The market for mobile-based ride services such as Lyft and Uber is growing rapidly, especially in urban areas. When drivers of these services drop off a passenger, they often have to decide where to go next, taking into account peak prices, fuel cost, and travelling time. Suboptimal decisions can lead to increase in urban traffic and greenhouse gas emissions. The aim of this project is to develop a fast and effective between-ride routing algorithm to advise drivers on what to do between rides. Afterwards, we will implement the algorithm to test how well it works in a real-life situation and make any corresponding adjustments if necessary. Ultimately, we hope that the final product will be a significant improvement over the current algorithms used by transportation services.

I am participating in SuperUROP as it allows me to apply what I have learnt from classes to a more practical setting. I am interested in algorithms and optimization problems, and I believe the material from the algorithms classes I have taken (6.006, 6.046, 6.854) will be relevant to the project as well. As a double major in computer science and mathematics, this project is also a good fit for me because it requires knowledge from both disciplines.