Abstract: An anticipatory lane change system is described for assisting a host vehicle positioned in a current lane that is adjacent an adjacent lane. The anticipatory lane change system may include an identification module that identifies a potential lane change location and receives proximate vehicle data associated with proximate vehicles. The anticipatory lane change system may include a prediction module that predicts future kinematic data at a future time for a set of the proximate vehicles. The anticipatory lane change system may include a determination module that determines whether a gap will be available at the potential lane change location at the future time based on the future kinematic data. The anticipatory lane change system may include a lane change module that initiates a lane change maneuver for the host vehicle in response to determining that the gap will be available at the potential lane change location at the future time.

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.

Abstract: A computer-implemented method for lane hazard prediction including receiving vehicle data from a plurality of vehicles each equipped for computer communication. Each vehicle in the plurality of vehicles is travelling along a road network including a plurality of lanes, and each lane in the plurality of lanes includes a plurality of lane level cells where each lane level cell includes a particular portion of a lane in the plurality of lanes. The method includes integrating the vehicle data into the plurality of lane level cells, and for each lane level cell in the plurality of lane level cells, calculating a probability that a hazard exists with respect to the lane level cell based on the vehicle data associated with the lane level cell, an adjacent upstream cell, and an adjacent downstream cell. Further, the method includes controlling a host vehicle based on the probability that the hazard exists downstream from the host vehicle.

Abstract: An anticipatory lane change system is described for assisting a host vehicle positioned in a current lane that is adjacent an adjacent lane. The anticipatory lane change system may include an identification module that identifies a potential lane change location and receives proximate vehicle data associated with proximate vehicles. The anticipatory lane change system may include a prediction module that predicts future kinematic data at a future time for a set of the proximate vehicles. The anticipatory lane change system may include a determination module that determines whether a gap will be available at the potential lane change location at the future time based on the future kinematic data. The anticipatory lane change system may include a lane change module that initiates a lane change maneuver for the host vehicle in response to determining that the gap will be available at the potential lane change location at the future time.

Abstract: The disclosure relates to vehicle navigation systems. More specifically, the disclosure relates to vehicle navigation systems that utilize fuel use and emissions criteria as a parameter to determine directions between two locations.

Abstract: The disclosure relates to vehicle navigation systems. More specifically, the disclosure relates to vehicle navigation systems that utilize fuel use and emissions criteria as a parameter to determine directions between two locations.