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📄 MAP – Project Statement

The MAP program is responsible for handling location-based services, including routing, traffic estimation, energy consumption, and cost calculations. It will be developed under the map-hub repository, following the same microservice architecture as Snapp.

Its outputs will be used by other programs (Snapp for ride pricing and Food for delivery routes).

🎯 Core Responsibilities of MAP

  1. Shortest Route Calculation → Given origin and destination, return the best route.

  2. Traffic Modeling → Estimate traffic conditions dynamically based on usage data (number of active vehicles using Snapp/Food).

  3. Energy Consumption Estimation → Predict energy/fuel usage considering distance, slope, and traffic.

  4. ETA & Pricing Support → Provide estimated travel time and support Snapp in fare calculation.

🏗 Phases of Development

Phase 1 – MVP (Minimum Viable Product)

Goal: Deliver a simple but functional version quickly.

  1. Basic Routing

    • Given start & end coordinates, return a simple path.

    • For MVP, use a simplified graph representation (nodes = intersections, edges = roads).

    • Return distance and estimated time (using average fixed speed).

  2. Mock Energy Calculation

    • Assume a fixed consumption rate per km.

    • Return approximate fuel/energy usage.

  3. Basic API Endpoints

    • POST /route → Input: origin, destination → Output: route (list of points), distance, ETA, energy.

✅ At the end of Phase 1, Snapp can request a route and pricing support with standard but mocked results.

Phase 2 – Traffic Simulation

Goal: Make routing more realistic.

  1. Traffic Model

    • Collect the number of active vehicles from Snapp (via API or message broker).

    • Define traffic density rules (e.g., >100 vehicles in area = slower speed).

  2. Dynamic ETA

    • Adjust travel time according to traffic.

    • Update routes with slow/medium/heavy traffic categories.

  3. API Update

    • Return ETA and adjusted route cost based on live traffic.

Phase 3 – Advanced Energy & Cost Estimation

Goal: Improve realism of energy/fuel calculation.

  1. Slope-aware Calculation

    • Add elevation data to routes (can be mocked for MVP).

    • Energy consumption increases on uphill slopes, decreases on downhill.

  2. Traffic-aware Energy Use

    • Higher energy consumption in heavy traffic (idling, stop-go).

  3. Vehicle Type Profiles

    • Different models for car, motorcycle, cargo van.

    • Each has different base consumption rates.

Phase 4 – Optimized Routing & Algorithms

Goal: Deliver production-quality map features.

  1. Shortest vs Fastest Route

    • Allow user to choose between minimizing distance or time.

    • Implement algorithms like Dijkstra / A Search*.

  2. Alternative Routes

    • Provide multiple possible routes with trade-offs (shorter but more traffic, longer but faster).

  3. Scalability

    • Cache frequently requested routes.

    • Optimize graph storage and queries.

Phase 5 – Integration & Expansion

Goal: Complete professional integration with the rest of the ecosystem.

  1. Integration with Snapp

    • Provide real-time routes, ETA, and pricing support.

    • Feed Snapp traffic data to improve matching drivers ↔ passengers.

  2. Integration with Food

    • Provide delivery optimization for multiple stops (restaurant → multiple customers).

  3. Analytics & Reports

    • Store historical traffic data.

    • Generate insights like busiest areas, peak hours.

📌 Priorities

  • Phase 1 (MVP) must be implemented first → basic route, ETA, and energy.
  • Phase 2–3 introduce realism (traffic + energy models).
  • Phase 4–5 add professional-level features for optimization and integration.