Smart Traffic Engagement and Management System (STEMS)

Traditional Traffic Lights (TTL)

SUMO_TTL.mp4

STEMS

SUMO_STEMS.mp4

Plots

Waiting Time Comparison

Queue Length Comparison

Average Speed Comparison

Environment

• A 4x4 intersection with left-hand driving rule
• Each arm is 500 meters long
• Right-most lane dedicated to right-turn only
• Left-most lane dedicated to left turn and straight
• Two middle lanes dedicated to only going straight

Traffic Generation

• SUMO_HOME/tools/random_trips.py is used to generate vehicle trips
• The insertion times follow headway pattern of the Poisson distribution

The Double Deep Q-Learning Agent

State

• The current signal phase (one-hot encoded)
• Queue lengths per lane
• Total number of vehicles per lane
• Cumulative waiting time per lane

Reward

Change in cumulative waiting time of all vechicles between actions

Action

Choice of the traffic light phase from the 4 possible phases, described below. Every phase has a duration of 10 seconds. When the phase changes, a yellow phase of 3 seconds is activated

• North-South Advance: green for lanes in the north and south arm dedicated to turning left or going straight
• North-South Right Advance: green for lanes in the north and south arm dedicated to turning right
• East-West Advance: green for lanes in the east and west arm dedicated to turning left or going straight
• East-West Right Advance: green for lanes in the east and west arm dedicated to turning right

Credits

AndreaVidali - Deep Q-Learning Agent for Traffic Signal Control