Abstract: Systems, methods, and computer-readable media are provided for wireless sensor networks (WSNs), including vehicle-based WSNs. A road side unit (RSU) includes one or more fixed sensors covering different sectors of a designated coverage area. The RSU uses the sensors to capture sensor data that is representative of objects in the coverage area, tracks objects (e.g., vehicles) in the coverage area, and determines regions in the coverage area that are not adequately covered by the sensors (e.g., “perception gaps”). When the RSU identifies an object that is in or at a perception gap, then the RSU sends a request to that object for sensor data captured by the object's on-board sensors. The RSU obtains the sensor data from the object, and uses the obtained sensor data to complement the knowledge that the RSU (i.e., “filling the peception gaps”). Other embodiments are disclosed and/or claimed.

Abstract: Various embodiments are generally directed to techniques for providing improved privacy protection against vehicle tracking for connected vehicles of a vehicular network. For example, at least one road side unit may: identify a set of vehicles that require pseudonym changes and send an invitation for a pseudonym change event to each of the vehicles, determine at least a total number of the acceptances, determine whether the total number meets or exceeds a predetermined threshold number, send acknowledgement messages to the accepting vehicles if the threshold number is met, and form a vehicle group to coordinate the pseudonym change event during a privacy period. During the privacy period, the RSU and the vehicles may communicate with each other in a confidential and private manner via key-session-based unicast transmission, and coordinate transmission power and vehicle trajectory adjustments to maximize the benefits for safety and obfuscation for privacy.

Abstract: Disclosed herein are systems, devices, and methods for improving the safety of a robot. The safety system may determine a safety envelope of a robot based on a planned movement of the robot and based on state information about a load carried by a robot. The state information may include a dynamic status of the load. The safety system may also determine a safety risk based on a detected object with respect to the safety envelope. The safety system may also generate a mitigating action to the planned movement if the safety risk exceeds a threshold value.

Abstract: Techniques are disclosed for the exploration of environments for the estimation and detection of hazards or near hazards within the environment and the mitigation of hazards therein. The exploration of the environment and mitigation of hazards therein may use one or more autonomous agents, including a hazard response robot. The estimation of the hazards may use a policy learning engine, and the hazards may be detected, and the associated risks therefrom, may be determined using a hazard estimation system.

Abstract: A computing device, including: a memory configured to store computer-readable instructions; and unintended human motion detection processing circuitry configured to execute the computer-readable instructions to cause the computing device to: interpret a human action; receive autonomous mobile robot (AMR) sensor data from an AMR sensor; and detect whether the human action is intended or unintended, wherein the detection is based on a predicted human action, a current human emotional or physical state, the interpreted human action, and the AMR sensor data.

Abstract: Disclosed herein are systems, devices, and methods of a robot safety system for improving the safety of human-robot collaborations. The robot safety system may include a processor that receives a collaboration policy for task collaboration between a robot and a collaborator. The task collaboration may include a movement plan of the robot to move a manipulator to a collaboration position. The robot safety system may also determine a new collaboration position based on the collaboration policy. The robot safety system may also update the collaboration position of the movement plan to the new collaboration position.

Abstract: Various embodiments are generally directed to techniques for providing improved privacy protection against vehicle tracking for connected vehicles of a vehicular network. For example, at least one road side unit may: identify a set of vehicles that require pseudonym changes and send an invitation for a pseudonym change event to each of the vehicles, determine at least a total number of the acceptances, determine whether the total number meets or exceeds a predetermined threshold number, send acknowledgement messages to the accepting vehicles if the threshold number is met, and form a vehicle group to coordinate the pseudonym change event during a privacy period. During the privacy period, the RSU and the vehicles may communicate with each other in a confidential and private manner via key-session-based unicast transmission, and coordinate transmission power and vehicle trajectory adjustments to maximize the benefits for safety and obfuscation for privacy.

Abstract: Techniques are disclosed to address issues related to the use of personalized training data to supplement machine learning trained models for Driver Monitoring System (DMS), and the accompanying mechanisms to maintain confidentiality of this personalized training data. The techniques disclosed herein also address issues related to maintaining transparency with respect to collected sensor data used in a DMS. Additionally, the techniques disclosed herein facilitate the generation of a digital representation of a driver for use as supplemental training data for the DMS machine learning trained models, which allow for DMS algorithms to be tailored to individual users.

Abstract: Disclosed herein are systems and methods for detecting and mitigating inappropriate behavior. The systems and methods may include receiving data. Using the data a harassment score and/or classification for a behavior may be determined. Using the harassment score and/or classification, a determination may be made as to when the harassment score and/or classification for the behavior exceeds a threshold. When the threshold is exceeded, a protection system and/or action engine may be activated to mitigate the inappropriate behavior.

Abstract: Systems, methods, and computer-readable media are provided for wireless sensor networks (WSNs), including vehicle-based WSNs. A road side unit (RSU) includes one or more fixed sensors covering different sectors of a designated coverage area. The RSU uses the sensors to capture sensor data that is representative of objects in the coverage area, tracks objects (e.g., vehicles) in the coverage area, and determines regions in the coverage area that are not adequately covered by the sensors (e.g., “perception gaps”). When the RSU identifies an object that is in or at a perception gap, then the RSU sends a request to that object for sensor data captured by the object's on-board sensors. The RSU obtains the sensor data from the object, and uses the obtained sensor data to complement the knowledge that the RSU (i.e., “filling the perception gaps”). Other embodiments are disclosed and/or claimed.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums which automatically generate standardized interfaces to sensor data consumers, provide sensor data search functionality, automatically determine data quality, and cache previously used sensor data to minimize the burden on application developers and minimize API call costs.

Abstract: A vehicle data relation device includes an internal audio/image data analyzer, configured to receive first data representing at least one of audio from within the vehicle or an image from within the vehicle; identify within the first data second data representing an audio indicator or an image indicator, wherein the audio indicator is human speech associated with a significance of an object external to the vehicle, and wherein the image indicator is an action of a human within the vehicle associated with a significance of an object external to the vehicle; an external image analyzer, configured to receive third data representing an image of a vicinity external to the vehicle; identify within the third data an object corresponding to at least one of the audio indicator or the video indicator; and an object data generator, configured to generate data corresponding to the object.

Abstract: Various systems and methods for a reconfigurable roadside network. Current traffic data of a road segment is received from sensors. A traffic scenario is identified based on current the traffic data. Key performance indicators are determined for the traffic scenario. The roadside network is modified based on the key performance indicators.

Abstract: Methods, systems, and apparatus, including computer programs encoded on non-transitory computer storage medium(s), are directed to improving completeness of map information and data related to maps created through sensor data. Map completeness can be improved by determining object completeness and coverage completeness of a generated map and reducing amount of unknown areas of the generated map.

Abstract: An embodiment of a semiconductor package apparatus may include technology to establish communication between a first stationary unit and one or more vehicles, combine sensor data from the first stationary unit and at least one source outside the first stationary unit, generate an environmental map based on the combined sensor data, divide the environmental map into two or more map segments, and broadcast the two or more map segments. Other embodiments are disclosed and claimed.

Abstract: Systems, methods, and computer-readable media are provided for wireless sensor networks (WSNs), including sensor deployment mechanisms for road surveillance. Disclosed embodiments are applied to design roadside infrastructure with optimal perception for a given geographic area. The deployment mechanisms account for the presence of static and dynamic obstacles, as well as symmetry aspects of the underlying environment. The deployment mechanisms minimize the number of required sensors to reduce costs and conserve compute and network resources, and extended infrastructure the sensing capabilities of sensor networks. Other embodiments are disclosed and/or claimed.

Abstract: Systems and methods for automated driving vehicle parking detection are described herein. The systems and methods are directed to detecting an available space, the available space comprising a space dimension larger than the automated driving vehicle, detecting a road marker associated with the available space, and determining that the available space is not a parking space based on the road marker and the space dimension. The systems and methods are also directed to guiding the automated driving vehicle to park in the available space in response to determining that the available space is not the parking space, and activating an occlusion prevention subsystem.

Abstract: Disclosure herein are systems and methods for deploying an autonomous vehicle during an idle time. As disclosed herein, a request for a mobility service may be received. The request may include constraints for usage of the autonomous vehicle. An optimal mobility service strategy may be determined based on the constraints. The optimal mobility service strategy may be selected from a plurality of mobility service strategies. A notification may be transmitted to a user device. The notification may include details of the optimal mobility service strategy.

Abstract: Disclosed embodiments prioritize gaps in V2X coverage and then selectively route traffic based on the prioritized gaps. Some embodiments combine historical vehicle presence along a route with predicted prospective vehicle traffic along the route to generate a map of regions that have a high confidence of a need for V2X coverage. This high confidence map is compared to a historical V2X coverage in those regions. From this comparison, a set of high priority V2X gaps is identified. Vehicles are then selectively routed either around or into the gaps.

Abstract: Various systems and methods for providing autonomous driving within a restricted area are discussed. In an examples, an autonomous vehicle control system can include an interface for receiving data from multiple sensors for detecting an environment about the vehicle, a security processor coupled to the configured to receive sensor information from the sensor interface, and autonomous driving system including one or more virtual machines configured to selectively receive information from the security processor based on a security request from infrastructure of the restricted area.