Systems and methods for determining object prioritization and predicting future object locations for an autonomous vehicle are provided. A method can include obtaining, by a computing system comprising one or more processors, state data descriptive of at least a current or past state of a plurality of objects that are perceived by an autonomous vehicle. The method can further include determining, by the computing system, a priority classification for each object in the plurality of objects based at least in part on the respective state data for each object. The method can further include determining, by the computing system, an order at which the computing system determines a predicted future state for each object based at least in part on the priority classification for each object and determining, by the computing system, the predicted future state for each object based at least in part on the determined order.

At least a method for determining risk behavior of a driver is described. While a vehicle is being driven, data is obtained related to the position and movement of a wireless communications device. The data may indicate the type of behavior exhibited by the driver while the vehicle is being driven.

Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive images captured over a time period; analyze images to identify a target vehicle; receive map information associated including a plurality of target trajectories; determine, based on analysis of the images, first and second estimated positions of the target vehicle within the time period; determine, based on the first and second estimated positions, a trajectory of the target vehicle over the time period; compare the determined trajectory to the plurality of target trajectories to identify a target trajectory traversed by the target vehicle; determine, based on the identified target trajectory, a position of the target vehicle; and determine a navigational action for the host vehicle based on the determined position.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using anchor trajectories.

A system and method for generating traffic reports is described. The system receives a set of inputs specifying at least a geographical region, a first period of time, and a second period of time. The system then identifies one or more streets within at least a threshold proximity of the specified geographical region and aggregates traffic information for the one or more streets over the first period of time and the second period of time, respectively. Further, the system generates a traffic report for the geographical region based at least in part on a comparison of the aggregated traffic information for the first period of time with the aggregated traffic information for the second period of time.

Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

An example operation may include one or more of identifying transports operating on a roadway, determining a degree of transport traffic based on the identified transports, when the degree of transport traffic has exceeded a traffic level, assigning one or more of the identified transports as a roadway manager, controlling movement of the roadway manager, and generating a roadway indicator on the roadway manager to direct the identified transports.

Systems and methods are provided for predicting blind spot incursions for a host vehicle. In one implementation, a navigation system for a host vehicle may comprise a processor. The processor may be programmed to receive, from an image capture device located on a rear of the host vehicle, at least one image representative of an environment of the host vehicle. The processor may be programmed to analyze the at least one image to identify an object in the environment of the host vehicle and to determine kinematic information associated with the object. The processor may further be programmed to predict, based on the kinematic information, that the object will travel in a region outside of a field of view of the image capture device and perform a control action based on the prediction.

Provided is a driving assistance device capable of ensuring safety by allowing an opposite lane to be always seen from a time of entering an intersection to a start of executing a right/left turn and enabling the right/left turn at the intersection without missing a right/left turn execution opportunity. An own vehicle C is caused to stand by at a standby position Cb which allows detecting a following vehicle D of the own vehicle C by a rear side sensor and determining whether or not an oncoming right/left-turn standby vehicle E is capable of a right/left turn. In a case where it is determined that the oncoming right/left-turn standby vehicle E crosses the intersection and turns right or left, and the own vehicle C is capable of crossing the intersection and turning right or left, a right/left turn of the own vehicle C is started.