Full Case Study
How We Built DMU Car Pool
A Smart University Carpooling Platform for Students & Staff
DMU Car Pool – Full Case Study
A Smart University Carpooling Platform for Students & Staff
Table of Contents
- Introduction
- Client Problem
- Proposed Solution
- Project Objectives
- Key Features
- User Roles
- System Architecture
- Data Flow Diagrams (DFD)
- Database Design Overview
- Matching & Fare Algorithm
- UI/UX Design Approach
- Security Features
- Technology Stack
- Challenges Solved
- Results & Business Impact
- Future Enhancements
- Conclusion
1. Introduction
DMU Car Pool is a modern ride-sharing mobile application designed specifically for De Montfort University (DMU) students and staff.
The purpose of the platform is to help users:
- Share rides with others traveling in the same direction
- Reduce fuel costs
- Reduce traffic congestion
- Improve sustainability
- Provide safer transport options for students
- Build a trusted campus commuting network
Unlike taxi apps, DMU Car Pool focuses on carpooling, meaning drivers are everyday users already traveling to campus or nearby destinations.
2. Client Problem
University students face several transport issues:
Daily Challenges:
- High taxi costs
- Expensive fuel prices
- Lack of parking space
- Public transport delays
- Students traveling alone with empty car seats
- Difficulty finding reliable rides late at night
- Traffic congestion near university
Business Need:
The university needed a solution that:
- Encourages shared commuting
- Saves money for students
- Promotes eco-friendly travel
- Uses modern mobile technology
3. Proposed Solution
We designed DMU Car Pool, a mobile platform where:
Drivers Can:
- Publish available trips
- Add number of seats
- Accept ride requests
- Earn fuel contribution money
Passengers Can:
- Search available rides
- Book seats instantly
- Track driver live location
- Split travel costs fairly
4. Project Objectives
- Build secure login system
- Real-time ride booking
- GPS route tracking
- Smart fare calculation
- Driver/passenger dashboards
- In-app notifications
- Review & rating system
- Scalable architecture
5. Key Features
Authentication
- Email Sign Up / Login
- Google Login
- Student verification using university email
- Password reset
Passenger Features
- Search rides
- Select destination
- Request seat
- View driver profile
- Track driver
- Pay contribution
- Ride history
Driver Features
- Post trip
- Set seats available
- View incoming requests
- Accept / Reject passengers
- Navigation support
- Earnings summary
Admin Features
- Manage users
- Verify drivers
- Block suspicious accounts
- View ride analytics
- Manage complaints
6. User Roles
| Role | Permissions |
|---|---|
| Passenger | Search & join rides |
| Driver | Offer rides |
| Admin | Manage system |
7. System Architecture
Mobile App (React Native / Kotlin)
|
v
REST API Backend
(Node.js / Django / Firebase)
|
v
PostgreSQL / Firebase DB
|
v
Google Maps API / Notifications
---
# DFD Level 0 – Context Diagram
```text
+------------------+
| Passenger |
+--------+---------+
|
| Search / Request Ride
v
+-----------------------+
| DMU Car Pool App |
+-----------------------+
^
|
| Trip Offers / Accept Requests
+--------+---------+
| Driver |
+------------------+
^
|
| Monitoring / Reports
+--------+---------+
| Admin |
+------------------+
DFD Level 1 – Ride Booking Process
Passenger
|
| Search Destination
v
[Search Module]
|
v
[Available Trips DB]
|
v
Matching Rides
|
v
Passenger Sends Request
|
v
[Ride Request Module]
|
v
Driver Receives Request
|
+----Accept----> Booking Confirmed
|
+----Reject----> Passenger Notified
DFD Level 2 – Fare Calculation
Input:
- Total Distance
- Fuel Price
- Vehicle Mileage
- Number of Passengers
|
v
Fuel Cost = Distance / Mileage × Fuel Price
|
v
Total Cost ÷ Passengers
|
v
Passenger Shared Fare
DFD Level 3 – Live Tracking
Driver GPS
|
v
Location API
|
v
Backend Server
|
v
Passenger App Map Screen
9. Database Design Overview
Users Table
- id
- name
- password
- role
- verified
Trips Table
- trip_id
- driver_id
- start_location
- destination
- seats
- departure_time
Ride Requests Table
- request_id
- passenger_id
- trip_id
- status
Payments Table
- payment_id
- amount
- status
Ratings Table
- rating_id
- from_user
- to_user
- stars
10. Matching & Fare Algorithm
Ride Matching Logic
System checks:
- Destination similarity
- Route overlap
- Departure time proximity
- Available seats
Example:
If Driver route:
Leicester City -> DMU Campus
Passenger request:
Narborough Road -> DMU
System suggests this driver.
Smart Fare Calculation
Unlike taxi apps, fare is based on cost sharing, not profit.
Formula:
Fuel Cost = Trip Distance × Fuel Rate
Shared Fare = Fuel Cost ÷ Total Riders
Example:
- Fuel Cost = £8
- 4 Riders
Each Pays:
£2
Much cheaper than Uber.
11. UI/UX Design Approach
Login Page
- Clean university branding
- Yellow + White theme
- Email & password login
- Quick signup
Passenger Dashboard
- Search bar
- Nearby rides
- Book now cards
- Live ride updates
Driver Dashboard
- Today’s trip list
- Requests counter
- Earnings
- Start trip button
12. Security Features
- JWT Authentication
- Encrypted passwords
- Email verification
- Student identity validation
- Ride history logging
- Fraud detection rules
13. Technology Stack
| Layer | Tech |
|---|---|
| Mobile App | React Native / Kotlin |
| Backend | Django / Node.js |
| Database | PostgreSQL / Firebase |
| Maps | Google Maps API |
| Notifications | Firebase Cloud Messaging |
| Hosting | AWS / DigitalOcean |
14. Challenges Solved
Problem: Trust Between Strangers
Solution:
- University email verification
- Ratings system
- Ride history
Problem: High Taxi Prices
Solution:
- Shared fuel pricing model
Problem: No Real-Time Updates
Solution:
- Live trip tracking
- Push notifications
15. Results & Business Impact
Expected Benefits
- 60% lower commute cost
- Reduced parking demand
- Lower carbon emissions
- Faster student commuting
- Stronger campus community
16. Future Enhancements
- AI ride prediction
- Subscription plans
- Women-only rides option
- Emergency SOS button
- Multi-university expansion
- Driver reward points
17. Conclusion
DMU Car Pool successfully transforms daily commuting into a smart, affordable, and eco-friendly shared transport system.
Instead of paying expensive private taxi fares, students split real fuel costs and travel together safely.
The project demonstrates expertise in:
- Mobile app development
- Real-time systems
- Maps integration
- Scalable backend APIs
- Smart business solutions