route, mapping information is used to characterize the route segment and one of a plurality of driving modes is selected for the route segment based on the characterization of the route segment and the at least one of the item characteristic and the item identity. A driving plan comprising a collection of the selected driving modes corresponding to the plurality of route segments comprising the selected route is provided to a vehicle and the vehicle delivers the item from the origin to the destination via the selected route using the driving plan.

Abstract: The subject disclosure relates to techniques for managing the configuration of vehicles. A process of the disclosed technology can include steps of receiving a first vehicle identifier for a first vehicle, wherein the first vehicle is associated with a first vehicle platform, identifying a first configuration for the first vehicle platform based on the first vehicle identifier, receiving a second vehicle identifier for a second vehicle, wherein the second vehicle is associated with a second vehicle platform, and wherein the first vehicle platform is different from the second vehicle platform, and identifying a second configuration for the second vehicle platform based on the second vehicle identifier, wherein the first vehicle and the second vehicle run on an identical software stack. Systems and machine-readable media are also provided.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination and selecting one of a plurality of possible routes between the origin and the destination. For each of a plurality of route segments of the selected route, mapping information is used to characterize the route segment and one of a plurality of driving modes is selected for the route segment based on the characterization of the route segment and the at least one of the item characteristic and the item identity. A driving plan comprising a collection of the selected driving modes corresponding to the plurality of route segments comprising the selected route is provided to a vehicle and the vehicle delivers the item from the origin to the destination via the selected route using the driving plan.

Abstract: Systems and methods are provided for child-friendly authentication for autonomous vehicle rides. In particular, systems and methods are provided for offering alternative authentication methods that automatically engage child-friendly features. The systems and methods provided enable unsupervised children to take advantage of autonomous rideshare and delivery programs using child-friendly authentication methods. Additionally, augmented autonomous vehicle safety and security practices for children are provided.

Abstract: A safety apparatus may include a tray table coupled to an interior surface of a vehicle via a release mechanism. The safety apparatus may also include a collision detection system communicatively coupled to the release mechanism. The collision detection system is configured to engage with the release mechanism if the tray table is in an open position, and to de-couple the tray table from the interior surface of the vehicle or to break away the tray table from a portion of a tray table structure if a collision is detected with respect to the vehicle.

Abstract: The present technology is directed to dynamically adjusting an autonomous vehicle (AV) system based on deep learning optimizations. An AV management system can generate a downscaling signal based on a result of comparing a complexity of an environment for an AV to navigate with a predetermined complexity threshold. Further, the AV management system can perform a downscaling of a neural network associated with an AV system based on the downscaling signal and determine a scenario to test the downscaled neural network in a simulation. The AV management system can adjust one or more parameters of the AV system based on simulated outputs and perform the simulation of the AV based on the adjusted one or more parameters of the AV system and the downscaled neural network to generate simulated performance data. Furthermore, the AV management system can compare the simulated performance data with a predetermined performance threshold.