Abstract
Introduction
Route planning algorithms serve as a building block to help transportation networks
including cars, buses, and trains get from one point to another. These algorithms have gone
through rapid development, resulting in advancements that have led to increased safety, reduced
transportation expenses, and overall better planning for businesses.
Using route planning algorithms, third-party delivery companies continue to grow by
generating large amounts of revenue from advertising ordering low-cost food. To increase usage,
these delivery apps have minimized costs for consumers, forming a convenience culture to train
them to expect what they want and when they want it. However, while making it convenient for
consumers, delivery apps charge high commission rates for every order, squeezing restaurants
with high fees. From the perspective of restaurants, these apps are predatory and leave them
without much profit on the order.
In real world contexts, route planning algorithms are seen in various applications,
including autonomous vehicles, and taxis. Most notably, these algorithms are at the core of the
operation of the primary services delivery apps offer, from companies such as DoorDash,
Grubhub, and Uber Eats. The exploration of creating better and new methods of route planning is
directly related to the underlying technologies used by the products of these companies that are
discussed as creating conflicting business models.
Technical Topic: Engineering Route Planning Algorithms in Polar Coordinates
Rigorous research has brought improvements to the functionality of classic route
planning algorithms, but they have yet to be placed and examined in more complex settings. The
objective of my technical research is to adapt existing route planning algorithms to more
complex environments and, potentially, further optimize them. More specifically, I will place
these algorithms in polar coordinates to gain insight as to how they work, which will be done by
building a simulator in the form of a Java applet. The end product will hopefully make the
algorithms more efficient and improve route planning in practice.
STS Topic: Delivery Apps’ Convenient and Destructive Business Models
The goal of my STS research paper is to detail the convenient business model third-party
delivery apps have created for consumers, but the financially destructive business model they
have created for workers and restaurants. Beneath their wonderfully designed route planning
technology, delivery platforms leave restaurants with next to nothing, as reported by multiple
sources. Although delivery platforms have promised a higher demand from customers to
partnered restaurants, top takeout platforms bring on enormous fees and that recently there has
even been a pushback against high commission-based delivery apps, even calling for boycotts.
These delivery apps are taking advantage of and causing restaurants to lose the majority of their
hard-earned revenue.
Conclusion
Creating the project from scratch, I built a Java applet useful for visualization, and
numerous discoveries of graph algorithms in polar coordinates. Popular graph algorithms were
placed in a unique environment, introducing a new perspective to their behavior. Although some
progress has been made, going forward, more algorithms are to be implemented into the
simulator, including A* and bidirectional search. Observations are still in the process of being
converted into optimizations to make them more efficient and improve route planning in
practice
