# TrafficLightAI
A python traffic simulation serving as a playground to create traffic light A.I. systems. The traffic simulation uses a cellular automata approach to simulate large traffic grids. The simulation is optimized with Numba.
## Installation
```sh
pip install ai-traffic-light-simulator
```
## Example
```py
from traffic_simulation_numba import TrafficSimulation
# OR from traffic_simulation import TrafficSimulation
import random
NORTH_SOUTH_GREEN = 0
EAST_WEST_GREEN = 1
# A basic A.I. which randomly determines light timings
# Inputs: [North waiting, East waiting, South waiting, West Waiting, Previous Light Direction]
def my_ai(inputs):
if inputs[-1] == NORTH_SOUTH_GREEN:
return EAST_WEST_GREEN, random.randint(1,30)
if inputs[-1] == EAST_WEST_GREEN:
return NORTH_SOUTH_GREEN, random.randint(1,30)
# Make traffic simulation object with our naive A.I.
sim = TrafficSimulation(
my_ai,
grid_size_x=8,
grid_size_y=8,
lane_length=10,
max_speed=5,
in_rate=0.2,
initial_density=0.1,
seed=42
)
results = sim.run_simulation(1000) # Runs the simulation for 1000 ticks
print(results)
# Returns { 'cars_stopped': 131680, 'carbon_emissions': 672824 }
# Render a frame of the simulation after 1000 ticks
sim.render_frame("Small.png")
```
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"description": "# TrafficLightAI\r\nA python traffic simulation serving as a playground to create traffic light A.I. systems. The traffic simulation uses a cellular automata approach to simulate large traffic grids. The simulation is optimized with Numba.\r\n\r\n\r\n\r\n\r\n## Installation\r\n\r\n```sh\r\npip install ai-traffic-light-simulator\r\n```\r\n\r\n## Example\r\n\r\n```py\r\nfrom traffic_simulation_numba import TrafficSimulation\r\n# OR from traffic_simulation import TrafficSimulation\r\nimport random\r\n\r\nNORTH_SOUTH_GREEN = 0\r\nEAST_WEST_GREEN = 1\r\n\r\n# A basic A.I. which randomly determines light timings\r\n# Inputs: [North waiting, East waiting, South waiting, West Waiting, Previous Light Direction]\r\ndef my_ai(inputs):\r\n if inputs[-1] == NORTH_SOUTH_GREEN:\r\n return EAST_WEST_GREEN, random.randint(1,30)\r\n if inputs[-1] == EAST_WEST_GREEN:\r\n return NORTH_SOUTH_GREEN, random.randint(1,30)\r\n\r\n# Make traffic simulation object with our naive A.I.\r\nsim = TrafficSimulation(\r\n my_ai, \r\n grid_size_x=8,\r\n grid_size_y=8, \r\n lane_length=10,\r\n max_speed=5, \r\n in_rate=0.2, \r\n initial_density=0.1, \r\n seed=42\r\n)\r\n\r\nresults = sim.run_simulation(1000) # Runs the simulation for 1000 ticks\r\nprint(results)\r\n# Returns { 'cars_stopped': 131680, 'carbon_emissions': 672824 }\r\n\r\n# Render a frame of the simulation after 1000 ticks\r\nsim.render_frame(\"Small.png\")\r\n```\r\n",
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