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

Europe’s Collaborative Economy: Charting a constructive path forward. CEPS Task Force Report 12 Nov 2020.

Ride-hailing, home-sharing, meal-delivery, and other forms of digitally powered task-sharing are creating jobs and growth in Europe – and significant policy challenges. What should be the responsibilities of these new platforms, how should workers be classified, and how can insurers and others provide services to this new type of economic activity? Above all, what Europe-wide rules are required for the single market to work for the collaborative economy? This new report provides some answers to these questions. It completes the work of a year-long Task Force that heard from corporate, union, employer and city representatives, along with leading academics. Without reform, Europe risks falling behind in this new area of economic activity. Platforms, both European and non-European, face a labyrinth of local, often contradictory, rules. Their legal status as either internet society platforms or as transport or accommodation providers remains unclear. Most taxi and accommodation regulations date from the pre-internet era. Task Force sessions concurred that the present regulations must be modernised. There remained significant differences of opinion about the proper balance between local and European rules. But all members agreed that platforms should take on new responsibilities to combat illegal activities, which can mean sharing information and data on their users with cities – provided privacy rules are respected. They agreed that sectoral rules need to be updated to create a level playing field between hotels and short-term private rentals, and taxi and ride-hailing drivers. And while disagreements remained over the status of workers as independent contractors or employees, they agreed that workers should receive increased social protection

Cloud-based Privacy-Preserving Collaborative Consumption for Sharing Economy

Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these cloud-based platforms. This work presents novel cloud-based privacy-preserving solutions to support collaborative consumption applications for sharing economy. In typical collaborative consumption, information processing platforms need to enable fair cost-sharing among multiple users for utilizing certain shared facilities and communal services. Our cloud-based privacy-preserving protocols, based on homomorphic Paillier cryptosystems, can ensure that the cloud-based operator can only obtain an aggregate schedule of all users in facility sharing, or a service schedule conforming to service provision rule in communal service sharing, but is unable to track the personal schedules or demands of individual users. More importantly, the participating users are still able to settle cost-sharing among themselves in a fair manner for the incurred costs, without knowing each other's private schedules or demands. Our privacy-preserving protocols involve no other third party who may compromise privacy. We also provide an extensive evaluation study and a proof-of-concept system prototype of our protocols.Comment: To appear in IEEE Trans. Cloud Computin

Shared autonomous vehicle services: A comprehensive review

© 2019 Elsevier Ltd The actions of autonomous vehicle manufacturers and related industrial partners, as well as the interest from policy makers and researchers, point towards the likely initial deployment of autonomous vehicles as shared autonomous mobility services. Numerous studies are lately being published regarding Shared Autonomous Vehicle (SAV) applications and hence, it is imperative to have a comprehensive outlook, consolidating the existing knowledge base. This work comprehensively consolidates studies in the rapidly emerging field of SAV. The primary focus is the comprehensive review of the foreseen impacts, which are categorised into seven groups, namely (i) Traffic & Safety, (ii) Travel behaviour, (iii) Economy, (iv) Transport supply, (v) Land–use, (vi) Environment & (vii) Governance. Pertinently, an SAV typology is presented and the components involved in modelling SAV services are described. Issues relating to the expected demand patterns and a required suitable policy framework are explicitly discussed

A Fully Decentralized Hierarchical Transactive Energy Framework for Charging EVs with Local DERs in Power Distribution Systems

The penetration rates of both electric vehicles (EVs) and distributed energy resources (DERs) have been increasing rapidly as appealing options to address the global problems of carbon emissions and fuel supply issues. However, uncoordinated EV charging activities and DER generation result in operational challenges for power distribution systems. Therefore, this article has developed a hierarchical transactive energy (TE) framework to locally induce and coordinate EV charging demand and DER generation in electric distribution networks. Based on a modified version of the alternating direction method of multipliers (ADMMs), two fully decentralized (DEC) peer-to-peer (P2P) trading models are presented, that is, an hour-ahead market and a 5-min-ahead real-time market. Compared to existing P2P electricity markets, this research represents the first attempt to comprehensively incorporate alternating current (ac) power network constraints into P2P electricity trading. The proposed TE framework not only contributes to mitigating operational challenges of distribution systems, but also benefits both EV owners and DER investors through secured local energy transactions. The privacy of market participants is well preserved since the bid data of each participant are not exposed to others. Comprehensive simulations based on the IEEE 33-node distribution system are conducted to demonstrate the feasibility and effectiveness of the proposed method