What question did this study set out to answer?

The goal is to create a navigation system for informal bus networks that adapts to user needs.

April 13, 2026Open Access

Adaptive Public Transit Navigation System

Key Points

The goal is to create a navigation system for informal bus networks that adapts to user needs.
Models bus routes as continuous polylines with no fixed stops.
Uses a state-based A* algorithm with dynamic penalties for various factors.
Crowdsources real-time user feedback on transit conditions.
Supports offline navigation with a locally stored SQLite graph.
Constructs the graph using Python from KMZ files.
Achieved 100% success and near-optimal routes in benchmarking tests.
Improved retention and route quality through gamification and live metrics.

Abstract

Syrian Public Transit Navigator – Navigation for informal bus networksModels bus routes as continuous polylines with no fixed stops or schedules.Allows boarding/alighting anywhere by snapping users to the nearest route point.Builds a sparse multi‑graph with nodes only at transfer points (intersections and close parallels).Uses state‑based A* with dynamic penalties for walking, transfers, crowding, price, and slowness.Runs routing entirely on the device with a locally stored SQLite graph, supporting offline use.Crowdsources real‑time feedback (price, crowding, slowness) and blends it via confidence‑weighted averages.Backend built with Fastify + PostGIS; graph construction in Python from KMZ files.Achieved 100% success and near‑optimal routes under fixed constraints in benchmarking.Designed for Syrian cities where existing navigation apps fail due to fixed‑stop assumptions.Combines gamification and live metrics to improve retention and route quality. This work was conducted at Arab International University (AIU), Syria. The official website of the university is: https://www.aiu.edu.sy

Adaptive Public Transit Navigation System

Key Points

Abstract

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