Skip to content
← All work

P—09 Case study · Web & apps

Route Optimisation (Google Maps Clone)

Role

Web Developer

Status

completed

Started

Feb 2026

Last activity

Feb 2026

Stack

11 technologies

Overview

A real-time route optimization algorithm integrated into a web-based application that computes the shortest and most efficient paths using live data. The system dynamically processes factors such as distance, travel time, and routing constraints to deliver optimal navigation results. Paired with a user-friendly interface and interactive map features comparable to Google Maps, it enables seamless route visualization, turn-by-turn guidance, and responsive updates to enhance usability and decision-making.

Outcomes

2x

Implementations

650

C++ Lines

Real-time

Routing

OSM

Data Source

Impact

  1. 01Built dual-implementation system: Flask web app (OSMnx/NetworkX) + 650-line from-scratch C++ Dijkstra engine
  2. 02Implemented hand-built data structures: binary min-heap with decrease-key, adjacency-list graph, and QuickSort
  3. 03Engineered real-time hospital POI search with dynamic radius expansion (5km to 10km fallback)
  4. 04Integrated interactive Leaflet maps via Folium with turn-by-turn route visualization and ETA computation

Features

01

Dijkstra Algorithm

Dual implementation: Python (NetworkX library) + 650-line from-scratch C++ with hand-built binary min-heap and adjacency-list graph

02

OSM Integration

Real-world road network data via OSMnx — downloads, parses, and converts OpenStreetMap data into navigable graph structures

03

POI Search Engine

Hospital/landmark search with dynamic radius expansion (5km → 10km fallback) and proximity ranking

04

Hand-Built Data Structures

Binary min-heap with decrease-key operation, adjacency-list graph representation, and QuickSort for path post-processing

05

Flask Web App

Python Flask backend with route computation API, interactive Folium map rendering, and Leaflet.js frontend

06

Turn-by-Turn Navigation

Route visualization with waypoint markers, distance labels, and estimated travel time at each segment

Architecture

Dual-architecture system: (1) Python/Flask web app uses OSMnx to fetch road networks from OpenStreetMap, NetworkX for graph construction and Dijkstra routing, Folium for Leaflet map rendering with turn-by-turn visualization. (2) Standalone C++ engine with hand-built binary min-heap, adjacency-list graph, and Dijkstra implementation. Both compute shortest paths from weighted graphs using edge distance as cost. Hospital POI search uses KD-tree spatial indexing with progressive radius expansion.

Stack

PythonC++JavaScriptFlaskNetworkXOSMnxGeopyFoliumLeaflet.jsHTMLCSS

Development log

  1. · Started

    Emergency routing to the nearest hospital

    Emergency routing project aimed at finding the nearest hospital and computing the fastest route.

Next case study →