Matching mechanisms for two-sided shared mobility systems

Shared mobility systems have gained significant attention in the last few decades due, in large part, to the rise of the service-based sharing economy. In this thesis, we study the matching mechanism design of two-sided shared mobility systems which include two distinct groups of users. Typical examples of such systems include ride-hailing platforms like Uber, ride-pooling platforms like Lyft Line, and community ride-sharing platforms like Zimride. These two-sided shared mobility systems can be modeled as two-sided markets, which need to be designed to efficiently allocate resources from the supply side of the market to the demand side of the market. Given its two-sided nature, the resource allocation problem in a two-sided market is essentially a matching problem. The matching problems in two-sided markets present themselves in decentralized and dynamic environments. In a decentralized environment, participants from both sides possess asymmetric information and strategic behaviors. They may behave strategically to advance their own benefits rather than the system-level performance. Participants may also have their private matching preferences, which they may be reluctant to share due to privacy and ethical concerns. In addition, the dynamic nature of the shared mobility systems brings in contingencies to the matching problems in the forms of, for example, the uncertainty of customer demand and resource availability. In this thesis, we propose matching mechanisms for shared mobility systems. Particularly, we address the challenges derived from the decentralized and dynamic environment of the two-sided shared mobility systems. The thesis is a compilation of four published or submitted journal papers. In these papers, we propose four matching mechanisms tackling various aspects of the matching mechanism design. We first present a price-based iterative double auction for dealing with asymmetric information between the two sides of the market and the strategic behaviors of self-interested agents. For settings where prices are predetermined by the market or cannot be changed frequently due to regulatory reasons, we propose a voting-based matching mechanism design. The mechanism is a distributed implementation of the simulated annealing meta-heuristic, which does not rely on a pricing scheme and preserves user privacy. In addition to decentralized matching mechanisms, we also propose dynamic matching mechanisms. Specifically, we propose a dispatch framework that integrates batched matching with data-driven proactive guidance for a Uber-like ride-hailing system to deal with the uncertainty of riders’ demand. By considering both drivers’ ride acceptance uncertainty and strategic behaviors, we finally propose a pricing mechanism that computes personalized payments for drivers to improve drivers' average acceptance rate in a ride-hailing system

CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

How to optimally dispatch orders to vehicles and how to tradeoff between immediate and future returns are fundamental questions for a typical ride-hailing platform. We model ride-hailing as a large-scale parallel ranking problem and study the joint decision-making task of order dispatching and fleet management in online ride-hailing platforms. This task brings unique challenges in the following four aspects. First, to facilitate a huge number of vehicles to act and learn efficiently and robustly, we treat each region cell as an agent and build a multi-agent reinforcement learning framework. Second, to coordinate the agents from different regions to achieve long-term benefits, we leverage the geographical hierarchy of the region grids to perform hierarchical reinforcement learning. Third, to deal with the heterogeneous and variant action space for joint order dispatching and fleet management, we design the action as the ranking weight vector to rank and select the specific order or the fleet management destination in a unified formulation. Fourth, to achieve the multi-scale ride-hailing platform, we conduct the decision-making process in a hierarchical way where a multi-head attention mechanism is utilized to incorporate the impacts of neighbor agents and capture the key agent in each scale. The whole novel framework is named as CoRide. Extensive experiments based on multiple cities real-world data as well as analytic synthetic data demonstrate that CoRide provides superior performance in terms of platform revenue and user experience in the task of city-wide hybrid order dispatching and fleet management over strong baselines.Comment: CIKM 201

Spectrum sharing models in cognitive radio networks

Spectrum scarcity demands thinking new ways to manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models for organizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks and analyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoption and exploitation of cognitive radios for open civil networks.L'escassetat de demandes d'espectre fan pensar en noves formes de gestionar la distribució de les bandes de freqüència de ràdio perquè el seu ús sigui més efectiu. La tecnologia emergent que pot permetre aquest canvi de paradigma és la ràdio cognitiva. Han sorgit diferents models d'organització i gestió de les ràdios cognitives, tots amb determinats fins estratègics. En aquest article es revisen els patrons d'assignació de l'espectre de les xarxes de ràdio cognitiva i s'analitzen quals són la base comuna de cada model. S'exposen les vulnerabilitats i els desafiaments oberts que segueixen amenaçant l'adopció i l'explotació de les ràdios cognitives per obrir les xarxes civils.La escasez de demandas de espectro hacen pensar en nuevas formas de gestionar la distribución de las bandas de frecuencia de radio para que su uso sea más efectivo. La tecnología emergente que puede permitir este cambio de paradigma es la radio cognitiva. Han surgido diferentes modelos de organización y gestión de las radios cognitivas, todos con determinados fines estratégicos. En este artículo se revisan los patrones de asignación del espectro de las redes de radio cognitiva y se analizan cuales son la base común de cada modelo. Se exponen las vulnerabilidades y los desafíos abiertos que siguen amenazando la adopción y la explotación de las radios cognitivas para abrir las redes civiles

Importance of mutual benefits in online knowledge sharing communities

The sustainability of knowledge sharing e-communities is a major issue at present. A hypothesis was proposed at the outset in the paper that the provision of mutual benefits among participants will lead to positive participation. Drawing from the economic and social theories, a framework for analysis was developed and tested in an empirical study. The preliminary results demonstrated a direct relationship between mutual benefits and the level of participation, and hence supported the hypothesis

An Analysis of issues against the adoption of Dynamic Carpooling

Using a private car is a transportation system very common in industrialized countries. However, it causes different problems such as overuse of oil, traffic jams causing earth pollution, health problems and an inefficient use of personal time. One possible solution to these problems is carpooling, i.e. sharing a trip on a private car of a driver with one or more passengers. Carpooling would reduce the number of cars on streets hence providing worldwide environmental, economical and social benefits. The matching of drivers and passengers can be facilitated by information and communication technologies. Typically, a driver inserts on a web-site the availability of empty seats on his/her car for a planned trip and potential passengers can search for trips and contact the drivers. This process is slow and can be appropriate for long trips planned days in advance. We call this static carpooling and we note it is not used frequently by people even if there are already many web-sites offering this service and in fact the only real open challenge is widespread adoption. Dynamic carpooling, on the other hand, takes advantage of the recent and increasing adoption of Internet-connected geo-aware mobile devices for enabling impromptu trip opportunities. Passengers request trips directly on the street and can find a suitable ride in just few minutes. Currently there are no dynamic carpooling systems widely used. Every attempt to create and organize such systems failed. This paper reviews the state of the art of dynamic carpooling. It identifies the most important issues against the adoption of dynamic carpooling systems and the proposed solutions for such issues. It proposes a first input on solving the problem of mass-adopting dynamic carpooling systems.Comment: 10 pages, whitepaper, extracted from B.Sc. thesis "Dycapo: On the creation of an open-source Server and a Protocol for Dynamic Carpooling" (Daniel Graziotin, 2010