Abstract: A computer device is provided. The computer device includes at least one processor and at least one memory device. The computer device is associated with a host vehicle. The at least one processor is programmed to: receive sensor information from one or more sensors associated with the host vehicle; build a local object map of the surroundings of the host vehicle based upon the received sensor information; identify a driving scenario based on the local object map; identify a target vehicle that will be affected by the identified driving scenario; and transmit one or more messages to the target vehicle about the detected driving scenario.

Abstract: A computer-implemented method for emotion detection and communication includes receiving host passenger data for a host passenger of a host vehicle and determining an emotion of the host vehicle based on the host passenger data. The method includes communicating the emotion of the host vehicle to one or more remote vehicles and an emotion of the one or more remote vehicles to the host vehicle. Further, the method includes generating an output based on the emotion of the host vehicle and the emotion of the one or more remote vehicles. The output is an interactive user interface providing an indication of the emotion of the host vehicle and an indication of the emotion of the one or more remote vehicle. The method includes rendering the output to a human machine interface device.

Abstract: A computer-implemented method for intersection communication includes detecting a first vehicle behind a host vehicle and in a same lane as the host vehicle and determining a rear distance between a rear end of the host vehicle and a front end of the first vehicle. The method also includes transmitting a backup request to the first vehicle based on the rear distance and a wait time period between the stop state and a go state controlled by a traffic signal device. Further, the method includes controlling the host vehicle to perform a backup maneuver with respect to an intersection based on the rear distance and the wait time period.

Abstract: Systems and methods for reporting electrical infrastructure and vegetation twining are provided. In one embodiment, a system for reporting electrical infrastructure and vegetation twining is provided. The system includes a recognition module, a position module, a twining module, and a report module. The recognition module is configured to detect electrical infrastructure and vegetation in a set of sensor data received from vehicle sensors. The position module is configured to associate a location with the set of sensor data. The twining module is configured to identify a twining event of the vegetation and the electrical infrastructure based on a proximity threshold of the electrical infrastructure and the vegetation. The report module is configured to generate a report including the twining event and the location.

Abstract: Systems and methods for reporting electrical infrastructure and vegetation twining are provided. In one embodiment, a system for reporting electrical infrastructure and vegetation twining is provided. The system includes a recognition module, a position module, a twining module, and a report module. The recognition module is configured to detect electrical infrastructure and vegetation in a set of sensor data received from vehicle sensors. The position module is configured to associate a location with the set of sensor data. The twining module is configured to identify a twining event of the vegetation and the electrical infrastructure based on a proximity threshold of the electrical infrastructure and the vegetation. The report module is configured to generate a report including the twining event and the location.

Abstract: A computer-implemented method for emotion detection and communication includes receiving host passenger data for a host passenger of a host vehicle and determining an emotion of the host vehicle based on the host passenger data. The method includes communicating the emotion of the host vehicle to one or more remote vehicles and an emotion of the one or more remote vehicles to the host vehicle. Further, the method includes generating an output based on the emotion of the host vehicle and the emotion of the one or more remote vehicles. The output is an interactive user interface providing an indication of the emotion of the host vehicle and an indication of the emotion of the one or more remote vehicle. The method includes rendering the output to a human machine interface device.

Abstract: A computer-implemented method for intersection communication includes detecting a first vehicle behind a host vehicle and in a same lane as the host vehicle and determining a rear distance between a rear end of the host vehicle and a front end of the first vehicle. The method also includes transmitting a backup request to the first vehicle based on the rear distance and a wait time period between the stop state and a go state controlled by a traffic signal device. Further, the method includes controlling the host vehicle to perform a backup maneuver with respect to an intersection based on the rear distance and the wait time period.

Abstract: According to one aspect, a computer-implemented method for communication between a plurality of vehicles at an intersection includes detecting the intersection ahead of a first vehicle. The method includes determining a time of arrival of a first vehicle at the intersection and a time of arrival of a second vehicle at the intersection is approximately the same. Further, the method includes receiving behavior data about the first vehicle for a previous time of duration before the time of arrival of the first vehicle at the intersection, and receiving behavior data about the second vehicle for a previous time of duration before the time of arrival of the second vehicle at the intersection. The method includes transmitting a resolution message including information for determining a right of way maneuver between the first vehicle and the second vehicle at the intersection.

Abstract: Systems and methods for cooperative smart lane selection are described. According to one embodiment, a computer-implemented method for cooperative smart lane selection includes receiving vehicle data for a plurality of vehicles. Each vehicle in the plurality of vehicles is travelling along a road segment having a plurality of lanes. The road segment is parsed into a plurality of inter-lane zones including a buffer zone and an implementation zone downstream of the buffer zone. Each inter-lane zone includes the lanes of the plurality of lanes. The computer-implemented method includes integrating the vehicle data into the plurality inter-lane zones by lane of the plurality of lanes. The computer-implemented method also includes calculating flow factors for the lanes in the implementation zone. The computer-implemented method further includes selecting a lane from the plurality of lanes based on the flow factors and controlling a host vehicle based on the flow factors.

Abstract: Systems and methods for cooperative smart lane selection are described. According to one embodiment, a computer-implemented method for cooperative smart lane selection includes receiving vehicle data for a plurality of vehicles. Each vehicle in the plurality of vehicles is travelling along a road segment having a plurality of lanes. The road segment is parsed into a plurality of inter-lane zones including a buffer zone and an implementation zone downstream of the buffer zone. Each inter-lane zone includes the lanes of the plurality of lanes. The computer-implemented method includes integrating the vehicle data into the plurality inter-lane zones by lane of the plurality of lanes. The computer-implemented method also includes calculating flow factors for the lanes in the implementation zone. The computer-implemented method further includes selecting a lane from the plurality of lanes based on the flow factors and controlling a host vehicle based on the flow factors.