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 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: A method for asset identification string error detection can include receiving an asset identification string corresponding to an asset and aggregating data associated with the asset from multiple sources. The method can include creating one or more probabilistic tables linking the aggregated data to the asset and determining a likelihood that at least a portion of the asset identification string is correct based on the probabilistic tables. The method can indicate that the asset identification string includes an error when the likelihood is less than a selected threshold and otherwise indicate that the asset identification string is correct when the likelihood is greater than or equal to the selected threshold.

Abstract: This disclosure describes systems and using dual vehicle digital twins for model-based learning and remotely-operated vehicles. An example method may include receiving, by a processor associated with a first digital twin stored locally on a computing system of a vehicle or a second digital twin stored remotely on a first remote system, data relating to a first sub-system of the vehicle and a second sub-system of the vehicle. The example method may also include sending the data to the first digital twin or the second digital twin, wherein sending the data includes synchronizing with the first digital twin or the second digital twin.

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: While operating a vehicle, a candidate marker is detected via first image data from a first image sensor. Upon failing to identify the candidate marker, vehicle exterior lighting is actuated to illuminate the candidate marker. Then the candidate marker is determined to be one of a real marker or a projected marker based on determining whether the candidate marker is detected via second image data from the first image sensor. Upon determining the candidate marker is the real marker, the vehicle is operated based on the real marker.

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: Methods and systems are provided for a start/stop feature. In one example, a method includes adjusting start/stop conditions in response to a vehicle operator customizing start/stop conditions. The vehicle operator customizes start/stop conditions for a plurality of different driving conditions.

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: While operating a vehicle, a candidate marker is detected via first image data from a first image sensor. Upon failing to identify the candidate marker, vehicle exterior lighting is actuated to illuminate the candidate marker. Then the candidate marker is determined to be one of a real marker or a projected marker based on determining whether the candidate marker is detected via second image data from the first image sensor. Upon determining the candidate marker is the real marker, the vehicle is operated based on the real marker.

Abstract: This disclosure is generally directed to systems and methods related to providing advice to a driver of a vehicle involved in a traffic accident. In an example embodiment, a sensor generates a sensor signal based on detecting a traffic accident involving the vehicle in which the sensor is mounted. A computer evaluates the sensor signal and identifies various actions to be performed in conformance with legal and/or insurance requirements applicable to the site of the traffic accident. The legal and/or insurance requirements can vary from one site to another (state to state, for example). The computer may carry out some of the actions automatically and may provide an advisory to the driver of the vehicle to carry out some other actions, such as to exit or stay in the vehicle and to move or not to move the vehicle.

Abstract: A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to monitor a position of a vehicle while an adaptive cruise control feature of the vehicle is set to operate in a standard operation mode, identify, based on the position of the vehicle and on visibility zone information, a limited visibility zone in a route of travel of the vehicle, and cause the adaptive cruise control feature to operate in a modified operation mode while the vehicle is in the limited visibility zone, wherein during operation in the modified operation mode, the adaptive cruise control feature operates in accordance with one or more modified operating parameters.

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: Methods and systems are provided for a start/stop feature. In one example, a method includes adjusting start/stop conditions in response to a vehicle operator customizing start/stop conditions. The vehicle operator customizes start/stop conditions for a plurality of different driving conditions.

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 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.