# On the Importance of demand Consolidation in Mobility on Demand

## TL;DR

This paper systematically studies how demand consolidation in Mobility on Demand services affects operator costs and user Quality of Service, demonstrating a trade-off between capacity and QoS through stop location density.

## Contribution

It introduces a MoD system with limited stop locations, analyzing how adjusting stop density impacts capacity and QoS, and provides an open-source simulation tool.

## Key findings

- Decreasing stop density increases system capacity.
- Increasing stop density improves user QoS.
- The system can adapt between taxi-like and bus-like modes.

## Abstract

Mobility on Demand (MoD) services, like Uber and Lyft, are revolutionizing the way people move in cities around the world and are often considered a convenient alternative to public transit, since they offer higher Quality of Service (QoS - less waiting time, door-to-door service) at a cheap price. In the next decades, these advantages are expected to be further amplified by Automated MoD (AMoD), in which drivers will be replaced by automated vehicles, with a big gain in terms of cost-efficiency. MoD is usually intended as a door-to-door service. However, there has been recent interest toward consolidating, e.g., aggregating, the travel demand by limiting the number of admitted stop locations. This implies users have to walk from/to their intended origin/destination. The contribution of this paper is a systematic study the impact of consolidation on the operator cost and on user QoS. We introduce a MoD system where pick-ups and drop-offs can only occur in a limited subset of admitted stop locations. The density of such locations is a system parameter: the less the density, the more the user demand is consolidated. We show that, by decreasing stop density, we can increase system capacity (number of passengers we are able to serve). On the contrary, increasing it, we can improve QoS. The system is tested in AMoDSim, an open-source simulator. The code to reproduce the results presented here is available on-line. This work is a first step toward flexible mobility services that are able to autonomously re-configure themselves, favoring capacity or QoS, depending on the amount of travel demand coming from users. In other words, the services we envisage in this work shift their operational mode to any intermediate point in the range from a taxi-like door-to-door service to a bus-like service, with few served stops and more passengers on-board.