Add Smart Traffic Light Example

examples/smart_traffic_lights/README.md

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+# Smart Traffic Lights
+
+## Summary
+
+An optimization simulation where traffic light agents use local information to minimize vehicle wait times at intersections.
+
+![Simulation of Smart Traffic Controller](./assets/chrome-capture-2026-03-09_TrafficModel_Mesa.gif)
+
+## Installation
+
+To install the dependencies use pip and the requirements.txt in this directory. e.g.
+
+```
+    $ pip install -r requirements.txt
+```
+
+
+
+Then open your browser to [http://127.0.0.1:8521/](http://127.0.0.1:8521/), select the model parameters, press Reset, then Start.
+
+## Files
+
+* ``smart_traffic_light/agents.py``: Defines the CarAgent, the TrafficLightAgent and the IntersectionController classes.
+* ``smart_traffic_light/model.py``: Defines the Traffic model and the DataCollector functions.
+* ``run_example.py``: Script to compare waiting time in traffic using smart and normal traffic light controller.
+* ``app.py``: Visualization script on Solara.

examples/smart_traffic_lights/app.py

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+from typing import Any
+
+import mesa
+from mesa.visualization import SolaraViz, make_plot_component, make_space_component
+from smart_traffic_lights.agents import (
+    CarAgent,
+    Direction,
+    LightState,
+    TrafficLightAgent,
+)
+from smart_traffic_lights.model import TrafficModel
+
+
+def traffic_portrayal(agent: mesa.Agent) -> dict[str, Any]:
+    """
+    Determines how agents are drawn on the grid.
+
+    - Cars: Blue for East, Purple for North.
+    - Lights: Circle markers, Red or Green based on state.
+    - Controller: Hidden (has no position).
+    """
+
+    if isinstance(agent, TrafficLightAgent):
+        return {
+            "color": "tab:green" if agent.state == LightState.GREEN else "tab:red",
+            "marker": "o",  # Circle for lights
+            "size": 100,
+            "zorder": 1,  # Ensure lights are drawn above cars
+            "alpha": 1.0,
+        }
+    if isinstance(agent, CarAgent):
+        return {
+            "color": "tab:blue" if agent.direction == Direction.EAST else "tab:purple",
+            "marker": "s",  # Square for cars
+            "zorder": 0,  # Ensure lights are drawn above cars
+            "size": 40,
+        }
+    return {}
+
+
+# Define interactive parameters for Solara UI
+model_params = {
+    "width": mesa.visualization.Slider(
+        label="Width of the grid", value=20, min=5, max=40, step=1
+    ),
+    "height": mesa.visualization.Slider(
+        label="Height of the grid", value=20, min=5, max=40, step=1
+    ),
+    "num_cars_east": mesa.visualization.Slider(
+        label="Number of cars going east", value=8, min=1, max=20, step=1
+    ),
+    "num_cars_north": mesa.visualization.Slider(
+        label="Number of cars going north", value=8, min=1, max=20, step=1
+    ),
+    "smart_lights": mesa.visualization.Slider(
+        label="Smart Lights (0=Off, 1=On)", value=1, min=0, max=1, step=1
+    ),
+}
+
+# Create the Grid View
+space_component = make_space_component(traffic_portrayal)
+
+# Create the Wait Time Chart
+wait_time_chart = make_plot_component({"Total_Red_Light_Wait_Time": "tab:red"})
+
+initial_model = TrafficModel()
+
+# Instantiate the Solara Visualization Page
+app = SolaraViz(
+    model=initial_model,
+    model_params=model_params,
+    components=[
+        space_component,
+        wait_time_chart,
+    ],
+    name="Smart Traffic Simulation",
+)
+
+
+# app

examples/smart_traffic_lights/requirements.txt

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+mesa[viz]>=3.0
+networkx
+numpy
+pandas
+enum
+typing
+matplotlib

examples/smart_traffic_lights/run_example.py

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+import numpy as np
+from smart_traffic_lights.model import TrafficModel
+
+STEPS = 2000
+
+width = 20
+height = 20
+num_cars_east = 8
+num_cars_north = 8
+
+
+print("Running Static Traffic Lights Simulation...")
+model_static = TrafficModel(smart_lights=False)
+for _ in range(STEPS):
+    model_static.step()
+
+print("Running Smart Traffic Lights Simulation...")
+model_smart = TrafficModel(smart_lights=True)
+for _ in range(STEPS):
+    model_smart.step()
+
+# Retrieve data
+static_df = model_static.datacollector.get_model_vars_dataframe()
+smart_df = model_smart.datacollector.get_model_vars_dataframe()
+
+# Calculate the percentage improvement
+final_wait_static = static_df["Total_Red_Light_Wait_Time"].iloc[-1]
+final_wait_smart = smart_df["Total_Red_Light_Wait_Time"].iloc[-1]
+
+improvement = np.round(
+    (final_wait_static - final_wait_smart) / final_wait_static * 100, 2
+)
+
+print("-" * 40)
+print(f"Results after {STEPS} steps:")
+print(f"Total Red Light Wait Time (Static Lights): {final_wait_static} steps")
+print(f"Total Red Light Wait Time (Smart Lights) : {final_wait_smart} steps")
+print(
+    f"Performance Improvement        : {improvement}% reduction in red light wait time"
+)
+print("-" * 40)
+
+final_wait_static = static_df["Total_Wait_Time"].iloc[-1]
+final_wait_smart = smart_df["Total_Wait_Time"].iloc[-1]
+
+improvement = np.round(
+    (final_wait_static - final_wait_smart) / final_wait_static * 100, 2
+)
+
+print("-" * 40)
+print(f"Total Wait Time (Static Lights): {final_wait_static} steps")
+print(f"Total Wait Time (Smart Lights) : {final_wait_smart} steps")
+print(f"Performance Improvement        : {improvement}% reduction in total wait time")
+print("-" * 40)

examples/smart_traffic_lights/smart_traffic_lights/agents.py

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+import enum
+
+import mesa
+
+
+class Direction(enum.Enum):
+    EAST = (1, 0)
+    NORTH = (0, 1)
+
+
+class LightState(enum.Enum):
+    RED = 0
+    GREEN = 1
+
+
+class TrafficLightAgent(mesa.Agent):
+    """
+    An agent representing a single traffic light.
+
+    Attributes:
+        state (LightState): The current state of the light (RED or GREEN).
+        direction (Direction): The flow of traffic this light controls.
+    """
+
+    def __init__(self, model: mesa.Model, state: LightState, direction: Direction):
+        super().__init__(model)
+        self.state = state
+        self.direction = direction
+
+    def step(self):
+        # Traffic lights are passive; the Controller changes their state.
+        pass
+
+
+class CarAgent(mesa.Agent):
+    """
+    An agent representing a car in the grid.
+
+    Attributes:
+        direction (Direction): The direction the car is traveling.
+        wait_time (int): Accumulator for time steps spent not moving.
+    """
+
+    def __init__(self, model: mesa.Model, direction: Direction):
+        super().__init__(model)
+        self.direction = direction
+        self.total_wait_time = 0
+        self.red_light_wait_time = 0
+
+    def step(self):
+        """
+        Determines if the car can move forward based on obstacles and lights.
+        """
+
+        # Calculate the next coordinate based on direction
+        next_x = (self.pos[0] + self.direction.value[0]) % self.model.grid.width
+        next_y = (self.pos[1] + self.direction.value[1]) % self.model.grid.height
+        next_pos = (next_x, next_y)
+
+        can_move = True
+        stopped_by_red_light = False
+        cell_contents = self.model.grid.get_cell_list_contents([next_pos])
+
+        for obj in cell_contents:
+            if isinstance(obj, CarAgent):
+                can_move = False
+                break
+            elif isinstance(obj, TrafficLightAgent):
+                # Only stop if the light controls our direction and is red
+                if obj.direction == self.direction and obj.state == LightState.RED:
+                    can_move = False
+                    stopped_by_red_light = True
+                    break
+
+        if can_move:
+            self.model.grid.move_agent(self, next_pos)
+        else:
+            self.total_wait_time += 1
+            if stopped_by_red_light:
+                self.red_light_wait_time += 1
+
+
+class IntersectionController(mesa.Agent):
+    """
+    A meta-agent that controls the traffic lights at an intersection.
+
+    Attributes:
+        smart (bool): If True, uses queue density to toggle. If False, uses fixed timer.
+        lights (List[TrafficLightAgent]): The lights managed by this controller.
+    """
+
+    def __init__(
+        self,
+        model: mesa.Model,
+        smart: bool,
+        lights: list[TrafficLightAgent],
+        sensor_range: int = 5,
+        static_wait=15,
+    ):
+        super().__init__(model)
+        self.smart = smart
+        self.static_wait = static_wait
+        self.lights = {light.direction: light for light in lights}  # Dictionary
+        self.sensor_range = sensor_range
+        self.timer = 0
+        self.cooldown = 2  # Minimum steps before a light can change again
+
+    def get_queue_density(self, light: TrafficLightAgent) -> int:
+        """
+        Calculates the number of cars waiting in the sensor zone approaching the light.
+        """
+        count = 0
+        # Look backwards from the light based on the direction it controls
+        dx, dy = light.direction.value
+        for i in range(1, self.sensor_range + 1):
+            check_x = (light.pos[0] - dx * i) % self.model.grid.width
+            check_y = (light.pos[1] - dy * i) % self.model.grid.height
+
+            check_pos = (check_x, check_y)
+            if any(
+                isinstance(a, CarAgent)
+                for a in self.model.grid.get_cell_list_contents([check_pos])
+            ):
+                count += 1
+        return count
+
+    def toggle_lights(self):
+        """
+        Switches all lights managed by the controller.
+        """
+        for light in self.lights.values():
+            light.state = (
+                LightState.GREEN if light.state == LightState.RED else LightState.RED
+            )
+        self.timer = 0
+
+    def step(self):
+        self.timer += 1
+
+        if not self.smart:
+            # Static: Toggle every fixed interval
+            if self.timer >= self.static_wait:
+                self.toggle_lights()
+        else:
+            # Smart: Toggle based on dynamic queue density
+            if self.timer >= self.cooldown:
+                # Select lights by direction to find queue lengths
+                east_light = self.lights[Direction.EAST]
+                north_light = self.lights[Direction.NORTH]
+
+                east_queue = self.get_queue_density(east_light)
+                north_queue = self.get_queue_density(north_light)
+
+                # If the current green light has a smaller queue than the red light, toggle
+                if (
+                    east_light.state == LightState.GREEN and north_queue > east_queue
+                ) or (
+                    north_light.state == LightState.GREEN and east_queue > north_queue
+                ):
+                    self.toggle_lights()