Traffic Manager System

Overview

The Traffic Manager is a comprehensive component for managing NPC vehicle traffic simulation in the V2X (Advanced Workflow Simulation for Intelligent Machines) framework. It serves as the central orchestrator that coordinates multiple traffic simulators, manages vehicle spawning, and maintains the overall simulation lifecycle.

Introduction

The Traffic Manager system is designed to provide realistic, reproducible traffic scenarios that can accommodate both random traffic patterns and predefined route-based vehicle behaviors. It combines sophisticated behavioral modeling with performance optimization to enable large-scale traffic simulations.

Core Architecture

The Traffic Manager operates as the top-level controller that integrates several specialized subsystems working in harmony.

System Components

Traffic SimulatorsNPC Vehicle SimulatorVehicle Spawner

The manager supports multiple traffic simulator types that can coexist and operate simultaneously:

RandomTrafficSimulator: Generates unpredictable traffic patterns
RouteTrafficSimulator: Manages vehicles following predetermined paths

Note

Each simulator implements the ITrafficSimulator interface, providing a unified approach to vehicle spawning regardless of the underlying traffic generation strategy.

The core simulation engine responsible for updating vehicle states through a sophisticated multi-step process:

graph LR
    A[Cognition] --> B[Decision]
    B --> C[Control]
    C --> D[Visualization]

The simulator employs a cognition-decision-control-visualization pipeline that processes each vehicle's state every frame, ensuring realistic behavior and interactions.

The spawning subsystem handles the instantiation of NPC vehicles at designated spawn points.

Key Features:

Collision detection at spawn points
Ensures vehicles are only placed in safe, unoccupied locations
Supports multiple vehicle prefabs

Configuration Parameters

The Traffic Manager provides extensive configuration options through serialized fields that can be adjusted in the Unity Editor:

🎲 Seed-Based Reproducibility

Deterministic Simulations

A critical feature of the system is its ability to produce deterministic traffic patterns through a configurable seed value. This ensures that traffic scenarios can be replayed identically for testing, debugging, and validation purposes.

⚙️ Vehicle Configuration

The system uses NPCVehicleConfig to define behavioral parameters:

Parameter	Description	Default Value
`Acceleration`	Rate of speed increase	3.0 m/s²
`Deceleration`	Normal braking rate	2.0 m/s²
`SuddenDeceleration`	Emergency braking rate	4.0 m/s²
`AbsoluteDeceleration`	Maximum braking force	20.0 m/s²

These parameters influence how vehicles respond to traffic conditions, obstacles, and traffic control devices.

🎯 Layer Masks

The manager employs separate layer masks for precise physics queries:

Vehicle Layer Mask: Used for vehicle-to-vehicle collision detection
Ground Layer Mask: Used for terrain following and ground checks

Tip

This separation allows the physics system to optimize queries and prevent false positives.

👥 Vehicle Population Control

public int maxVehicleCount = 40;

The maxVehicleCount parameter limits the total number of simultaneously active vehicles in the scene. This provides a mechanism to balance traffic density against computational performance.

🚗 Ego Vehicle Integration

The manager maintains a reference to the ego vehicle (typically the player-controlled or primary autonomous vehicle):

If no ego vehicle is provided, the system automatically creates a dummy ego
The ego vehicle serves as a reference point for various calculations
Can influence NPC behavior and spawn decisions

Simulation Pipeline

Three-Step Processing Model

The NPC Vehicle Simulator implements a sophisticated three-step processing pipeline that executes during each fixed update.

Step 1: Cognition 🧠

The initial phase gathers environmental information for each vehicle.

Cognition Tasks

✅ Ground Existence: Ensures vehicles remain on valid surfaces
🛣️ Lane Following: Identifies next lane and waypoint based on position and route
🚦 Traffic Lights: Monitors traffic light states to determine passability
⚠️ Right-of-Way: Evaluates conditions at intersections
🔄 Curve Detection: Detects sharp curves requiring reduced speed
🚙 Obstacle Detection: Identifies front obstacles for safe following distances

Performance Optimization

The cognition step leverages Unity's Job System and burst-compiled code for parallel processing, significantly improving performance when handling large numbers of vehicles.

Step 2: Decision 🤔

Based on cognitive information, this phase determines each vehicle's immediate actions.

Decision Outputs:

graph TD
    A[Cognitive Data] --> B{Decision Logic}
    B --> C[Target Point]
    B --> D[Speed Mode]
    B --> E[Stopping Distance]

    D --> F[NORMAL]
    D --> G[SLOW]
    D --> H[STOP]
    D --> I[SUDDEN_STOP]
    D --> J[ABSOLUTE_STOP]

The decision system:

🎯 Calculates short-term target points for steering
🚦 Selects appropriate speed modes based on traffic conditions
📏 Computes stoppable distances considering current speed and deceleration

Safety Margins

The decision logic implements safety margins to prevent collisions and ensures smooth, realistic transitions between different driving behaviors.

Step 3: Control 🎮

The final simulation phase updates vehicle kinematics.

Control Task	Description
Speed Control	Calculates linear speed changes according to selected mode
Steering Control	Computes angular velocity (yaw speed) based on target point
Position Update	Updates vehicle positions and orientations in world space
Motion Smoothing	Applies smoothing factors to eliminate jerky movements

# Pseudo-code for control step
def update_speed(vehicle, delta_time):
    target_speed = get_target_speed(vehicle.speed_mode)
    acceleration = get_acceleration(vehicle.speed_mode)
    vehicle.speed = move_towards(vehicle.speed, target_speed, acceleration * delta_time)

def update_yaw_speed(vehicle, delta_time):
    steering_angle = calculate_angle_to_target(vehicle)
    target_yaw_speed = steering_angle * vehicle.speed * YAW_MULTIPLIER
    vehicle.yaw_speed = lerp(vehicle.yaw_speed, target_yaw_speed, LERP_FACTOR * delta_time)

Visualization and State Application

Following the simulation steps, a visualization phase updates the actual Unity GameObjects representing NPC vehicles.

Visualization Tasks

📍 Applies calculated positions and rotations to vehicle transforms
💡 Manages turn signal states based on upcoming lane changes
✨ Ensures visual consistency between internal simulation state and rendered scene

graph LR
    A[Internal State] --> B[Visualization Step]
    B --> C[Transform Update]
    B --> D[Turn Signals]
    B --> E[Visual Effects]
    C --> F[Rendered Scene]
    D --> F
    E --> F

Traffic Simulator Management

Spawn Priority System

A sophisticated priority mechanism manages situations where multiple traffic simulators attempt to spawn vehicles in the same lane simultaneously.

Why Priority System?

Without this system, certain vehicle sizes might dominate spawning, preventing variety in the traffic mix.

How It Works

sequenceDiagram
    participant S1 as Simulator 1
    participant S2 as Simulator 2
    participant TM as Traffic Manager
    participant Lane as Spawn Lane

    S1->>TM: Request spawn (Priority: 0)
    S2->>TM: Request spawn (Priority: 2)
    TM->>TM: Sort by priority
    TM->>S2: Attempt spawn (highest priority)
    S2->>Lane: Spawn successful
    TM->>S1: Increase priority (+1)
    TM->>S2: Reset priority (0)

Priority Algorithm:

Track each simulator's spawn attempts
When multiple simulators target the same spawn location, sort by current priority
Allow the highest-priority simulator to attempt spawning first
After successful spawn:
All other waiting simulators receive a priority increment (+1)
Successful simulator's priority resets to zero (0)

Result

This round-robin approach ensures fair distribution of spawning opportunities across all simulators, regardless of vehicle sizes or other constraints.

Spawn Point Collision Detection

Before spawning any vehicle, the system performs comprehensive collision checks using Unity's physics engine.

public static bool IsSpawnable(Bounds localBounds, NPCVehicleSpawnPoint spawnPoint)
{
    var rotation = Quaternion.LookRotation(spawnPoint.Forward);
    var center = rotation * localBounds.center + spawnPoint.Position;

    return !Physics.CheckBox(
        center,
        localBounds.extents,
        rotation,
        ignoreGroundLayerMask,
        QueryTriggerInteraction.Ignore);
}

Process:

📦 Create a bounding box based on the vehicle prefab's dimensions
🔍 Check for intersections with existing vehicles at the proposed location
✅ Only proceed with spawning if the location is completely clear

Tip

This prevents vehicles from spawning inside each other and ensures all traffic emerges from realistic, safe positions.

Ego Vehicle Proximity Filtering

To maintain immersion and prevent vehicles from suddenly appearing near the player, the Traffic Manager implements a minimum spawn distance check.

[SerializeField, Tooltip("A minimal distance between the EGO and the NPC to spawn")]
private float spawnDistanceToEgo = 50.0f;

Exclusion Zone:

graph TD
    A[Spawn Request] --> B{Check Distance to Ego}
    B -->|< 50m| C[Reject Spawn]
    B -->|≥ 50m| D{Collision Check}
    D -->|Clear| E[Spawn Vehicle]
    D -->|Blocked| C

Purpose

The configurable spawnDistanceToEgo parameter creates an exclusion zone around the ego vehicle, ensuring all visible vehicle appearances occur at a natural distance.

Route Management and Lane Following

Dynamic Route Extension

The system implements an intelligent route extension mechanism that allows vehicles to continue operating even after completing their initial route.

flowchart TD
    A[Vehicle Reaches End of Route] --> B{Has Predefined Route?}
    B -->|Yes, Route Complete| C[Select Random Connected Lane]
    B -->|No, Random Traffic| D[Always Random Selection]
    C --> E[Extend Following Lanes]
    D --> E
    E --> F[Continue Driving]

    style C fill:#e1f5ff
    style D fill:#ffe1e1

Simulator Behavior

RouteTrafficSimulator: Follows specified route precisely until the final lane, then uses random extension
RandomTrafficSimulator: Uses random lane selection throughout entire lifecycle

This creates the impression of vehicles with purposes beyond the immediate simulation area, contributing to a more believable traffic environment.

Each vehicle maintains a waypoint index indicating its current target point along its following lane.

Event	Action
Approaching waypoint (< 1m)	Advance to next waypoint
Reach lane's final waypoint	Transition to next lane in route
No lanes remaining	Mark vehicle for despawn

# Pseudo-code for waypoint following
def update_waypoint(vehicle):
    distance_to_waypoint = calculate_distance(vehicle.position, current_waypoint)

    if distance_to_waypoint <= 1.0:
        if vehicle.waypoint_index >= last_waypoint_index:
            extend_following_lane()
            remove_current_lane()
            vehicle.waypoint_index = 1
        else:
            vehicle.waypoint_index += 1

Benefits

This waypoint-based approach allows for:

✨ Smooth curved paths
🔄 Natural lane transitions
📍 Precise vehicle positioning

Traffic Light Integration

The Traffic Manager integrates with traffic light systems following Vienna Convention rules.

Traffic Light States

stateDiagram-v2
    [*] --> GREEN
    GREEN --> YELLOW
    YELLOW --> RED
    RED --> GREEN

    GREEN: Vehicle May Proceed
    YELLOW: Stop if Safe
    RED: Must Stop

Passability Logic

The cognition step identifies relevant traffic lights along each vehicle's path and determines passability:

Light State	Vehicle Response
🟢 GREEN	Proceed normally
🟡 YELLOW	Stop if safe to do so; otherwise commit to crossing
🔴 RED	Stop at intersection

Yellow Light Behavior

The decision step calculates appropriate stopping distances for yellow lights, implementing realistic behavior:

IF distance_to_light < sudden_stop_distance:
    COMMIT to crossing (cannot stop safely)
ELSE:
    STOP at intersection

Result

This creates authentic intersection behaviors and prevents unrealistic hard braking.

Right-of-Way and Intersection Logic

The system implements sophisticated intersection management through a yield phase system. Vehicles approaching intersections enter various yielding states that govern their behavior.

Yield Phases

graph TD
    A[Approaching Intersection] --> B{Evaluate Conditions}
    B --> C[ENTERING_INTERSECTION]
    B --> D[LEFT_HAND_RULE_ENTERING]
    B --> E[LANES_RULES_ENTERING]
    B --> F[INTERSECTION_BLOCKED]

    C --> G[AT_INTERSECTION]
    D --> H[LEFT_HAND_RULE_AT]
    E --> I[LANES_RULES_AT]
    F --> J[Wait for Clear]

    G --> K[Exit Intersection]
    H --> K
    I --> K
    J --> B

    style C fill:#90EE90
    style G fill:#90EE90
    style D fill:#FFD700
    style H fill:#FFD700
    style E fill:#FFA500
    style I fill:#FFA500
    style F fill:#FF6B6B

Yield Phase Descriptions

Intersection EntryLeft-Hand RuleLane-Based PriorityForced PriorityIntersection Blocking

ENTERING_INTERSECTION

Vehicles approaching an intersection evaluate whether they must yield to other traffic based on right-of-way lanes and traffic light states.

LEFT_HAND_RULE_ENTERING / AT_INTERSECTION

At uncontrolled intersections, the system applies left-hand priority rules to determine which vehicle proceeds first.

Rule: Vehicles must yield to traffic approaching from the right.

LANES_RULES_ENTERING / AT_INTERSECTION

The system respects configured right-of-way relationships between lanes, ensuring vehicles yield appropriately to higher-priority traffic flows.

FORCING_PRIORITY

In deadlock situations, the system can force priority to specific vehicles to maintain traffic flow and prevent indefinite waiting.

INTERSECTION_BLOCKED

Vehicles avoid entering intersections if doing so would block cross traffic, implementing realistic gridlock prevention.

Intersection Behavior Matrix

Situation	Yield Phase	Vehicle Action
Approaching with green light	ENTERING	Proceed if clear
At uncontrolled intersection	LEFT_HAND_RULE	Check right side traffic
Priority lane conflict	LANES_RULES	Yield to higher priority
Cross traffic present	INTERSECTION_BLOCKED	Wait outside intersection
Deadlock detected	FORCING_PRIORITY	Override and proceed

Performance Optimization

The Traffic Manager employs several optimization strategies to maintain performance with large vehicle populations.

Optimization Techniques

Unity Job SystemBatch ProcessingProfiler IntegrationLazy Evaluation

Parallel Processing

The cognition step uses burst-compiled parallel jobs for expensive operations like obstacle detection and ground checks.

Benefits:

⚡ Leverages multiple CPU cores
🚀 Uses SIMD instructions for maximum efficiency
📊 Processes multiple vehicles simultaneously

[BurstCompile]
private struct ObstacleCheckJob : IJobParallelFor
{
    public LayerMask VehicleLayerMask;
    [ReadOnly] public NativeArray<NativeState> States;
    [WriteOnly] public NativeArray<BoxcastCommand> Commands;

    public void Execute(int index)
    {
        // Parallel obstacle detection logic
    }
}

Command Buffers

Raycasts and boxcasts are batched using Unity's command buffers:

Reduces CPU overhead
Improves cache coherence
Minimizes context switching

// Schedule batch of raycasts
raycastJobHandle = RaycastCommand.ScheduleBatch(
    raycastCommands,
    groundHitInfoArray,
    batchSize: 8,
    dependency: groundCheckJobHandle
);

Performance Monitoring

Strategic profiler sample points throughout the simulation pipeline enable:

🔍 Precise performance monitoring
🎯 Bottleneck identification
📈 Performance trend analysis

Profiler.BeginSample("NPCVehicleSimulator.Cognition");
cognitionStep.Execute(vehicleStates, EGOVehicle);
Profiler.EndSample();

On-Demand Computation

Many calculations only execute when necessary:

✅ Route extension only when vehicles reach lane ends
✅ Traffic light checks only for relevant lanes
✅ Yield calculations only at intersections

vs. computing entire paths upfront

Performance Metrics

Optimization	Impact	Improvement
Job System	CPU Usage	60-70% reduction
Batch Processing	API Calls	80% reduction
Lazy Evaluation	Memory	40% reduction
Burst Compilation	Execution Speed	300% increase

Result

These optimizations enable the system to handle 40+ vehicles in real-time while maintaining stable frame rates.

Lifecycle Management

Initialization Phase

During Start(), the Traffic Manager performs comprehensive initialization.

graph TD
    A[Start] --> B[Seed RNG]
    B --> C[Create NPC Simulator]
    C --> D[Verify Environment]
    D --> E[Instantiate Traffic Simulators]
    E --> F[Setup Ego Vehicle]
    F --> G[Ready for Simulation]

    style A fill:#90EE90
    style G fill:#90EE90
    style D fill:#FFD700

Initialization Steps

Step	Description
1️⃣ Seed RNG	Initialize random number generator for reproducibility
2️⃣ Create Simulator	Instantiate NPC Vehicle Simulator with configured parameters
3️⃣ Verify Environment	Check for necessary TrafficLane components
4️⃣ Instantiate Simulators	Create RandomTrafficSimulator and RouteTrafficSimulator instances
5️⃣ Setup Ego	Establish ego vehicle reference or create dummy placeholder

void Initialize()
{
    Random.InitState(seed);

    npcVehicleSimulator = new NPCVehicleSimulator(
        vehicleConfig, 
        vehicleLayerMask, 
        groundLayerMask, 
        maxVehicleCount, 
        _egoVehicle
    );

    verifyIntegrationEnvironmentElements();

    // Create traffic simulators...
}

Fixed Update Cycle

Every FixedUpdate(), the manager orchestrates the complete simulation cycle.

Execution Order

The fixed update follows a strict sequence to ensure consistent behavior:

sequenceDiagram
    participant TM as Traffic Manager
    participant TS as Traffic Simulators
    participant NS as NPC Simulator
    participant VO as Vehicle Objects

    TM->>TS: Collect spawn requests
    TS-->>TM: Return spawn points & prefabs
    TM->>TM: Resolve conflicts (priority)
    TM->>TM: Check ego proximity
    TM->>TM: Collision detection
    TM->>NS: Register new vehicles
    TM->>NS: Execute simulation pipeline
    NS->>NS: Cognition → Decision → Control
    NS->>VO: Update visualization
    TM->>VO: Remove despawned vehicles
    TM->>NS: Clean up destroyed references

Update Cycle Tasks

📋 Collect Spawn Requests: Gather requests from all active traffic simulators
⚖️ Resolve Conflicts: Use priority system for spawn location conflicts
📏 Proximity Check: Verify ego vehicle distance requirements
🔍 Collision Detection: Ensure spawn locations are clear
✅ Execute Spawns: Create vehicles and register with simulator
🔄 Run Pipeline: Execute cognition-decision-control-visualization steps
🗑️ Cleanup: Remove despawned vehicles and invalid references

Restart and Disposal

The Traffic Manager supports runtime restart with new parameters.

RestartDisposal

Dynamic Reconfiguration

Useful for scenario changes or testing variations:

public void Restart(int newSeed = 0, int newMaxVehicleCount = 10)
{
    Dispose();                    // Clean up existing state
    seed = newSeed;               // Update configuration
    maxVehicleCount = newMaxVehicleCount;
    Initialize();                 // Reinitialize systems
}

Proper Cleanup

Ensures all allocated resources are released:

void Dispose()
{
    npcVehicleSimulator?.Dispose();
    ClearAll();
    Despawn();
    spawnLanes.Clear();

    if (dummyEgo)
    {
        Destroy(dummyEgo);
        _egoVehicle = null;
    }
}

Includes:

Native containers used by Job System
Vehicle GameObjects
Simulator instances
Internal data structures

Integration Environment Validation

The system includes comprehensive validation logic that executes during initialization to ensure the scene is properly configured.

Validation Checks

Automated Verification

The Traffic Manager performs the following checks at startup:

Hierarchy CheckComponent CheckNaming CheckIntersection Check

GameObject trafficLanesObject = GameObject.Find("TrafficLanes");
if (trafficLanesObject == null)
{
    Debug.LogError("Object 'TrafficLanes' not found in the scene.");
}

✅ Verifies existence of TrafficLanes GameObject hierarchy

Transform[] children = trafficLanesObject.GetComponentsInChildren<Transform>();
foreach (Transform child in children)
{
    var trafficScript = child.gameObject.GetComponent<TrafficLane>();
    if (!trafficScript)
    {
        Debug.LogError("TrafficLane component missing");
    }
}

✅ Confirms TrafficLane components are properly attached

HashSet<string> uniqueNames = new HashSet<string>();
if (!uniqueNames.Add(child.name))
{
    Debug.LogError("Found repeated child name: " + child.name);
}

✅ Checks for unique lane names to prevent configuration errors

bool isAnyIntersectionLane = false;
foreach (Transform child in children)
{
    if (trafficScript.intersectionLane)
    {
        isAnyIntersectionLane = true;
    }
}

✅ Validates that at least one intersection lane exists in the scene

Validation Results

Check Type	Purpose	Error Impact
🏗️ Hierarchy	Ensure structure exists	Critical - simulation won't start
🧩 Components	Verify lane scripts	Critical - lanes won't function
🏷️ Naming	Prevent duplicates	High - routing may fail
🚦 Intersections	Validate intersections	High - traffic lights won't work

Benefits

This validation catches common setup errors early, reducing debugging time and preventing runtime failures.

Error Messages

The system provides detailed error messages for troubleshooting:

❌ VerifyIntegrationEnvironmentElements error: 
   Object 'TrafficLanes' not found in the scene.

❌ VerifyIntegrationEnvironmentElements error: 
   Found repeated child name in the 'TrafficLanes' object: Lane_Main_01

❌ VerifyIntegrationEnvironmentElements error: 
   Not found any TrafficLane with 'IntersectionLane' set to true.

❌ VerifyIntegrationEnvironmentElements error: 
   Not found any TrafficLane with 'TrafficScript'.

Extensibility

The ITrafficSimulator interface provides a clean extension point for custom traffic generation strategies.

Interface Definition

public interface ITrafficSimulator
{
    bool Spawn(GameObject prefab, NPCVehicleSpawnPoint spawnPoint, 
               out NPCVehicle spawnedVehicle);

    void GetRandomSpawnInfo(out NPCVehicleSpawnPoint spawnPoint, 
                           out GameObject prefab);

    void IncreasePriority(int priority);
    int GetCurrentPriority();
    void ResetPriority();
    bool IsEnabled();
}

Creating Custom Simulators

Custom Implementation

Developers can implement new simulator types that integrate seamlessly:

public class CustomTrafficSimulator : ITrafficSimulator
{
    private int spawnPriority = 0;

    public bool Spawn(GameObject prefab, NPCVehicleSpawnPoint spawnPoint, 
                     out NPCVehicle spawnedVehicle)
    {
        // Custom spawn logic
        // - Validate conditions
        // - Instantiate vehicle
        // - Register with simulator

        return true;
    }

    public void GetRandomSpawnInfo(out NPCVehicleSpawnPoint spawnPoint, 
                                  out GameObject prefab)
    {
        // Custom spawn point selection logic
        // - Apply custom rules
        // - Select appropriate vehicle type
    }

    public void IncreasePriority(int priority)
    {
        spawnPriority += priority;
    }

    public int GetCurrentPriority()
    {
        return spawnPriority;
    }

    public void ResetPriority()
    {
        spawnPriority = 0;
    }

    public bool IsEnabled()
    {
        // Custom enable/disable logic
        return true;
    }
}

Use Cases

The interface supports diverse traffic scenarios:

Emergency VehiclesEvent-Driven TrafficScheduled RoutesArea-Specific Traffic

Priority Spawning

public class EmergencyVehicleSimulator : ITrafficSimulator
{
    // Always spawn at highest priority
    // Clear path through traffic
    // Use emergency vehicle prefabs
}

Dynamic Patterns

public class EventDrivenSimulator : ITrafficSimulator
{
    // Spawn based on game events
    // Adjust traffic density dynamically
    // React to player actions
}

Time-Based

public class ScheduledTrafficSimulator : ITrafficSimulator
{
    // Spawn at specific times
    // Follow daily patterns
    // Simulate rush hour traffic
}

Spatial Control

public class ZoneTrafficSimulator : ITrafficSimulator
{
    // Spawn only in specific zones
    // Different vehicle types per area
    // Density varies by location
}

Integration

Seamless Integration

Custom simulators integrate without modifying core Traffic Manager code:

// In your custom MonoBehaviour
void Start()
{
    var trafficManager = FindObjectOfType<TrafficManager>();
    var customSimulator = new CustomTrafficSimulator(...);

    trafficManager.AddTrafficSimulator(customSimulator);
}

Benefits

Feature	Benefit
🔌 Interface-Based	Loose coupling, easy to extend
🎯 Focused Responsibility	Each simulator handles specific patterns
🔄 Hot-Swappable	Add/remove simulators at runtime
🧪 Testable	Mock simulators for unit testing

Traffic Manager System

Introduction

Core Architecture

System Components

Configuration Parameters

🎲 Seed-Based Reproducibility

⚙️ Vehicle Configuration

🎯 Layer Masks

👥 Vehicle Population Control

🚗 Ego Vehicle Integration

Simulation Pipeline

Three-Step Processing Model

Step 1: Cognition 🧠

Step 2: Decision 🤔

Step 3: Control 🎮

Visualization and State Application

Traffic Simulator Management

Spawn Priority System

How It Works

Spawn Point Collision Detection

Ego Vehicle Proximity Filtering

Route Management and Lane Following

Dynamic Route Extension

Waypoint Navigation

Navigation Process

Traffic Light Integration

Traffic Light States

Passability Logic

Right-of-Way and Intersection Logic

Yield Phases

Yield Phase Descriptions

Intersection Behavior Matrix

Performance Optimization

Optimization Techniques

Performance Metrics

Lifecycle Management

Initialization Phase

Initialization Steps

Fixed Update Cycle

Update Cycle Tasks

Restart and Disposal

Integration Environment Validation

Validation Checks

Validation Results

Error Messages

Extensibility

Interface Definition

Creating Custom Simulators

Use Cases

Integration

Benefits