Abstract: A host map system for updating a region of a host map based on sensor data received from a plurality of connected vehicles travelling in the region comprises monitoring a host map region for discrepancies, defining a geo-fence around an area of a discrepancy and setting a schedule for activing the geo-fence. When a connected vehicle enters the geo-fence, the host mapping system transmits the geo-fence to the connected vehicle and requests that it share its sensor data while travelling in the geo-fenced area. The host mapping system receives the sensor data and processes the data to update details of the host map. The host mapping system may transmit the updated map to connected vehicles travelling in the map region.

Abstract: System, methods, and embodiments described herein relate to predicting a future state of an object detected in a vicinity of a vehicle. In one embodiment, a method for predicting a state of an object includes detecting, at a plurality of discrete times [t, t?1, t?2, . . . ], a respective plurality of states of the object, obtaining, based at least in part on a present location of the vehicle, supplemental information, associated with an environment of the present location, that indicates at least a speed reduction factor, executing a prediction operation to determine a predicted state of the object at a time t+1 based at least in part on the detected plurality of states and the supplemental information, determining an actual state of the object at a time t+1 based on data from the one or more sensors, and modifying the prediction operation based at least in part on the actual state.

Abstract: A vehicle behavior monitor installed in a host vehicle that monitors the behavior of other vehicles. When the behavior of the other vehicles appears to deviate from an expected trajectory of an in-vehicle map, a geo-fenced region is monitored by external sensors. The external sensor data stream is input to a pre-trained anomaly detector. The clusters from the feature space of the encoder are compared to a database of known behaviors. A confidence level is determined based on the number of vehicles which exhibit the behavior. If the confidence level is equal to or greater than a confidence level threshold, a persistence value is calculate based on the type of behavior. The behavior and the persistence value are used to update the in-vehicle map. Based on the persistence value, the update is transmitted to a map server when the host vehicle enters an area of high data connectivity or is dropped.

Abstract: Methods and a system are described for prioritizing the upload of connected vehicle map data in a central mapping system. A central mapping unit includes a central server which receives and processes data uploads by priority order, from highest priority to lowest priority. The uploaded data is compared to central map data to determine whether the central map requires updating. When the central mapping unit determines that there is not enough information to update the central map in a region, a priority list is updated to give high priority to data collection in the region. The updated priority list is pushed to connected vehicles travelling in the region, which have external sensors for data collection in the surrounding environment. When a connected vehicle enters the region, its external sensors collect data regarding the region, which is uploaded to the central mapping unit with highest priority.

Abstract: A host map system for updating a region of a host map based on sensor data received from a plurality of connected vehicles travelling in the region comprises monitoring a host map region for discrepancies, defining a geo-fence around an area of a discrepancy and setting a schedule for activing the geo-fence. When a connected vehicle enters the geo-fence, the host mapping system transmits the geo-fence to the connected vehicle and requests that it share its sensor data while travelling in the geo-fenced area. The host mapping system receives the sensor data and processes the data to update details of the host map. The host mapping system may transmit the updated map to connected vehicles travelling in the map region.

Abstract: A host map system for updating a region of a host map based on sensor data received from a plurality of connected vehicles travelling in the region comprises monitoring a host map region for discrepancies, defining a geo-fence around an area of a discrepancy and setting a schedule for activing the geo-fence. When a connected vehicle enters the geo-fence, the host mapping system transmits the geo-fence to the connected vehicle and requests that it share its sensor data while travelling in the geo-fenced area. The host mapping system receives the sensor data and processes the data to update details of the host map. The host mapping system may transmit the updated map to connected vehicles travelling in the map region.

Abstract: System, methods, and embodiments described herein relate to predicting a future state of an object detected in a vicinity of a vehicle. In one embodiment, a method for predicting a state of an object includes detecting, at a plurality of discrete times [t, t?1, t?2, . . . ], a respective plurality of states of the object, obtaining, based at least in part on a present location of the vehicle, supplemental information, associated with an environment of the present location, that indicates at least a speed reduction factor, executing a prediction operation to determine a predicted state of the object at a time t+1 based at least in part on the detected plurality of states and the supplemental information, determining an actual state of the object at a time t+1 based on data from the one or more sensors, and modifying the prediction operation based at least in part on the actual state.

Abstract: Methods and a system are described for prioritizing the upload of connected vehicle map data in a central mapping system. A central mapping unit includes a central server which receives and processes data uploads by priority order, from highest priority to lowest priority. The uploaded data is compared to central map data to determine whether the central map requires updating. When the central mapping unit determines that there is not enough information to update the central map in a region, a priority list is updated to give high priority to data collection in the region. The updated priority list is pushed to connected vehicles travelling in the region, which have external sensors for data collection in the surrounding environment. When a connected vehicle enters the region, its external sensors collect data regarding the region, which is uploaded to the central mapping unit with highest priority.

Abstract: A host map system for updating a region of a host map based on sensor data received from a plurality of connected vehicles travelling in the region comprises monitoring a host map region for discrepancies, defining a geo-fence around an area of a discrepancy and setting a schedule for activing the geo-fence. When a connected vehicle enters the geo-fence, the host mapping system transmits the geo-fence to the connected vehicle and requests that it share its sensor data while travelling in the geo-fenced area. The host mapping system receives the sensor data and processes the data to update details of the host map. The host mapping system may transmit the updated map to connected vehicles travelling in the map region.

Abstract: A vehicle behavior monitor installed in a host vehicle that monitors the behavior of other vehicles. When the behavior of the other vehicles appears to deviate from an expected trajectory of an in-vehicle map, a geo-fenced region is monitored by external sensors. The external sensor data stream is input to a pre-trained anomaly detector. The clusters from the feature space of the encoder are compared to a database of known behaviors. A confidence level is determined based on the number of vehicles which exhibit the behavior. If the confidence level is equal to or greater than a confidence level threshold, a persistence value is calculate based on the type of behavior. The behavior and the persistence value are used to update the in-vehicle map. Based on the persistence value, the update is transmitted to a map server when the host vehicle enters an area of high data connectivity or is dropped.

Abstract: Systems and methods are provided for operating a vehicle based on at least one updated road rule. The system may include one or more sensors or communication devices. The one or more sensors or communication devices may be configured to acquire data indicative of at least one temporal change in a road rule. A processor is provided operatively connected to the one or more communication devices. The processor is configured to update a standard road rule to an updated road rule based on the temporal change in the road rule, determine a change in a driving maneuver permitted for the vehicle based on the updated road rule, and cause the vehicle to implement the change in the driving maneuver. The processor may also be configured to send a command to update a road map display of the vehicle to graphically illustrate the temporal change in the road rule.

Abstract: System, methods, and other embodiments described herein relate to associating coordinates between separate coordinate systems. In one embodiment, a method includes acquiring location coordinates of a vehicle in a surrounding environment according to sensor data from at least one sensor of the vehicle. The method includes transforming reference coordinates associated with the location coordinates into first intermediate coordinates associated with a first coordinate system that is based, at least in part, on a distorted two-dimensional map projection, and second intermediate coordinates associated with a second coordinate system that is a Cartesian coordinate system associated with a Geodetic datum. The method includes generating, using the first intermediate coordinates and the second intermediate coordinates, an estimated transform for converting between the first coordinate system and the second coordinate system.

Abstract: System, methods, and other embodiments described herein relate to associating coordinates between separate coordinate systems. In one embodiment, a method includes acquiring location coordinates of a vehicle in a surrounding environment according to sensor data from at least one sensor of the vehicle. The method includes transforming reference coordinates associated with the location coordinates into first intermediate coordinates associated with a first coordinate system that is based, at least in part, on a distorted two-dimensional map projection, and second intermediate coordinates associated with a second coordinate system that is a Cartesian coordinate system associated with a Geodetic datum. The method includes generating, using the first intermediate coordinates and the second intermediate coordinates, an estimated transform for converting between the first coordinate system and the second coordinate system.

Abstract: System, methods, and other embodiments described herein relate to improving calibration of an onboard sensor of a vehicle. In one embodiment, a method includes, in response to acquiring sensor data from a surrounding environment of the vehicle using the onboard sensor, analyzing the sensor data to determine calibration parameters for the onboard sensor. The method includes identifying a suitability parameter that characterizes how well the surrounding environment provides for determining the calibration parameters. The method includes generating annotations within a map that specify at least the suitability parameter for a location associated with the sensor data. In further aspects, the method includes identifying, from the map, a calibration route for the vehicle that is a deviation from a current route in response to determining that the calibration state of the onboard sensor does not satisfy the calibration threshold.

Abstract: The systems and methods described herein disclose detecting objects in a vehicular environment using extracted high level features. As described here, a survey vehicle detects objects in the environment with a survey sensor. Vehicles can then use the extracted features from the survey sensor data to compare with extracted features from input sensor data. Thus, vehicles can benefit from different sensor data without employing said sensor. The systems and methods can include extracting one or more survey features from a survey data set, which can then be mapped to a feature-based map of an environment. An input data set can then be collected using an input sensor type with one or more input features being extracted from the input data set. The one or more input features can then be correlated to the one or more survey features to identify an object in the environment.

Abstract: The systems and methods described herein disclose detecting objects in a vehicular environment using extracted high level features. As described here, a survey vehicle detects objects in the environment with a survey sensor. Vehicles can then use the extracted features from the survey sensor data to compare with extracted features from input sensor data. Thus, vehicles can benefit from different sensor data without employing said sensor. The systems and methods can include extracting one or more survey features from a survey data set, which can then be mapped to a feature-based map of an environment. An input data set can then be collected using an input sensor type with one or more input features being extracted from the input data set. The one or more input features can then be correlated to the one or more survey features to identify an object in the environment.

Abstract: Systems and methods are provided for operating a vehicle based on at least one updated road rule. The system may include one or more sensors or communication devices. The one or more sensors or communication devices may be configured to acquire data indicative of at least one temporal change in a road rule. A processor is provided operatively connected to the one or more communication devices. The processor is configured to update a standard road rule to an updated road rule based on the temporal change in the road rule, determine a change in a driving maneuver permitted for the vehicle based on the updated road rule, and cause the vehicle to implement the change in the driving maneuver. The processor may also be configured to send a command to update a road map display of the vehicle to graphically illustrate the temporal change in the road rule.

Abstract: System, methods, and other embodiments described herein relate to improving calibration of an onboard sensor of a vehicle. In one embodiment, a method includes, in response to acquiring sensor data from a surrounding environment of the vehicle using the onboard sensor, analyzing the sensor data to determine calibration parameters for the onboard sensor. The method includes identifying a suitability parameter that characterizes how well the surrounding environment provides for determining the calibration parameters. The method includes generating annotations within a map that specify at least the suitability parameter for a location associated with the sensor data. In further aspects, the method includes identifying, from the map, a calibration route for the vehicle that is a deviation from a current route in response to determining that the calibration state of the onboard sensor does not satisfy the calibration threshold.