Sensor based roadway traffic control system

A method, comprising,

• identifying, by one or more processors coupled with memory, from one or more sensors of a roadway intersection, sensor data corresponding to one or more objects moving within an area comprising the roadway intersection;
• identifying, by the one or more processors, based on the sensor data input into one or more machine learning (ML) models trained on a plurality of objects moving in a plurality of directions and according to a plurality of velocities within one or more areas comprising one or more roadway intersections, an object to be assisted in traversing the roadway intersection;
• determining, by the one or more processors, from the sensor data, a predicted trajectory of the object and a predicted time duration for the object to traverse the roadway intersection;
• determining, by the one or more processors, using a priority matrix mapping the predicted trajectory and the predicted time duration to one or more variations of control of one or more signals for one or more signaling devices of the roadway intersection, one or more signals to apply to the one or more signaling devices, wherein the one or more signals are determined based on a priority associated with a type of the object of a plurality of types of objects within the area;
• generating, by the one or more processors, one or more instructions for controlling the one or more signaling devices according to the one or more signals to assist the object in traversing the roadway intersection;
• initiating, by the one or more processors, via a controller and responsive to the one or more instructions, actuation of one or more phases of the one or more signaling devices of the roadway intersection according to the time duration for the object to traverse the roadway intersection;
• and
• verifying, by the one or more processors, upon initiation of the actuation of the one or more phases and based on sensor data from the one or more sensors, whether the object has traversed the roadway intersection within the predicted time duration.

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to:

• identify, from one or more sensors of a roadway intersection, sensor data corresponding to one or more objects moving within an area comprising the roadway intersection;
• identify, based on the sensor data input into one or more machine learning (ML) models trained on a plurality of objects moving in a plurality of directions and according to a plurality of velocities within one or more areas comprising one or more roadway intersections, an object to be assisted in traversing the roadway intersection;
• determine, from the sensor data, a predicted trajectory of the object and a predicted time duration for the object to traverse the roadway intersection;
• determine, using a priority matrix mapping the predicted trajectory and the predicted time duration to one or more variations of control of one or more signals for one or more signaling devices of the roadway intersection, one or more signals to apply to the one or more signaling devices, wherein the one or more signals are determined based on a priority associated with a type of the object of a plurality of types of objects within the area;
• generate one or more instructions for controlling the one or more signaling devices according to the one or more signals to assist the object in traversing the roadway intersection;
• initiate, via a controller and responsive to the one or more instructions, actuation of one or more phases of the one or more signaling devices of the roadway intersection according to the time duration for the object to traverse the roadway intersection;
• and
• verify, upon initiation of the actuation of the one or more phases and based on sensor data from the one or more sensors, whether the object has traversed the roadway intersection within the predicted time duration.