With the proliferation of GPS-enabled smartphones, the dynamics of the taxi service industry has changed dramatically. Instead of walking out to the street to find a taxi, we use apps on our smartphones to locate one (Ex. Uber, Ola).
In this highly competitive taxi service industry, anticipating the location of future customer requests and accordingly select routes is critical toward gaining a competitive advantage. Such strategically selected routes would lead to shorter wait times for customers and reduced fuel costs for taxi drivers.
In this talk, we will discuss algorithms to achieve this goal both for the traditional scenario where a customer hires the entire taxi as well as the more recent ride-sharing model. Through extensive empirical evaluation on real datasets, we will present evidence that the proposed strategies lead to up to 70% shorter waiting times for customers, 40% more customers, and 20% lower rejection rate.
Key Takeaways:
- Route recommendation overview
- Impact of Reinforcement learning on the cab-industry.
Check out the video below to know more about the talk.
