Ride-Pooling Matching with a Compensatory Cost Function: Implications for Adoption, Efficiency and Level of Service

TL;DR

This study introduces a user-centric model for ride-pooling that considers trade-offs in travel time and discomfort, revealing that significant vehicle mileage savings depend on user willingness and pricing strategies.

Contribution

It formulates a compensatory cost function for user decision-making and analyzes how demand, preferences, and pricing influence ride-pooling adoption and efficiency.

Findings

Vehicle mileage savings up to 50% with high user willingness and discounts.

Savings drop to around 15% under less favorable behavioral assumptions.

User willingness and pricing are critical for ride-pooling success.

Abstract

By utilising vehicle capacity more efficiently, ride-pooling platforms can potentially lead to reduced congestion levels without adversely prolonging travel times. While previous studies concluded that shared rides can offer substantial benefits, initial evidence suggests low adoption levels. We postulate that previous studies that investigated the potential of ride-pooling failed to account for the trade-off that users are likely to make when considering a shared ride. We address this shortcoming by formulating user net benefit stemming from sharing as a compensatory function where the additional travel time and on-board discomfort need to be compensated by the price discount for a traveller to choose a shared ride over a private ride. The proposed formulation is embedded in a method for matching travel requests and vehicles. We conduct a series of experiments investigating how the potential of ride-pooling services depends on travel demand characteristics, user preferences and the pricing policy adopted by the service provider. In particular, the impact of various behavioural settings in terms of users' willingness to share their ride and delay aversion on service adoption and its operational efficiency is assessed. Our results suggest that the total vehicle mileage savings found by previous studies is only attainable when users are very willing to share their ride (i.e. attach low premium to private rides) and are offered a 50% discount for doing so. We find ride-pooling transportation distance savings as low as 15% in less favourable behavioural scenarios.