Abstract: Systems and methods for predicting an optimal use level of a driver assist system are provided. The system may collect historical driver behavior and road condition data, and train an optimization prediction model using the historical data, e.g., via machine learning or artificial intelligence. Moreover, the system may collect real-time driver behavior and road condition data, and predict an optimal use level of the driver assist system based on the real-time data using the trained optimization prediction model. The system may then send feedback to the driver assist system when the optimal use level falls outside a predetermined threshold, such that the driver assist system may be unavailable or have reduced functionality until the optimal use level improves.

Abstract: Autonomous management of wireless connectivity of priority response vehicles is provided. It is received, from a communications network including a plurality of access points, the access points configured to provide communications services to priority vehicles and non-priority vehicles, locations of the priority vehicles over the communications network. A SON server is utilized, in communication with the plurality of access points, to optimize wireless connectivity for the priority vehicles. It is received, by an enhanced vehicle management system (EVMS) server, in communication with the SON server, network quality information from the SON server. The priority vehicles are routed based on the network quality information.

Abstract: A method includes identifying a broadcast set of access points from among the plurality of access points based on access point interference data associated with a plurality of access points disposed in an environment, where the access point interference data includes current radio frequency (RF) signal interference data associated with each of the plurality of access points, predicted RF signal interference data associated with each of the plurality of access points, or a combination thereof. The method includes partitioning a data packet into a plurality of data subpackets based on the broadcast set of access points and broadcasting the plurality of data subpackets to a vehicle via the broadcast set of access points.

Abstract: A system includes a server computer programmed upon determining that a first portion of software data for updating an operational feature of a first computer is stored in the first computer and a second portion of the software data is stored in a second computer, to encode the first portion and the second portion to generate encoded data, and to send the encoded data via wireless data transfer to the first and second computers. The first computer is programmed to decode the second portion from the received encoded data, to update the operational feature of the first computer based on the stored first portion and the decoded second portion, and to operate the first computer based on the updated operational feature.

Abstract: System and methods for a decentralized hybrid air-ground autonomous last-mile goods delivery are disclosed herein. A drone can include a controller configured to cause the drone to depart from a docking station of a vehicle, transmit a discovery message to available vehicles in an operating area, the discovery message having drone metadata, select at least one of one of the available vehicles based on response codes received from the available vehicle, or a nearest fixed docking station, and dock with a docking station of the one of the available vehicles or the nearest fixed docking station.

Abstract: A method for controlling one or more operational characteristics of a plurality of wireless access points of a manufacturing environment includes generating a plurality of state vectors based on network data associated with the plurality of wireless access points and identifying a set of actions from among a plurality of actions and associated with the plurality of state vectors. The method includes determining a reward for each action from among the set of actions, selecting a target action from among the set of actions based on the reward associated with each action from among the set of actions, and selectively adjusting the one or more operational characteristics of the plurality of wireless access points based on the target action.

Abstract: Lane-level matching is provided. For a time index of a time slot of a period of receiving consecutive position information, a lateral distance of the vehicle to each of a plurality of lanes of a roadway is calculated using data from sensors of a vehicle. For each lane of the plurality of lanes, a positional uncertainty of the vehicle in an orthogonal direction to a lane bearing of the lane is calculated, a lane confidence based on an average of confidence values of the lane over the period of receiving consecutive position information is calculated, and a lane probability based on the lane confidence is calculated. For the time index, it is identified which of the lanes has a highest probability as being the lane to which the vehicle is matched.

Abstract: Mesh device communication is provided. A dictionary of indexes corresponding to different messages is stored to a cache memory of an access device. A message is received via a transceiver of the access device. The cache memory is accessed to look up the message to identify an index corresponding to the message. The message is propagated, via the transceiver, to a wireless access device mesh network including a plurality of other access devices by broadcasting the index of the message.

Abstract: Routes may be presented to a vehicle operator with information about predicted autonomous driving levels. A road network route to a destination is received. The road network route is partitioned into segments. Indicia of the segments are provided to an inference engine. The inference engine predicts levels of autonomous driving for the respective segments generated by the inference engine based on the indicia of the segments. Based on the predicted levels of autonomous driving for the respective segments, a ratio of a level of autonomous driving for the road network route is computed. The ratio corresponds to a proportion of time and/or distance for the road network route during which a driver-system is predicted to be engaged at the level of autonomous driving. A user interface is displayed, which includes a graphic representation of the road network route and a graphic indication of the ratio.

Abstract: A method includes obtaining a radio frequency (RF) signal magnitude for a plurality of RF signals broadcasted in an environment and generating a digital RF heat map of the environment based on each RF signal magnitude. The method includes determining an RF coverage of the environment based on the digital RF heat map and selecting, for a wireless communication device, a communication channel from among a plurality of communication channels based on the RF coverage and one or more RF probability distribution functions.

Abstract: A computer is programmed to allocate respective connectivity quality data of a geographic area to a first map or a second map. The computer is further programmed to assign one of a plurality of subsets of the first map and one of a plurality of subsets of the second map to a first vehicle, identify respective locations of the first and second vehicles and one of the first or second maps that includes the locations of the first and second vehicles. The computer is further programmed to send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified map that includes the location of the first vehicle assigned to the first vehicle and (2) the subset of the identified map that includes the location of the second vehicle assigned to the second vehicle.

Abstract: A system includes a server computer programmed upon determining that a first portion of software data for updating an operational feature of a first computer is stored in the first computer and a second portion of the software data is stored in a second computer, to encode the first portion and the second portion to generate encoded data, and to send the encoded data via wireless data transfer to the first and second computers. The first computer is programmed to decode the second portion from the received encoded data, to update the operational feature of the first computer based on the stored first portion and the decoded second portion, and to operate the first computer based on the updated operational feature.

Abstract: A method includes identifying a broadcast set of access points from among the plurality of access points based on access point interference data associated with a plurality of access points disposed in an environment, where the access point interference data includes current radio frequency (RF) signal interference data associated with each of the plurality of access points, predicted RF signal interference data associated with each of the plurality of access points, or a combination thereof. The method includes partitioning a data packet into a plurality of data subpackets based on the broadcast set of access points and broadcasting the plurality of data subpackets to a vehicle via the broadcast set of access points.

Abstract: Systems and methods for predicting an optimal use level of a driver assist system are provided. The system may collect historical driver behavior and road condition data, and train an optimization prediction model using the historical data, e.g., via machine learning or artificial intelligence. Moreover, the system may collect real-time driver behavior and road condition data, and predict an optimal use level of the driver assist system based on the real-time data using the trained optimization prediction model. The system may then send feedback to the driver assist system when the optimal use level falls outside a predetermined threshold, such that the driver assist system may be unavailable or have reduced functionality until the optimal use level improves.

Abstract: A V2X event-message dictionary and a binning function are received from a cloud server. Sensor data is compared to events specified in the V2X event-message dictionary to identify a best-fit event for the sensor data. A number of bins and a bin number for the event are computed using the binning function. A V2X message is transmitted including the number of bins and the bin number, thereby avoiding including the sensor data in the V2X message.

Abstract: System and methods for a decentralized hybrid air-ground autonomous last-mile goods delivery are disclosed herein. A drone can include a controller configured to cause the drone to depart from a docking station of a vehicle, transmit a discovery message to available vehicles in an operating area, the discovery message having drone metadata, select at least one of one of the available vehicles based on response codes received from the available vehicle, or a nearest fixed docking station, and dock with a docking station of the one of the available vehicles or the nearest fixed docking station.

Abstract: A method includes obtaining a radio frequency (RF) signal magnitude for a plurality of RF signals broadcasted in an environment and generating a digital RF heat map of the environment based on each RF signal magnitude. The method includes determining an RF coverage of the environment based on the digital RF heat map and selecting, for a wireless communication device, a communication channel from among a plurality of communication channels based on the RF coverage and one or more RF probability distribution functions.

Abstract: A graph of devices is constructed, each network device serving an amount of bandwidth over the network, each vertex of the graph corresponding to a respective one of the network devices, each edge of the graph connecting network devices by interference weight, such that edges between connected network devices using different channels have an interference weight of zero, and edges between connected network devices using the same channel have an interference weight denoting an amount of interference between the connected network devices. A cell utilization of each of the network devices is determined according to an amount of traffic served by the respective network device compared to a total of the amounts of bandwidth for all network devices. A vehicle requesting bandwidth is assigned to the one of the network devices having a smallest product of cell utilization and maximum interference weight edge.

Abstract: A graph of devices is constructed, each network device serving an amount of bandwidth over the network, each vertex of the graph corresponding to a respective one of the network devices, each edge of the graph connecting network devices by interference weight, such that edges between connected network devices using different channels have an interference weight of zero, and edges between connected network devices using the same channel have an interference weight denoting an amount of interference between the connected network devices. A cell utilization of each of the network devices is determined according to an amount of traffic served by the respective network device compared to a total of the amounts of bandwidth for all network devices. A vehicle requesting bandwidth is assigned to the one of the network devices having a smallest product of cell utilization and maximum interference weight edge.

Abstract: A computer is programmed to divide respective data of a first high-resolution map of a first geographic area and a second high-resolution map of a second geographic area into a plurality of respective subsets, assign one of the subsets of each of the first high-resolution map and the second high-resolution map to a first vehicle and a second vehicle, identify respective locations of the first vehicle and the second vehicle and the one of the first high-resolution map or the second high-resolution map that includes the locations of the first and second vehicles, and send, to the first and second vehicles, a map dataset that is a result of applying an XOR function to (1) the subset of the identified high-resolution map including the location of the first vehicle and (2) the subset of the identified high-resolution map including the location of the second vehicle.