Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.

Abstract: Techniques for three-dimensional (3D) reconstruction of a dynamic scene as a set of voxels are provided. One technique includes: receiving, by a processor, image data from each of two or more spatially-separated sensors observing the scene from a corresponding two or more vantage points; fusing, by the processor, the image data into the set of voxels on a frame-by-frame basis; segmenting, by the processor, the image data into objects that constitute the scene; detecting, by the processor, which of the objects remain static from frame to frame, remaining ones of the objects being dynamic; filtering, by the processor, the set of voxels to remove those of the voxels corresponding to the static objects, to produce a dynamic subset of the voxels; and outputting, by the processor to a display device, those of the voxels corresponding to the dynamic objects (such as the dynamic subset) and not to the static objects.

Abstract: An apparatus for autonomous vehicles includes a perception pipeline having independent classification processes operating in parallel to respectively identify objects belonging to a specific object type based on sensor data flows from multiple ones of a plurality of different types of sensors. The apparatus also includes a sensor monitoring stage to operate in parallel with the perception pipeline and to use the sensor data flows to estimate and track a confidence level of each of the plurality of different types of sensors, and nullify a deficient sensor when the confidence level associated with the deficient sensor fails to meet a confidence threshold.

Abstract: Techniques are disclosed to use existing vehicle speakers alone or in conjunction with other sensors (e.g. SRS sensors and/or microphones) that may already be implemented as part of the vehicle to identify acoustic signatures. Suitable low-cost and widely available hardware components (e.g., relays) may be used to modify the vehicle's existing speakers for a bi-directional mode of operation. Moreover, the vehicle's existing of audio amplifiers may be used to amplify signals collected by the speakers when operating in “reverse,” and process these collected signals to determine vehicle state information.

Abstract: In an automated vehicle (AV) system, interdependencies between components of the AV are determined, an operational domain state of one or more of the components can be determined based on the determined interdependencies, and an output signal representing the operational domain state of the one or more components can be generated. A user interface can present a notification based on the output signal to notify the driver and/or other occupants of the AV of the operational domain state of one or more of the components.

Abstract: Apparatus, method and computer readable medium associated with autonomous/semi-autonomous driving (AD/Semi-AD) are disclosed herein. In embodiments, an apparatus may comprise an accessibility engine disposed in an AD/semi-AD vehicle to control accessibility elements of the vehicle. The accessibility engine may be configured to receive sensor data from a plurality of sensors disposed in the vehicle, and determine a specific spot for the vehicle to stop at a destination for a passenger or driver to ingress or egress the vehicle, based at least in part on the sensor data and a model of the vehicle that includes information about accessibility elements of the vehicle, including determination of accessibility needs of the passenger or driver based at least in part on at least some of the sensor data. Other embodiments may be disclosed or claimed.

Abstract: In an autonomous vehicle system, data received from one or more autonomous vehicles (AVs) can be aggregated to generate aggregated data. From this aggregated data, a vector-field map can be generated that includes a plurality of cells. Each of the cells can include a corresponding vector. The vector field map can be analyzed to identify one or more vectors of the plurality of cells that exceed one or more predetermined threshold values. The analysis can include a magnitude analysis and/or a frequency analysis. Based on the analysis, traffic and/or road conditions can be determined, which can provide prior knowledge about the driving behavior of other vehicles. Advantageously, aspects of the disclosure improve predictive motion models and enhance navigation algorithms.

Abstract: Techniques are disclosed to realize a self-adaptive multiresolution digital plate (SAMDP) system that facilitates sharing of vehicle state information via a dynamically generated binary two-dimensional multispectral pattern. The binary 2D multispectral pattern adjusts its resolution to adapt to the visual perception process while communicating vehicle state information without relying on wireless communications (i.e. V2V, V2X, etc.). The techniques as described herein leverage the use of a multichannel spectral means that helps lower the error present in sensing and representation models used by automated driving systems.

Abstract: An Autonomous Vehicle (AV) system, including: a tracking subsystem configured to detect and track relative positioning of another vehicle that is behind or lateral to an AV configured to comply with a safety driving model, and to check a safety driving model compliance status of the other vehicle; and a risk reduction subsystem configured to plan, based on the safety driving model compliance status of the other vehicle, an AV action, wherein if the safety driving model compliance status of the other vehicle is unknown or is known to be non-compliant, the AV action is administration of a safety driving model compliance test to the other vehicle, or is a maneuver by the AV to reduce risk of collision with a leading vehicle positioned in front of the AV.

Abstract: Techniques for high-fidelity three-dimensional (3D) reconstruction of a dynamic scene as a set of voxels are provided. One technique includes: receiving, by a processor, image data from each of two or more spatially-separated sensors observing the scene from a corresponding two or more vantage points; generating, by the processor, the set of voxels from the image data on a frame-by-frame basis; reconstructing, by the processor, surfaces from the set of voxels to generate low-fidelity mesh data; identifying, by the processor, performers in the scene from the image data; obtaining, by the processor, high-fidelity mesh data corresponding to the identified performers; and merging, by the processor, the low-fidelity mesh data with the high-fidelity mesh data to generate high-fidelity 3D output. The identifying of the performers includes: segmenting, by the processor, the image data into objects; and classifying, by the processor, those of the objects representing the performers.

Abstract: Sensor data is accessed, which was generated sensors of a device in an environment. An observation of an event is determined, from the sensor data, that identifies movement of one or more machines within the environment in association with the event, where at least one of the machines is configured to move autonomously. Observation data is generated to describe the observation. The observation data is caused to be stored in a distributed linked data structure.

Abstract: An autonomous object modeler includes a modeling table, a controllable arm, a depth camera attached to the controllable arm, and a controller to control operation of the modeling table, the controllable arm, and the depth camera. The modeling table may be movable and includes a mass sensor to produce mass sensor data indicative of a mass of an object positioned on the modeling table. The controllable arm includes a force-torque sensor to produce force-torque sensor data indicative of an inertia of the object while the object is moved by the controllable arm. The controller is configured to control operation of the controllable arm to reposition the object on the modeling table to generate three-dimensional models of the object. The three-dimensional models include the mass data and the inertia data.

Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.

Abstract: Techniques are disclosed herein for collecting annotation data via a gamified user interface in a vehicle control system. According to an embodiment disclosed herein, the vehicle control system detects a trigger to initiate an annotation prompt associated with an object classified from an image. The vehicle control system presents, via a user interface, the annotation prompt. The vehicle control system receives, via the user interface, user input indicative of a response to the annotation prompt by a user and updates a confidence score associated with the classified object as a function of one or more metrics associated with the user.

Abstract: Technologies for intelligent traffic optimization include a directional flow server that receives dynamic traffic data from traffic infrastructure devices in a monitored region. The traffic data may include traffic volume data and traffic control status data. The server updates a dynamic layer of a high-definition map based on the dynamic traffic data. The high-definition map also includes a static layer and a directional flow layer. The server optimizes the directional flow in response to updating the dynamic layer. The directional flow layer is indicative of traffic direction associated with roads in the monitored region. The server may optimize each of several sub-regions and then optimize connection roads between the regions. The server may distribute the optimized directional flow layer to consumers such as traffic control devices, autonomous vehicles, and other subscribing devices. Other embodiments are described and claimed.

Abstract: Disclosures herein may be directed to a method, technique, or apparatus directed to a CA/AD that includes a system controller, disposed in a first CA/AD vehicle, to manage a collaborative three-dimensional (3-D) map of an environment around the first CA/AD vehicle, wherein the system controller is to receive, from another CA/AD vehicle proximate to the first CA/AD vehicle, an indication of at least a portion of another 3-D map of another environment around both the first CA/AD vehicle and the other CA/AD vehicle and incorporate the at least the portion of the 3-D map proximate to the first CA/AD vehicle and the other CA/AD vehicle into the 3-D map of the environment of the first CA/AD vehicle managed by the system controller.

Abstract: Techniques for three-dimensional (3D) reconstruction of a dynamic scene as a set of voxels are provided. One technique includes: receiving, by a processor, image data from each of two or more spatially-separated sensors observing the scene from a corresponding two or more vantage points; fusing, by the processor, the image data into the set of voxels on a frame-by-frame basis; segmenting, by the processor, the image data into objects that constitute the scene; detecting, by the processor, which of the objects remain static from frame to frame, remaining ones of the objects being dynamic; filtering, by the processor, the set of voxels to remove those of the voxels corresponding to the static objects, to produce a dynamic subset of the voxels; and outputting, by the processor to a display device, those of the voxels corresponding to the dynamic objects (such as the dynamic subset) and not to the static objects.

Abstract: Systems, apparatuses, and methods for trusted vehicle messaging may include receiving a communication from one or more of an internal vehicle component or an external communication system and composing a trusted message to be displayed in response to the received communication. Content may be managed to be displayed on one or more displays supported by a body of a vehicle.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve spatial-temporal data management. An example apparatus includes a hypervoxel data structure generator to generate a root hexatree data structure having sixteen hypernodes, an octree manager to improve a spatiotemporal data access efficiency by generating a first degree of symmetry in the root hexatree, the octree manager to assign a first portion of the hypernodes to a positive temporal subspace and to assign a second portion of the hypernodes to a negative temporal subspace, and a quadtree manager to improve the spatiotemporal data access efficiency by generating a second degree of symmetry in the root hexatree, the quadtree manager to assign respective hypernodes of the positive temporal subspace and the negative temporal subspace to respective positive and negative spatial subspaces.

Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.