Bilkent University Senior Design Project 2025

E-Way

Predictive Routing: Know the Availability Before You Arrive.

AI-powered charging station occupancy prediction for electric vehicles in Turkiye

Why E-Way?

Aggregation

All Charging Networks. One Single Map.

No more switching between apps. E-Way aggregates all charging stations from EPDK EV Charging Network, giving you a complete view of every available station across Turkiye.

Grab a Coffee While Charging: Nearby Amenities Included.

E-Way Hub
Cafe
Restaurant
Mall
Battery68%
Range~ 312 km
Tesla Model 3
1 charge stop
Personalization

Smart Routes Tailored to Your Vehicle and Battery Level.

E-Way considers your specific EV model, current battery percentage, and driving preferences to generate the most efficient route with optimal charging stops.

Enjoy the Drive. Let E-Way Plan the Stops.

AI Prediction

Will It Be Full? Know Before You Go.

Our AI models analyze historical data and real-time patterns to predict station occupancy at your exact arrival time. No more surprises, no more waiting.

No More Queues: See Station Status at Your Exact ETA.

Predicted Occupancy

Today

LIVE
10
11
12
13
YOU
14
15
16

At your ETA · 14:00

Available · Short wait

35%

Busy

Smart Routing

Choose Your Way

Three intelligent routing modes designed for every kind of journey

Get There Faster. Smart Stops Included.

Optimized for minimum travel time with strategic high-power charging stops along the most direct path.

Start
Destination
2h 15m
Travel Time
245 km
Distance
1
Charging Stops
Click a mode above to see the route update in real time

About the Project

What is E-Way?

E-Way is an intelligent route planning system designed to address range anxiety and optimize travel efficiency for Electric Vehicle users in Türkiye. The system predicts charging station occupancy using AI models and generates smart routes based on these predictions, integrating real-time data from EPDK EV Charging Network.

Technologies Used

FlutterFastAPIMongoDBPythonGoogle Maps APIMachine LearningREST APIMongoDB Atlas

Project Goals

  • 1
    Predict charging station occupancy using AI models trained on historical data from EPDK
  • 2
    Generate smart routes that avoid congested stations and minimize total travel time
  • 3
    Provide detailed station information including socket types, power levels, and operator details
  • 4
    Recommend nearby amenities such as cafés, markets, and rest zones based on user preferences
  • 5
    Reduce range anxiety for EV drivers through intelligent, data-driven planning
  • 6
    Support cross-platform availability through Flutter mobile application (Android & iOS)
Documentation

Project Documents

Explore the full set of reports and documentation produced throughout the E-Way senior design project.

Project Specification

Initial project scope, objectives, and high-level requirements.

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Analysis & Requirements

Detailed functional and non-functional requirements analysis.

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Detailed Design Report

System architecture, database design, and technical specifications.

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Final Report

Complete project outcomes, evaluations, and final deliverables.

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User Manual

Step-by-step guide on how to use the E-Way mobile application.

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Our Team

The dedicated team behind E-Way

Project Advisors

SÖÖ

Salih Özgür Öğüz

Project Supervisor

MB

Mert Bıçakçı

Course Instructor

Development Team

UY

Utku Yüksel

Student ID: 22103511

Developer
FÖ

Furkan Özek

Student ID: 22103680

Developer
HVT

Halis Vefa Türkyılmaz

Student ID: 22102898

Developer
AÜ

Aziz Üzümcü

Student ID: 22102800

Developer