Abstract: In various examples, scenarios may be defined using a declarative description—e.g., defining a behavior of interest—that the present system may convert into a procedural description for generating one or more instances and/or variations of a scenario for testing an autonomous or semi-autonomous machine in a virtual environment. The system may execute observers or evaluators for testing the performance and accuracy of the machine and may compute coverage of various elements based on the generated virtual scenarios, and may feed the results back to the system to generate additional instances and/or variations where the coverage or accuracy is below a desired level. As a result, the system may include an end-to-end framework for generating scenarios in virtual environments, testing and validating the scenarios themselves, and/or testing and validating the underlying autonomous or semi-autonomous systems of the machine—all based on a declarative description.

Abstract: A semi-public blockchain maintained on one or more nodes in a map cloud platform comprises data for maintaining a global map of a predetermined geographic area. The blockchain also comprises a plurality of data records, where each data record is associated with an update to a global map. When a message associated with a map update to the global map is received, the nodes of the blockchain determine a consensus by evaluating the map update, where the evaluating comprises performing a plurality of proofs including a proof of location, a proof of iterations, a proof of physical delivery and a proof of safety. When consensus is attained and the map update is validated, a data record associated with the map update is generated and added to the blockchain with a timestamp and a link to prior data records in the blockchain.

Abstract: A semi-public blockchain maintained on one or more nodes in a map cloud platform comprises data for maintaining a global map of a predetermined geographic area. The blockchain also comprises a plurality of data records, where each data record is associated with an update to a global map. When a message associated with a map update to the global map is received, the nodes of the blockchain determine a consensus by evaluating the map update, where the evaluating comprises performing a plurality of proofs including a proof of location, a proof of iterations, a proof of physical delivery and a proof of safety. When consensus is attained and the map update is validated, a data record associated with the map update is generated and added to the blockchain with a timestamp and a link to prior data records in the blockchain.

Abstract: A disaster response system includes a communication infrastructure including a plurality of sensor assemblies configured to generate data indicative of at least one of environmental conditions, motion, position, chemical detection, and medical information; and wirelessly provide the generated data to the communication infrastructure. The system also includes an incident command infrastructure configured to exchange data with the communication infrastructure; and detect an incident based on the data from the sensor assemblies. The system also includes an unmanned aerial vehicle (UAV) configured to deliver a payload in response to the detected incident.

Abstract: In various examples, searching of data—including real-world data, simulation data, system under test (SUT) data, and/or map data—may be executed using a query engine configured to compile detailed binary code from high-level declarative queries for searching the data to identify scenarios or engineering artifacts of interest. A user may identify a behavior or scenario of interest, define the behavior or scenario in a descriptive and/or declarative manner—including implicit indications of temporal or spatial relationships—and the query engine may then compile an explicit procedural description that may be used to search the data for one or more instances and/or variations of the defined scenario or computational representation of an engineering artifact under investigation. Once the scenarios are identified, behaviors of the machine may be observed, criteria with respect to the machine performance may be evaluated, and/or test coverage with respect to the scenario type may be collected.

Abstract: An embodiment of a disaster response system is disclosed that includes a communication and monitoring environment (CME). The CME includes an incident command infrastructure, and a communication infrastructure configured to exchange data with the incident command infrastructure. The communication infrastructure includes a network comprising a plurality of sensor assemblies that are configured to wirelessly communicate with the communication infrastructure. The sensor assemblies are configured to acquire data that includes at least one of environmental conditions, motion, position, chemical detection, and medical information. One or more of the sensors are configured to aggregate data from a subset of the plurality of sensors. The CME is configured to detect an incident based on at least the data acquired by the sensor assemblies.

Abstract: In various examples, scenarios may be defined using a declarative description—e.g., defining a behavior of interest—that the present system may convert into a procedural description for generating one or more instances and/or variations of a scenario for testing an autonomous or semi-autonomous machine in a virtual environment. The system may execute observers or evaluators for testing the performance and accuracy of the machine and may compute coverage of various elements based on the generated virtual scenarios, and may feed the results back to the system to generate additional instances and/or variations where the coverage or accuracy is below a desired level. As a result, the system may include an end-to-end framework for generating scenarios in virtual environments, testing and validating the scenarios themselves, and/or testing and validating the underlying autonomous or semi-autonomous systems of the machine—all based on a declarative description.

Abstract: A semi-public blockchain maintained on one or more nodes in a map cloud platform comprises data for maintaining a global map of a predetermined geographic area. The blockchain also comprises a plurality of data records, where each data record is associated with an update to a global map. When a message associated with a map update to the global map is received, the nodes of the blockchain determine a consensus by evaluating the map update, where the evaluating comprises performing a plurality of proofs including a proof of location, a proof of iterations, a proof of physical delivery and a proof of safety. When consensus is attained and the map update is validated, a data record associated with the map update is generated and added to the blockchain with a timestamp and a link to prior data records in the blockchain.

Abstract: In some embodiments, the disclosed subject matter involves a system and method for dynamic object identification and environmental changes for use with autonomous vehicles. For efficient detection of changes for autonomous, or partially autonomous vehicles, embodiments may use a technique based on background removal and image subtraction which use motion detection rather than full object identification for all objects in an image. Road side units proximate to a road segment or virtual road side units in the cloud, other vehicles or mobile device (e.g., drones) are used to retrieve and store background images for a road segment, to be used by the autonomous vehicle. Other embodiments are described and claimed.

Abstract: A semi-public blockchain maintained on one or more nodes in a map cloud platform comprises data for maintaining a global map of a predetermined geographic area. The blockchain also comprises a plurality of data records, where each data record is associated with an update to a global map. When a message associated with a map update to the global map is received, the nodes of the blockchain determine a consensus by evaluating the map update, where the evaluating comprises performing a plurality of proofs including a proof of location, a proof of iterations, a proof of physical delivery and a proof of safety. When consensus is attained and the map update is validated, a data record associated with the map update is generated and added to the blockchain with a timestamp and a link to prior data records in the blockchain.

Abstract: An embodiment of a disaster response system is disclosed that includes a communication and monitoring environment (CME). The CME includes an incident command infrastructure, and a communication infrastructure configured to exchange data with the incident command infrastructure. The communication infrastructure includes a network comprising a plurality of sensor assemblies that are configured to wirelessly communicate with the communication infrastructure. The sensor assemblies are configured to acquire data that includes at least one of environmental conditions, motion, position, chemical detection, and medical information. One or more of the sensors are configured to aggregate data from a subset of the plurality of sensors. The CME is configured to detect an incident based on at least the data acquired by the sensor assemblies.

Abstract: A device generates a block for a model associated with a system, and the system is associated with middleware. The block subscribes to information generated by the middleware based on communication between the middleware and the system. The device receives subscriber configuration information for configuring the block, and creates, based on the subscriber configuration information, a signal that converts the information generated by the middleware into a format compatible with the model.

Abstract: A device may determine temporal ages of a first signal and a second signal provided in a graphical model generated in a technical computing environment, where the first signal is different than the second signal. The device may determine whether the temporal age of the first signal is equivalent to the temporal age of the second signal at a particular block of the graphical model. The device may either display an indication that the first signal is synchronized with the second signal when the temporal age of the first signal is equivalent to the temporal age of the second signal, or may display another indication that the first signal is not synchronized with the second signal when the temporal age of the first signal is not equivalent to the temporal age of the second signal.

Abstract: A semi-public blockchain maintained on one or more nodes in a map cloud platform comprises data for maintaining a global map of a predetermined geographic area. The blockchain also comprises a plurality of data records, where each data record is associated with an update to a global map. When a message associated with a map update to the global map is received, the nodes of the blockchain determine a consensus by evaluating the map update, where the evaluating comprises performing a plurality of proofs including a proof of location, a proof of iterations, a proof of physical delivery and a proof of safety. When consensus is attained and the map update is validated, a data record associated with the map update is generated and added to the blockchain with a timestamp and a link to prior data records in the blockchain.

Abstract: Technologies for customized crowd-sourced update and validation include a computing device having a technical computing environment (TCE)-based engine that receives user information from one or more user devices, executes a TCE model with the user information to generate behavior data of the TCE model, and generates a software update for the TCE model based on the behavior data. The TCE model may be a model for an autonomous system such as a self-driving vehicle, and the software update may be a safety update for the autonomous vehicle. The user information may include sensor data, such as distance detection sensor data. The computing device may transmit an incentive such as a software update, feature update, or safety software update to the user devices. The computing device may also receive information associated with the TCE model from one or more developer devices. Other embodiments are described and claimed.

Abstract: In some embodiments, the disclosed subject matter involves a system and method for dynamic object identification and environmental changes for use with autonomous vehicles. For efficient detection of changes for autonomous, or partially autonomous vehicles, embodiments may use a technique based on background removal and image subtraction which use motion detection rather than full object identification for all objects in an image. Road side units proximate to a road segment or virtual road side units in the cloud, other vehicles or mobile device (e.g., drones) are used to retrieve and store background images for a road segment, to be used by the autonomous vehicle. Other embodiments are described and claimed.

Abstract: A method may include establishing a connection with a physical device, by a device. The method may include receiving information identifying the physical device, by the device. The method may include determining physical device information based on receiving the information identifying the physical device, by the device. The physical device information may be a description of the physical device. The method may include generating a set of model elements based on the physical device information, by the device. The set of model elements may include program code associated with simulating a behavior associated with the physical device. The method may include associating the set of model elements with a device model corresponding to the physical device, by the device.

Abstract: In some embodiments, the disclosed subject matter involves a system and method for dynamic object identification and environmental changes for use with autonomous vehicles. For efficient detection of changes for autonomous, or partially autonomous vehicles, embodiments may use a technique based on background removal and image subtraction which use motion detection rather than full object identification for all objects in an image. Road side units proximate to a road segment or virtual road side units in the cloud, other vehicles or mobile device (e.g., drones) are used to retrieve and store background images for a road segment, to be used by the autonomous vehicle. Other embodiments are described and claimed.

Abstract: A data processing system (DPS) provides protection for firmware. The DPS comprises (a) a host module comprising a management engine and (b) a security module in communication with the host module. The security module comprises a security coprocessor and a secret identifier for the security module. The DPS also comprises at least one machine-accessible medium comprising host firmware and security firmware. The host firmware, when executed by the management engine, enables to management engine to determine whether the security module is in communication with the host module, based on the secret identifier for the security module. The security firmware, when executed by the security coprocessor, enables the security coprocessor (a) to verify integrity of the host firmware and (b) to prevent the host module from booting with the host firmware in response to a determination that the host firmware has lost integrity. Other embodiments are described and claimed.

Abstract: A device generates a block for a model associated with a system, and the system is associated with middleware. The block subscribes to information generated by the middleware based on communication between the middleware and the system. The device receives subscriber configuration information for configuring the block, and creates, based on the subscriber configuration information, a signal that converts the information generated by the middleware into a format compatible with the model.