A system receives confirmation that a vehicle has accepted automatic control imposition for a drive within a geo-fenced boundary. The system tracks travel of a plurality of vehicles, including the vehicle, within the geo-fenced boundary. The system may determine that the vehicle has a threshold likelihood of encountering at least one of another vehicle or a boundary of the geo-fence at a threshold speed or above and responsive to the determination, impose automatic control on the vehicle, including at least one of controlled braking or speed limiting.

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

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

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.

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.

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 apparatus for recording license plates of vehicles travelling on a road having several adjacent lanes comprises a vehicle classification sensor configured to detect a predetermined shape characteristic of a vehicle or group of vehicles. The apparatus further comprises at least one camera mounted at an elevated point beside one of the lanes and having an angle of aperture covering at least one of said lanes, each lane covered by at least one camera. The vehicle classification sensor is configured to, upon detecting the predetermined shape characteristic on a lane, trigger the camera that covers the lane the predetermined shape characteristic is detected on to record an image of a license plate on the back of the vehicle or group's leading vehicle, respectively, for which the predetermined shape characteristic is detected. The triggered camera is of a lane either adjacent to or at least one lane apart from the lane.

An information processing apparatus includes a risk area identification unit configured to identify a risk area outside a moving object and a transmission control unit configured to perform control for transmitting risk area information representing the risk area identified by the risk area identification unit to a server configured to retain information related to the risk area, in which the risk area identification unit is configured to identify an area defined by a plurality of points as the risk area, and the risk area identification unit is configured to identify, based on a boundary between a first area in which the moving object is prohibited from moving and a second area in which the moving object is allowed to move, a shape of the risk area on a side of the first area.

An information processing apparatus includes a risk area identification unit configured to identify a risk area outside a moving object and a transmission control unit configured to perform control for transmitting risk area information representing the risk area identified by the risk area identification unit to a server configured to retain information related to the risk area, in which the risk area identification unit is configured to identify an area defined by a plurality of points as the risk area, and the risk area identification unit is configured to identify, based on a boundary between a first area in which the moving object is prohibited from moving and a second area in which the moving object is allowed to move, a shape of the risk area on a side of the first area.