title: "Route Authority" subtitle: "Airline Operations Command Simulator — Dispatcher Planning & Network Control Training" date: "2026-05-28" category: "Aviation Operations Training" tech: "SvelteKit, SVG Route Mapping, Synthetic Weather Engine, Cross-Module Consequence Propagation"

Important

This project is "Work in progress". Not complete yet.

Route Authority

Airline Operations Command Simulator — Dispatcher Planning & Network Control Training

Summary

"Route Authority" is a comprehensive, dispatcher-centric airline operations command simulator designed to mirror the intense environment of an Operations Control Centre (OCC). Aligning directly with the GCAA Flight Dispatcher Licence Programme, the training platform requires users to proactively manage pre-flight planning, live synthetic weather disruptions, dynamic fuel modeling, and cross-departmental coordination across a unified six-module interface. By employing a robust consequence propagation engine where every decision triggers cascading effects across fuel margins, crew legality, and ramp readiness, the simulator effectively trains operations personnel in complex, network-level decision-making under uncertainty.

▶ Launch Simulator Opens in new tab — full-width operations view

What This Is

Route Authority is a dispatcher-centric airline operations command simulator built as a scenario-driven training platform. Unlike cockpit emergency trainers or cabin procedure games, this system places the trainee inside an Operations Control Centre (OCC) workstation where pre-flight planning, weather analysis, fuel calculation, crew legality, ramp coordination, and live flight following must be managed simultaneously under disruption pressure.

The project is specifically scoped to Air Arabia’s actual training ecosystem: T3 Aviation Academy runs the GCAA Flight Dispatcher Licence Programme with 90 days of hands-on training at Air Arabia’s Operations Control Centre. This simulator models that exact environment.

How to Use

Scenario Deep Dive: G9174 SHJ → IST

Aircraft: A320-214 (A6-ANA) | Route: 1542nm via GUTEB-W41-PABER | Block: 4h15m | Cruise: FL360

Pre-Flight State:

Origin (SHJ): 38°C, 14kt wind, CAVOK
Destination (IST): Rain, 22G35kt crosswind, 5000m visibility, TEMPO deterioration to 3000m
MEL: SATCOM voice inop, RMP #3 audio inop
Fuel: 9200kg onboard, 8960kg required, 240kg margin
Crew: PIC 8740h (fatigue concern), FO 3120h (no PIC upgrade), both CAT II qualified

Disruption Sequence:

14:15 — SIGMET for embedded thunderstorms on route; deviation adds 45nm and burns margin
14:22 — Destination runway 34L closed during arrival window; forces alternate runway with crosswind at FO limit
14:35 — ZFW bump (+640kg) from extra pax; fuel goes negative; offload cargo or reduce contingency
14:50 — PIC reports fatigue; duty time for return sector is critically tight
15:05 — Flow control delay +40min; holding fuel required; weather window closing
15:20 — De-icing required unplanned; 22min queue; slot at risk
15:45 — Return sector crew sick at IST; no PIC available; network protection required
16:10 — TAF amended: visibility drops below CAT I; CAT II required; MEL 22-10-01A creates legal conflict

Each event has 2–3 player options. Each option triggers consequences across all 6 modules. The “correct” answer is rarely obvious — trade-offs are intentionally painful.

Debrief Framework

After completion, the trainee receives scores across four dimensions with per-criterion breakdown:

Safety (40%): Weather minima respected? MEL compatibility verified? Fuel reserves protected? Crew duty limits observed?
Efficiency (25%): Minimal fuel waste? On-time performance protected? Network rotations preserved? Costs minimized?
Compliance (20%): Dispatch release complete? NOTAMs addressed? ATC coordination proper? Documentation signed?
Judgment (15%): Proactive hazard identification? PIC communication quality? Alternative evaluation depth? Consequence awareness?

The scoring is transparent (criteria visible, not black-box) so trainees learn from structure, not just outcome.

Technical Architecture

Frontend Engine: SvelteKit with route-group full-width layout override (+layout.svelte removes the site max-width container for this route only, preserving navigation and headers while allowing the simulator to use the full viewport). [cite:1]

Design System: Custom CSS variable stack — Soft Sand & Teal palette (#F5F0E8 background, #0F766E primary accent, #B45309 amber alert, #BE123C red for critical). No gradients, no shadows as decoration, no dark mode. Every pixel is functional. [cite:11]

Six-Module Layout:

Command Layer (top): Flight overview strip, readiness gauge (0–100%), live compliance checklist (10 items), and rolling alert rail
Decision Layer (center, 3 panels): Left panel shows module context (flights, weather, crew, ramp, or SOC data); center panel presents the active disruption event with decision options; right panel shows module-specific metrics (fuel matrix, alternate airports, duty-time bars, cargo load)
Narrative Layer (bottom): Captain / FO / ATC / Dispatch message thread with role-colored avatars, plus the Consequence Chain panel showing cross-module impact arrows [web:27][web:34]

Consequence Propagation Engine: Every decision triggers a cascade. The JSON scenario defines 8 disruption events, each with consequences mapped to all 6 modules. The engine appends these to a reactive array that feeds both the alert rail and the consequence panel. No random generation — all impacts are scenario-authored for training consistency. Total cross-module links: 48 directional consequences. [cite:1]

Synthetic Weather Engine: Real METAR/TAF syntax (not pseudo-weather). The scenario includes origin, destination, en-route SIGMET, and three alternates with live minima evaluation. The trainee must decode raw aviation weather and recognize when conditions drop below CAT I or CAT II thresholds. [web:41]

Fuel & Mass Modeling: Complete regulatory fuel plan (taxi, trip, contingency 5%, alternate, final reserve, extra) with live recalculation when ZFW changes. Margin visualization turns red when deficit occurs. [web:38]

Crew Duty Logic: Flight deck and cabin rosters with accumulated duty hours, max-remaining bars, and status badges (ready / rest / illegal). Duty-time visualization uses percentage bars that turn amber when approaching limits. [web:52]

MEL Regulatory Trap: Event 8 forces the trainee to discover that MEL 22-10-01A (SATCOM voice inoperative) may invalidate CAT II operations in low visibility — a genuine regulatory puzzle requiring OM-B consultation. This is not trivia; it is a real airworthiness-operations interface problem. [web:33]

Compliance Tracker: 10-item checklist mirroring GCAA dispatcher licence requirements. Items toggle dynamically based on scenario events. The readiness score is computed as (met / total) × 100 and drives the top gauge. [web:60]

Why This Is Different

Existing Projects	Route Authority
Cockpit emergencies, button presses	Pre-flight planning, resource negotiation
Game board, cards, timers	Multi-panel dashboard, data density, live chat
Post-incident debrief	Pre-flight go/no-go judgment with legal consequences
Single-role (pilot, crew, ground)	Dispatcher role coordinating across 6 departments
Reactive decision under time pressure	Proactive planning with cascading uncertainty

Zero visual resemblance to prior work. No shared components, colors, layouts, or interaction models. [cite:1]

AI Demonstration

The project demonstrates three AI-relevant competencies:

Natural Language Hazard Extraction: Raw METAR/TAF strings are parsed into decoded weather cards (wind, visibility, ceiling, temperature, QNH) without hardcoding every permutation — the decoder handles variable METAR formats using pattern rules.
Consequence Propagation Graph: A decision in one module (weather deviation) automatically updates fuel, crew, dispatch, ramp, and SOC panels through a reactive consequence array. This is a lightweight rule-based expert system demonstrating how AI could later replace the authored rules with learned operational models.
Scoring Rubric Engine: Four weighted dimensions (Safety 40%, Efficiency 25%, Compliance 20%, Judgment 15%) with explicit criteria per dimension. The structure is ready for adaptive scoring — e.g., adjusting weights based on airline KPIs or seasonal priorities.

Use Cases

Dispatcher Licence Training: GCAA Flight Dispatcher Licence Programme — theoretical knowledge reinforcement through synthetic scenarios
Ops Control Centre Familiarization: New hires at Air Arabia or partner airlines experience realistic workstation layout and decision pressure before touching live systems
CRM Adjacent Training: Pilots and crew learn what happens behind the dispatch desk — why certain decisions are made, what constraints the dispatcher faces, how a “simple delay” cascades into network damage
Airline Operations Research: Academic or industry studies on dispatcher workload, decision bias under disruption, and fuel-versus-delay trade-off behavior
Portfolio Demonstration: For AI/ML practitioners seeking airline-adjacent roles, this shows ability to design complex multi-module interfaces, handle dense regulatory data, and build consequence-aware systems [web:57][web:59]

File Architecture

src/lib/components/route-authority/
  RaEngine.svelte          — Main game loop, state manager
  RaTopBar.svelte          — Module tabs, UTC clock, live badge
  RaCommandLayer.svelte    — Flight strip, readiness gauge, alerts
  RaDecisionLayer.svelte   — 3-panel modular workspace
  RaNarrativeLayer.svelte  — Message thread + consequence chain
  HorizontalAccordion.svelte — Side-opening accordion component

src/routes/web-projects/route-authority/
  +page.svelte             — Route entry, imports RaEngine
  +layout.svelte           — Full-width layout override

static/data/css/route-authority/
  route-authority.css      — Complete design system

static/data/json/route-authority/
  scenario-001.json        — SHJ→IST scenario (8 events, 48 consequences)

External References

Air Arabia Academy Flight Dispatcher Licence Programme [web:34]
T3 Aviation Academy CBTA dispatcher training, UAE and GCC [web:37]
Aircraft Dispatcher Competency Model (FAA-aligned framework) [web:38]
SATCE: Simulated ATC Environment standards for flight simulation [web:33]
FL3XX Dispatch Module: timeline, crew, and slot coordination patterns [web:59]
Bytron Skybook: integrated dispatch, weather, and briefing workflow [web:57]
SND FleetCaptain: real-time cross-screen updates and compliance evaluation [web:48]
Weather Decision Making: FAA and airline collaborative mandate [web:41]

Credits & Licensing

All aviation terminology sourced from public ICAO, GCAA, and Eurocontrol documentation. METAR/TAF syntax follows WMO standards. MEL item references are fictional but structurally realistic. No proprietary airline manual content is included. Aircraft specifications reference public A320 type certificate data. [cite:16]

Built for portfolio demonstration of AI-assisted learning architecture and complex operational interface design. Not intended for certified flight dispatch use.

Route authority