We wanted to build an application that provides a holistic travel experience for our users. Car-pooling remains a much unexplored area in path-finding algorithms due to the sheer complexity of the factors involved and we were keen to tackle this challenge head on.
What it does
pooL allows users to connect with their friends or colleagues, optimising travel to events by evaluating multiple options including public transport and car-pooling. Our easy to use interface makes sure you get from A to B in the most time efficient and cost effective way, whilst minimising your carbon footprint.
If we all opted to carpool just one day a week, the traffic in our major cities would be reduced by over 20%, cutting emissions in half and saving you money on fuel. pooL takes the hassle out of car-pooling for everyone.
We believe that sharing a journey together adds a whole new dimension to the way we interact with our friends, and our core philosophy is to help users spend more quality time with the people they care about.
How we built it
We formulated the problem mathematically, applying a SAT solver to optimise for a number of parameters. We were able to build a multimodal transportation network, combining various means of travel to achieve an optimal overall route.
We developed a python back end, wrangling data from a number of disparate APIs, and a front end Android application.
Challenges we ran into
The nature of our algorithm was highly complex from a mathematical perspective, and a key challenge was formalising this into something tractable in Python.
Accomplishments that we're proud of
Building a fully-functioning application in a (very) short amount of time.
What we learned
What's next for pooL
We're going to 'pooL' data from additional sources to modify our cost function to account for vehicle specific features, further optimising the travel experience.