Method and system for multimodal deep traffic signal control

A system for traffic signal control for an intersection of a traffic network, the traffic network comprising one or more sensors, the system comprising one or more processors and a data storage, the one or more processors configurable to execute:

• a data extraction module to:
• receive sensor readings from the one or more sensors, the sensor readings comprising a plurality of physical characteristics associated with vehicles approaching the intersection;
• discretize the sensor readings based on a grid of cells projected onto one or more streets approaching the intersection;
• for each of the plurality of physical characteristics, associate, for each of the cells in the grid of cells, a respective value for the cell in the grid of cells representing the physical characteristic associated with each of the vehicles if the vehicles at least partially occupy the cell, otherwise associating a null value for the cell, and generate a matrix associated with the physical characteristic comprising the respective values for each cell in the grid of cells;
• a machine learning module to combine each matrix associated with each of the plurality of physical characteristics as separate layers in a multi-layered matrix, and to determine, using a machine learning model trained with a traffic control training set, one or more traffic actions with the multi-layered matrix as input, the traffic control training set comprising previously determined multi-layered matrices for a plurality of traffic scenarios at the intersection;
• and
• a controller module to communicate the one or more actions to the traffic network.