Method and system for traffic signal control with a learned model

A system for traffic signal control of a traffic network with a learned model of a traffic network, the traffic network comprising one or more intersections and sensors associated with the intersections to determine vehicle traffic approaching each intersection, the system comprising one or more processors and a data storage, the one or more processors configurable to execute at each timestep:

• an input module to receive sensor readings from the traffic network, the sensor readings comprising positions and speeds of vehicles approaching each intersection;
• a machine learning module to, using a dynamics model that takes the sensor readings as input, predict a plurality of possibilities for position and velocity of the vehicles approaching each intersection in a future timestep;
• a selection module to determine an 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
• an action module to output the action to the traffic network for implementation as a traffic control action at the one or more intersections.