Exploring shareability networks of probabilistic ride-pooling problems

TL;DR

This paper analyzes shareability networks in probabilistic ride-pooling, revealing structural differences and providing insights to enhance ride-sharing systems using a novel network analysis approach.

Contribution

It introduces and examines four types of shareability networks derived from probabilistic ride-pooling, using a new utility-based algorithm and extensive simulations.

Findings

Significant structural differences between network types.

Probabilistic pooling captures complex network features.

Insights can inform better ride-pooling system design.

Abstract

Travellers sharing rides in ride-pooling systems form various kinds of networks. While the notions of the so-called shareability graphs, has been in the core of many ride-pooling algorithms, so far they have not been explicitly analysed. Here, we introduce and examine four kinds of networks resulting from ride-pooling problems. We use 147 NYC taxi requests from 2016 pooled into attractive shared-rides with our utility based ExMAS algorithm and explore resulting shareability networks. To cover unknown individual properties of pooling travellers, we run 1000 replications of probabilistic pooling process, resulting in richer representation of weighted graphs instrumental to reveal complex network structures. Our findings reveal substantial differences between network structures and topologies. Properties of ride-pooling networks may be further analysed to better understand and improve ride-pooling systems.