Inspiration:
Transportation is a major contributor to CO₂ emissions, and route choices can meaningfully change a trip’s footprint. We wanted a tool that makes the greener choice obvious—simple enough for everyday drivers, yet accurate and transparent about distance, time, and estimated emissions.
What it does:
GreenRoute lets users enter a start and destination, then fetches at least two driving routes via the OpenRouteService Directions API. For each route, it calculates:
Total distance
Estimated travel time
Estimated CO₂ emissions (≈ 0.192 kg CO₂/km for a gasoline car)
It visualizes all routes on an interactive Leaflet.js map, color-codes them (green = lowest emissions, yellow = moderate, red = highest), and highlights the most eco-friendly option. A summary panel/table lists the key metrics for quick comparison.
How we built it:
Backend: Production-ready Flask app (app.py) with a clean service layer to call OpenRouteService, parse alternatives, and compute emissions. Secrets handled with python-dotenv and environment variables.
Frontend: templates/index.html + static/style.css + Leaflet.js for map rendering, route polylines, and a responsive metrics panel.
Routing & Data: OpenRouteService Directions API (driving-car profile) requested with alternatives=true to obtain multiple candidate routes. Emissions computed as distance_km * 0.192.
Quality: Input validation, error handling for API failures/rate limits, clear comments, and a small utility module for unit conversion and formatting.
Challenges we ran into:
Consistent alternatives: Ensuring the API reliably returned ≥2 distinct routes across regions required careful parameter tuning and fallbacks.
Polyline decoding & styling: Rendering multiple polylines with distinct colors/legends while keeping the UI uncluttered.
Unit handling & rounding: Keeping distance/time consistent (meters → km, seconds → hh:mm) and rounding without hiding meaningful differences.
Accomplishments that we’re proud of
A clean, minimal UX where the greener route is unmistakably green (literally).
Solid backend structure with environment-based configuration and graceful error paths.
A compact, readable codebase that’s easy to extend (e.g., adding vehicle types or traffic).
What we learned:
Practical tradeoffs between “fastest” vs “lowest-emissions” routing and how to present those differences clearly.
Working with third-party routing APIs (rate limits, geometry formats) and mapping libraries in a production-style Flask app.
Why small UX choices (legends, badges, ordering) matter for sustainability nudges.
What’s next for GreenRoute:
Vehicle profiles: Add diesel/hybrid/EV factors and custom g/km rates.
Traffic-aware estimates: Incorporate live traffic where available.
Waypoints & constraints: Avoid tolls/hills, prefer bike-lanes or low-emission zones.
Share & compare: One-click share of the greener route and weekly CO₂ savings reports.
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