RideCast

Inspiration

Every college student has used a Ride Sharing at some point in their lives. The issue with Ride Sharing APPs are often the price but the inevitability of using the APP is unavoidable. What if we could help not just students, but everyone to save a little bit of money while also making a more efficient way to compare prices between different Ride Sharing APPs.

What it does

RideCast is a downloadable Google Maps plug-in that pulls the APIs of Uber, Lyft, and Curb's APIs to utilize their database to analyze and create trends that can be implemented into predicting the future prices of car rides which also takes into account distance, weather and time. Another perk of RideCast is that it shows the comparisons in prices among the large RideSharing APPs, and will automatically show the cheapest price on top.

Challenges we ran into

One of the main challenges was that Lyft had a very secure API and must go through a long process to be approved to view the Data they have. Due to this we recorded data by hand every 30 minutes to check price changes over 16 hours. In the future once we are fully approved by Lyft it will be a much easier process to predict future trends. Another challenge that we faced was that it took a long time to decide on an idea. Our original idea on tracking heat and building a more heat resistant areas in the Cambridge area was not as viable as we once thought.

Accomplishments that we're proud of

As a group that most likely has less experience in coding compared to others, we spent most of the weekend attending workshops and watching YouTube videos in order to learn the coding we wanted to utilize. We are also very proud to have been able to become great friends over the weekend, it isn't often that people can become so close during such a small amount of time and, especially being able to work together without major arguments. We are all so glad to have met each other and hope that even after HackHarvard we can still stay in touch.

What we learned

A better world is about taking action and trying to implement it. The importance of consistency, persistence, and trusting in your vision are key abilities to bringing a better ideas into real life. Furthermore, we learned about how to proceed when we are facing bottlenecks. How to convince and encourage each other to make it through the goal. Tech wise, some of us has never previously used Figma, and never trained models. We are picking up a lot of new information and skills that will be invaluable to our project, and future lives.

What's next for RideCast

To create another model that predicts the probability of getting a driver at a certain time and location. Imagine you are in the middle of Michigan, you have a 5AM shift and you need a ride at 4AM. You reserved an Uber but still there was no driver; or you have an Uber, but the reserved price is like 10 plus dollars than you directly call it at the moment. We are also going to let the Google Maps Plug-In capable of requesting rides with APIs and without redirecting the users into the apps. It is also foreseeable to add features like directly requesting a ride by least wait time, price, comfort, etc, across all the platforms.