Flight Simulator Multiplayer: Sync, Prediction & Bubble Detail

Multiplayer simulation games, especially flight simulators, present unique challenges in data sharing and synchronization. The core problem is efficiently communicating the state of multiple players to each other across a network.

Essential Data for Simulation

For any simulated object, such as an aircraft, certain fundamental data points are crucial:

• Position: X, Y, and Z coordinates (altitude). While cars or trains might primarily need X and Y, aircraft critically require the Z-axis for altitude.
• Attitude: For aircraft, this includes:
  • Roll: Rotation around the longitudinal axis.
  • Pitch: Rotation around the lateral axis (nose up/down).
  • Yaw: Rotation around the vertical axis (nose left/right). These three axes define the aircraft's orientation in 3D space.
• Velocity: This is a vector quantity, indicating speed and direction in X, Y, and Z.

Initially, one might consider sending all these values (X, Y, Z, pitch, roll, yaw) as fast as possible. However, this approach is highly inefficient in network terms.

Network Efficiency and Unreliable Transfers

Multiplayer games typically use Unreliable Datagram Protocol (UDP) for frequent state updates. If a few packets are lost, it's acceptable because new updates are constantly arriving. This is in contrast to reliable protocols like TCP, which guarantee delivery but add overhead.

Sending all data constantly for multiple players (e.g., 20 players) generates an enormous amount of network traffic. To mitigate this, a more sophisticated approach is used:

Interpolation and Prediction

Most of the time, objects move at a constant speed. This allows for prediction:

1. Send Position and Velocity: Instead of just position, send X, Y, Z, and their corresponding velocities (velocity X, velocity Y, velocity Z).
2. Client-Side Prediction: If a client hasn't received an update for a while, it can estimate the object's current position by adding the last known velocity multiplied by the elapsed time to the last known position.
3. Reduced Packet Frequency: Packets only need to be sent when an object deviates significantly from its predicted path (e.g., starting a turn, changing speed).
4. Server-Side Validation: The sending client can perform the same prediction. If its actual position is close enough to its predicted position, it doesn't need to send an update, as other clients can accurately infer its location.

This method significantly reduces network traffic by only sending updates when necessary, such as during maneuvers.

Challenges in Flight Simulators

Flight simulators introduce several unique complexities:

Coordinate Systems and Scale

• Vast Distances: Unlike a racing game confined to a small track, flight simulators cover entire countries or even the world. This requires highly sophisticated coordinate systems.
• Floating-Point Precision: Standard floating-point numbers may not offer sufficient accuracy over such large scales, leading to "jittering" or inaccuracies, especially when objects are close together.
• Double Precision: Often, double-precision mathematics is required for X, Y, and Z coordinates to maintain accuracy across global distances.
• Curvature of the Earth: This must also be accounted for.
• Hybrid Origin Systems: To maintain precision, simulators often use a hybrid system with multiple "origins." For example, a packet might specify an origin (e.g., London) and then provide an offset from that origin, allowing for better local precision.

The "Bubble" Concept (Level of Detail and Relevance)

Given the vast scale, it's impractical and unnecessary to track every detail of every object at all times.

• Limited Visibility: Players only need detailed information about objects within a certain range or "bubble" around them.
• Rendering Choices:
  • Inside the Bubble: Objects within this bubble require accurate position, attitude, and potentially detailed visual rendering.
  • Outside the Bubble: Objects outside the bubble still need to be tracked, but with less detail. For instance, their exact pitch and roll might not be relevant if they are too far away to discern. They might be rendered as simpler models or even just a dot.
• Server-Side Management: Typically, a central server manages these bubbles. It receives full data from all players but only sends relevant, appropriately detailed information to each client based on their bubble.
• Dynamic Detail: As an object moves closer, its level of detail increases (e.g., triangle count for rendering, specific data like landing gear position or navigation lights). When far away, it might just be a dot.
• Real-World Analogy: This mirrors air traffic control, which only provides information about aircraft relevant to a pilot's immediate vicinity, not every aircraft in the sky.

Handling Less Frequent Events

While continuous position and velocity updates are often unreliable (UDP), certain events are critical and less frequent:

• Discrete Actions: Turning on navigation lights, deploying landing gear, or opening a canopy are events that happen once and persist.
• Reliable Delivery: These events are often sent via a more reliable protocol like TCP to ensure they are received, as they cannot be easily inferred from continuous data streams.

Latency and Smoothing

• Timestamps: Packets include timestamps to indicate when the data was sent. Late packets are usually discarded as newer information is already available.
• Lag: Players often experience "lag" when their client's prediction deviates significantly from the actual server state.
• Smooth Transitions: If a client receives an update that places an object far from its predicted position (e.g., after a network dropout), simply "jumping" to the new position looks jarring. Instead, the client will smoothly interpolate the object's movement from its last known position to the new, corrected position over a short period. This can sometimes lead to visual anomalies, like planes appearing to rise out of the ground if their predicted position was significantly off.

Advanced Considerations

• Acceleration Data: For even more accurate prediction, especially during turns, acceleration data (acceleration X, Y, Z) could be sent. However, constant acceleration is rare in real-world flight, making this less effective than it might seem.
• Space Simulators: In space, distances are even vaster. Simulators like Elite Dangerous often use "hyperdrive" jumps between star systems. This effectively shifts the player's "origin" to a new system, simplifying coordinate management within that system. This also addresses the issue of vast empty space where there's nothing to see.
• Update Frequency: The frequency of updates varies dramatically:
  • Dogfights: Updates might be sent every few milliseconds due to rapid maneuvers.
  • Long-Haul Flights: For an airliner maintaining a steady course, updates might only be needed every few minutes.
  • Flight Radar Analogy: Real-world flight tracking services like Flight Radar also use prediction and interpolation, which is why aircraft sometimes appear to jump positions.

Getting Started

For those interested in building a simple simulation, the core principles are:

1. Basic Physics: Start with X, Y, Z positions and velocities.
2. Prediction Formula: new_position = old_position + velocity * delta_time.
3. Iterative Updates: Continuously apply this formula to update positions.

This foundational understanding allows for the development of basic simulation mechanics, which can then be expanded upon with more complex features and network optimizations.