Mobile Responsive Transport Networking Web Application

, Mobile Responsive Transport Networking Web Application

Complex and functionality diverse web platform developed as an online cab aggregator to facilitate the daily commute in United Kingdom

Product Brief

Product is a cutting edge transportation networking web application developed for the United Kingdom-based client. It enables operators, minicab companies, executive private hire companies, and minibus owners and travel companies to meet passenger request for transport services and is one of the most cost-effective media for commuters to fulfill their transportation requirements. The scope of this product included the development of mobile responsive web application, testing, infrastructure management, and post-deployment support.


The client is a UK based company who wanted to provide a unique medium to expedite the daily commute in the country. Initially, the transportation scope of the product was limited to rigid commute between airports, rail stations, shopping centers, and other well-known tourist destinations but in a later phase, the scope was extended to be a comprehensive transportation network application.

Our Solution

The project was kick-started with market research and competitor analysis; based on the finalized modules and features VSH decided to leverage its Marketplace platform for the development of this product and employ its inbuilt modules to reduce the overall development costs and minimize the time to market.


Development of the Product has three important components:

  • End User module to facilitate the cab booking for commuters
  • Partner Module to comprehensively manage activities at the cab operator’s/driver’s end
  • Admin Panel to manage the complete activities of both the user and partner modules

Machine Learning

Google map service was integrated in the application and it was pivotal in the selection of the routes and providing directions to reach the commuters’ destination. But to improve the overall user experience and take the product offerings to next level, machine learning algorithms were developed for route selection, route calculation, and route optimization which were based on the number of variable factors like real-time traffic, driver’s current location, their preferred coverage areas and most suitable driver to complete a particular ride.

Pricing Strategy

Based on the average of the rates proposed by the partners, an algorithm was developed to calculate the mutually profitable rate for the users as well as for the partners. In the later phase, the strategy was fine-tuned to remove the anomalies arising from unusually high and low prices proposed by the partners.

Booking Bank

A unique module was developed to display all the unclaimed bookings which were initially offered to the nearest or suitable drivers selected by the algorithm. This feature allowed drivers from other locations to claim the ride which was otherwise going to be cancelled; making the engagement more beneficial for users as well as partners.

Payment Processing

Integrated with payment API’s to complete the two way payment processing i.e. for user and for partners. Automatic backend system was developed for this application to: refund the amount for cancelled rides, automatic invoice generation, settlement of the partner account after every seven days, calculation of penalties and the government taxes and transfer of the money directly to partner accounts.


Considering the various infrastructure management factors, Product was deployed on the AWS environment. Some of the characteristics of this environment include

Auto scalability

Auto scaling configuration to manage the server load with respect to surge in the users

Capacity Planning

Scale up and scale down the servers based on the requirement patterns to optimize the infrastructure costs

Performance Monitoring

Performance monitoring is a part of VSH’s deployment methodology. Each and every build deployment is audited for any
spikes in the usage of RAM, Database or CPU

Database Auto scaling

VSH leveraged AWS Aurora for auto scaling of database as per the usage requirement without need of any manual interference

Technology Architecture


Technology Stack

, Mobile Responsive Transport Networking Web Application
, Mobile Responsive Transport Networking Web Application
, Mobile Responsive Transport Networking Web Application
, Mobile Responsive Transport Networking Web Application
, Mobile Responsive Transport Networking Web Application
, Mobile Responsive Transport Networking Web Application



Team Composition

2 Web Developers

Account Owner

Senior Web Developer

Test Engineer

DevOps Engineer


Disconnected user experience was one of the early challenge faced by the management. To overcome the same multiple UX iterations were done and Google API’s were integrated to show the relevant auto fills, nearest location suggestions along with the ability to fine-tune the search functionality with the help of integrated map.

Partner/driver on-boarding was challenging and the involved technicalities were bothersome to some of the partners and drivers. Process simplification was done by developing a standard profile forms and by designing easily understandable training collaterals for partners.

Price for a particular ride was calculated with the help of an average price algorithm, but in case of unusual low and high prices proposed by the partners it used to show aberrancy in the average ride price leading to erroneous calculations. The issue was subdued by developing a separate algorithm to eliminate the outlier values.

AdWords cost optimization was a challenge during the marketing phase and absence of relevant keywords on site was the reason behind it. In order to include these keywords and names of popular tourists’ locations and places; a system was developed to create dynamic web content.


In case of aggregator portals serving large number of users, verification of various involved entities is crucial.

Development of mutually beneficial pricing strategy, then analysing and overhauling the strategy by eliminating the anomalies was insightful

Project Results


20% increase the active users after the marketing activities


10,000 partners in the network

Active Users

50,000+ active users

Booked Rides

More than 100,000 rides were booked

Partner onboarding

Improved partner on-boarding by 35% using the standard profile and providing the necessary training to them

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