Millions of dollars saved when scheduled travel providers adapt to on-demand scheduling

Uber and Lyft are popular on-demand ways to travel, but does that mean trains and busses are a thing of the past? Travelers prefer different modes of transportation at different times. So how can all these modes co-exist and do so successfully? New research in the INFORMS journal Transportation Science has created a model and an algorithm to redistribute transit resources based on commuter preferences resulting in millions in savings.

This post was originally published on this site