Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

2-2023

Abstract

The popularity of on-demand ride pooling is owing to the benefits offered to customers (lower prices), taxi drivers (higher revenue), environment (lower carbon footprint due to fewer vehicles) and aggregation companies like Uber (higher revenue). To achieve these benefits, two key interlinked challenges have to be solved effectively: (a) pricing – setting prices to customer requests for taxis; and (b) matching – assignment of customers (that accepted the prices) to taxis/cars. Traditionally, both these challenges have been studied individually and using myopic approaches (considering only current requests), without considering the impact of current matching on addressing future requests. In this paper, we develop a novel framework that handles the pricing and matching problems together, while also considering the future impact of the pricing and matching decisions. In our experimental results on a real-world taxi dataset, we demonstrate that our framework can significantly improve revenue (up to 17% and on average 6.4%) in a sustainable manner by reducing the number of vehicles (up to 14% and on average 10.6%) required to obtain a given fixed revenue and the overall distance travelled by vehicles (up to 11.1% and on average 3.7%). That is to say, we are able to provide an ideal win-win scenario for all stakeholders (customers, drivers, aggregator, environment) involved by obtaining higher revenue for customers, drivers, aggregator (ride pooling company) while being good for the environment (due to fewer number of vehicles on the road and lesser fuel consumed).

Keywords

'current, B-matching, Current matching, Customers drivers, Low carbon, Lowest price, Matchings, Number of vehicles, On demands, Taxi drivers

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, USA, 2023 February 7-14

Volume

37

First Page

14628

Last Page

14636

ISBN

9781577358800

Identifier

10.1609/aaai.v37i12.26710

Publisher

AAAI

City or Country

Washington

Additional URL

https://doi.org/10.1609/aaai.v37i12.26710

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