There is provided a system and method for traffic signal control of a traffic network with a learned model. The method including: receiving sensor readings from the traffic network, the sensor readings including positions and speeds of vehicles approaching each intersection; using a learned dynamics model that takes the sensor readings as input, predicting a plurality of possibilities for position and velocity of the vehicles approaching each intersection in a future timestep; determining a action for the one or more intersections by performing a tree search on the plurality of possibilities and selecting the possibility with a highest action value; and outputting the action to the traffic network for implementation as a traffic control action at the one or more intersections.

A vehicle navigation system includes an electronic control unit. The electronic control unit receives image data regarding a source of a traffic jam on a roadway from a plurality of sensors of a plurality of vehicles in a mesh network. Moreover, the electronic control unit generates a bird's eye view of the traffic jam based on the image data, wherein the bird's eye view includes a graphical representation of the source of the traffic jam and a graphical representation of vehicles on the roadway within the traffic jam. A display device displays the bird's eye view.

A vehicle navigation system includes an electronic control unit. The electronic control unit receives image data regarding a source of a traffic jam on a roadway from a plurality of sensors of a plurality of vehicles in a mesh network. Moreover, the electronic control unit generates a bird's eye view of the traffic jam based on the image data, wherein the bird's eye view includes a graphical representation of the source of the traffic jam and a graphical representation of vehicles on the roadway within the traffic jam. A display device displays the bird's eye view.

Systems and methods for detecting or predicting potential collisions between vehicles are provided. The systems and methods may receive sensor output indicative of a location, a heading, and/or a moving speed of a first vehicle and/or a second vehicle. The systems and methods may predict a collision between the vehicles at an intersection between routes based on the received sensor output. The systems and methods may change movement of the first vehicle and/or the second vehicle responsive to predicting the collision.

Systems and methods for detecting or predicting potential collisions between vehicles are provided. The systems and methods may receive sensor output indicative of a location, a heading, and/or a moving speed of a first vehicle and/or a second vehicle. The systems and methods may predict a collision between the vehicles at an intersection between routes based on the received sensor output. The systems and methods may change movement of the first vehicle and/or the second vehicle responsive to predicting the collision.

A system and method for providing an interpretable and unified representation for trajectory prediction that includes receiving birds-eye image data associated with travel of at least one agent within a roadway environment. The system and method also include analyzing the birds-eye image data to determine a potential field associated with the roadway environment and analyzing the birds-eye image data to determine a potential field associated with a past trajectory of the at least one agent. The system and method further include predicting a future trajectory of the at least one agent based on analysis of the potential fields.

A system and method for providing an interpretable and unified representation for trajectory prediction that includes receiving birds-eye image data associated with travel of at least one agent within a roadway environment. The system and method also include analyzing the birds-eye image data to determine a potential field associated with the roadway environment and analyzing the birds-eye image data to determine a potential field associated with a past trajectory of the at least one agent. The system and method further include predicting a future trajectory of the at least one agent based on analysis of the potential fields.

An example operation includes one or more of initially determining, via one or more sensors on a transport, that the transport is approaching a one-way road in a wrong direction based on a slowing down of the transport and a movement of the transport toward the one-way road, notifying, via the one or more sensors, one or more occupants of the transport about the approaching, and in response to the transport continuing to approach in the wrong direction, slowing the transport, by a computer associated with the transport, to not permit entry into the one-way road.

An example operation includes one or more of initially determining, via one or more sensors on a transport, that the transport is approaching a one-way road in a wrong direction based on a slowing down of the transport and a movement of the transport toward the one-way road, notifying, via the one or more sensors, one or more occupants of the transport about the approaching, and in response to the transport continuing to approach in the wrong direction, slowing the transport, by a computer associated with the transport, to not permit entry into the one-way road.

Techniques for collecting, synchronizing, and displaying various types of data relating to a road segment enable, via one or more local or remote processors, servers, transceivers, and/or sensors, (i) enhanced and contextualized analysis of vehicle events by way of synchronizing different data types, relating to a monitored road segment, collected via various different types of data sources; (ii) enhanced and contextualized analysis of filed insurance claims pertaining to a vehicle incident at a road segment; (iii) advantageous machine learning techniques for predicting a level of risk assumed for a given vehicle event or a given road segment; (iv) techniques for accounting for region-specific driver profiles when controlling autonomous vehicles; and/or (v) improved techniques for providing a GUI to display collected data in a meaningful and contextualized manner.