Exploring Passengers’ Experiences in Algorithmic Dynamic Ride-pooling Services

Abstract

Ride-pooling Mobility-on-Demand (MoD) services are a cutting-edge form of smart mobility services that operate through automated algorithmic decisions for optimal efficiency. However, the sociotechnical aspects of the passengers’ experience have not yet been investigated despite its significance. To address this gap, we conducted an empirical study in Shucle, a ride-pooling MoD service piloted in South Korea. Drawing on our interview with eight Shucle users, we explore the existing passengers’ experience in this context. Our initial findings revealed that passengers faced personal losses in terms of unpredictability and uncontrollability owing to the algorithmic decision-making that coordinates the sharing of the tool as transportation. We then discuss important issues to be considered for human-centered design in the context of passengers with different goals and interests sharing a real-time algorithm-based ride-pooling service.