A Ridesharing Analysis with a Hitchhiking Modification Applied to Taxi Trips in New York

Abstract

The past few years have seen the advent and rise of a number of transportation companies that uses the power of the Internet and mobile devices to fulfill consumers needs for efficient, timely taxi transport. Companies such as Uber and Lyft have leveraged communication networks to grow from small startups to firms exceeding market valuations in the billions of dollars. As these two spheres the public and the private sectors of taxi companies continue to compete, efficiency in managing large, sprawling transportation networks of taxis will become of paramount importance. The reasons for such policies are numerous. For one, increasing the efficiency of a transportation network reduces the emissions from these vehicles, limiting the impact of the transportation network on the environment. Also, implementing smarter policies regarding taxi usage can reduce the costs of a transportation company by limiting wear and tear on vehicles. In particular, the policy of ridesharing is one proposed alternative to limiting the dis- tance a taxi drives without any passengers, or in other words increasing the average vehicle occupancy of the taxis in question. The idea of ridesharing rests on the idea that multiple taxi riders can be picked up in the same or similar place and transported one-by-one to each of their different desired destinations. Such an analysis of the potential of ridesharing in New York City has already been investigated in thesis of A.J. Swoboda, who used trans- portation data from New York's taxis to determine the feasibility of ridesharing in New York. This thesis supplements this sort of analysis with the addition of a "hitchhiking" policy. With such a policy in place, a taxi would, in addition to the original ridesharing mechanics, pick up passengers en route to its destination or destinations. To identify the potential for efficiency policies such as ridesharing, one must leverage data and analyze data sets of taxi trips for ways to optimize networks of taxis and their clients. Publicly available data sets from the City of New York describing all taxi rides both through the public Taxi and Limousine Commission as well as those handled by Uber are available and used to determine the aggregate demand for taxis in the five boroughs of New York City. From there, the trip data is analyzed and the potential for ridesharing applicability can be determined or identified.