Improving Viability of Electric Taxis by Taxi Service Strategy Optimization: A Big Data Study of New York City

TL;DR

This study uses big data and Markov Decision Process modeling to evaluate and improve the viability of electric taxis in New York City by optimizing service strategies and analyzing profitability under various conditions.

Contribution

It introduces a novel approach combining big data analysis and MDP modeling to optimize electric taxi strategies and assess their profitability compared to conventional taxis.

Findings

Optimized taxi service strategies improve electric taxi viability.

Electric taxis can be profitable with sufficient battery capacity and charging infrastructure.

Big data analysis reveals key factors influencing electric taxi adoption.

Abstract

Electrification of transportation is critical for a low-carbon society. In particular, public vehicles (e.g., taxis) provide a crucial opportunity for electrification. Despite the benefits of eco-friendliness and energy efficiency, adoption of electric taxis faces several obstacles, including constrained driving range, long recharging duration, limited charging stations and low gas price, all of which impede taxi drivers' decisions to switch to electric taxis. On the other hand, the popularity of ride-hailing mobile apps facilitates the computerization and optimization of taxi service strategies, which can provide computer-assisted decisions of navigation and roaming for taxi drivers to locate potential customers. This paper examines the viability of electric taxis with the assistance of taxi service strategy optimization, in comparison with conventional taxis with internal combustion engines. A big data study is provided using a large dataset of real-world taxi trips in New York City. Our methodology is to first model the computerized taxi service strategy by Markov Decision Process (MDP), and then obtain the optimized taxi service strategy based on NYC taxi trip dataset. The profitability of electric taxi drivers is studied empirically under various battery capacity and charging conditions. Consequently, we shed light on the solutions that can improve viability of electric taxis.