A Polynomial-time, Truthful, Individually Rational and Budget Balanced Ridesharing Mechanism

Ridesharing has great potential to improve transportation efficiency while reducing congestion and pollution. To realize this potential, mechanisms are needed that allocate vehicles optimally and provide the right incentives to riders. However, many existing approaches consider restricted settings (e.g., only one rider per vehicle or a common origin for all riders). Moreover, naive applications of standard approaches, such as the Vickrey-Clarke-Groves or greedy mechanisms, cannot achieve a polynomial-time, truthful, individually rational and budget balanced mechanism. To address this, we formulate a general ridesharing problem and apply mechanism design to develop a novel mechanism which satisfies all four properties and whose social cost is within 8.6% of the optimal on average

Uber

Uber focuses primarily on the ride-hailing industry, which puts the company in direct competition with regular taxis. The company is like a lot of tech-driven, fast growing entrepreneurial firms in that it still struggles for profitability. Also, the popularity of this new form of transportation has put the company and its close competitors, such as Lyft, in the spotlight of government lawmakers and regulators. If they classify Uber drivers as employees rather than independent contractors, it could dramatically alter the Uber business model. This case is written in the aftermath of the ouster of one of the company’s co-founders as CEO, a not-so-successful initial public offering (IPO), and some very serious human resources issues associated with widely publicized instances of sexual harassment and mistreatment of drivers

Shared Mobility - Operations and Economics

In the last decade, ubiquity of the internet and proliferation of smart personal devices have given rise to businesses that are built on the foundation of the sharing economy. The mobility market has implemented the sharing economy model in many forms, including but not limited to, carsharing, ride-sourcing, carpooling, taxi-sharing, ridesharing, bikesharing, and scooter sharing. Among these shared-use mobility services, ridesharing services, such as peer-to-peer (P2P) ridesharing and ride-pooling systems, are based on sharing both the vehicle and the ride between users, offering several individual and societal benefits. Despite these benefits, there are a number of operational and economic challenges that hinder the adoption of various forms of ridesharing services in practice. This dissertation attempts to address these challenges by investigating these systems from two different, but related, perspectives. The successful operation of ridesharing services in practice requires solving large-scale ride-matching problems in short periods of time. However, the high computational complexity and inherent supply and demand uncertainty present in these problems immensely undermines their real-time application. In the first part of this dissertation, we develop techniques that provide high-quality, although not necessarily optimal, system-level solutions that can be applied in real time. More precisely, we propose a distributed optimization technique based on graph partitioning to facilitate the implementation of dynamic P2P ridesharing systems in densely populated metropolitan areas. Additionally, we combine the proposed partitioning algorithm with a new local search algorithm to design a proactive framework that exploits historical demand data to optimize dynamic dispatching of a fleet of vehicles that serve on-demand ride requests. The main purpose of these methods is to maximize the social welfare of the corresponding ridesharing services. Despite the necessity of developing real-time algorithmic tools for operation of ridesharing services, solely maximizing the system-level social welfare cannot result in increasing the penetration of shared mobility services. This fact motivated the second stream of research in this dissertation, which revolves around proposing models that take economic aspects of ridesharing systems into account. To this end, the second part of this dissertation studies the impact of subsidy allocation on achieving and maintaining a critical mass of users in P2P ridesharing systems under different assumptions. First, we consider a community-based ridesharing system with ride-back guarantee, and propose a traveler incentive program that allocates subsidies to a carefully selected set of commuters to change their travel behavior, and thereby, increase the likelihood of finding more compatible and profitable matches. We further introduce an approximate algorithm to solve large-scale instances of this problem efficiently. In a subsequent study for a cooperative ridesharing market with role flexibility, we show that there may be no stable outcome (a collusion-free pricing and allocation scheme). Hence, we introduced a mathematical formulation that yields a stable outcome by allocating the minimum amount of external subsidy. Finally, we propose a truthful subsidy scheme to determine matching, scheduling, and subsidy allocation in a P2P ridesharing market with incomplete information and a budget constraint on payment deficit. The proposed mechanism is shown to guarantee important economic properties such as dominant-strategy incentive compatibility, individual rationality, budget-balance, and computational efficiency. Although the majority of the work in this dissertation focuses on ridesharing services, the presented methodologies can be easily generalized to tackle related issues in other types of shared-use mobility services.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169843/1/atafresh_1.pd

Budget-balanced and strategy-proof auctions for multi-passenger ridesharing

Ridesharing and ridesourcing services have become widespread, and pricing the rides is a crucial problem for these systems. We propose and analyze a budget-balanced and strategy-proof auction, the Weighted Minimum Surplus (WMS) auction, for the dynamic ridesharing problem with multiple passengers per ride. Under the assumption of downward closed alternatives, we obtain lower bounds for the surplus welfare and surplus profit of the WMS auction. We also propose and analyze a budget-balanced version of the well-known VCG mechanism, the $\mathrm{VCG}_s$. Encouraging experimental results were obtained for both the WMS auction and the $\mathrm{VCG}_s$.Comment: 27 pages with 1 figur

Enhancing Capacity and Managing Demand to Increase Short-Term Throughput on the San Francisco-Oakland Bay Bridge

While there are many proposals for fixing congestion between San Francisco and Oakland in California by adding a new bridge or tube, these solutions will take decades to implement even though a solution is needed now. This thesis assesses sixteen different strategies for reducing congestion in the short-term in the four categories of improving transit, promoting carpooling, implementing intelligent transportation systems practices, and incentivizing alternatives to using the Bay Bridge. Top priorities include HOV improvements on the West Grand Avenue and Powell Street onramps, altering WestCAT Lynx and BART transit services, partnering with rideshare apps to increase transit station accessibility (last mile problem), partnering with vanpool/minibus apps, promoting carpooling and implementing a citizen report system for carpool violators, shifting corporate cultures away from requiring employees to drive and drive alone, and lastly, altering land-use planning practices. To reach this conclusion, an inventory of current proposals and relevant research was compiled. Ridership and capacity data for the various modes of transportation across the bay were assessed for shortfalls and opportunities. Through this research and its resultant conclusions, focus can be placed on the best strategies to pursue in the near-term, while the Bay Area waits on a second bridge or tube in the long-term

Physical and Socio Economic Affordability Elements that Regulate formal low cost housing tenure in Bauchi Metropolis

Purpose: The current practice housing policies of Nigeria did not highlight on the affordability of formal low cost houses. Low income earners don’t have sufficient income to buy a calorie of foods and meet basic necessities like clothing, rent, fuel, utilities, transport, communications, medical expenses, education, and on a broader sense, housing. Objectives of this study were (i) to investigate the current practices of housing policies in Bauchi Nigeria; (ii) to evaluate the affordability elements in Bauchi Nigeria, (iii) to study the relationship among the FLCH affordability elements in Bauchi Nigeria. Methodology employed includes descriptive statistics and Pearson correlation. Findings: The study found that there are no laws, sections or guidelines regulating the affairs of formal low cost housing. The design does not reflect user need; it did not conform to their culture, family background and size. No provision for public participation in the policy documents. Formal low cost houses are located at the peripheries of the town outside trekking distances which repel beneficiaries because of the awkward location. Residents have higher number of defendants, lower income and lower qualification. This study found that design, location, participation, highlight on affordability and family issues have prominent impact on affordability and hence be incorporated in policy document. It can therefore be clinch that formal low cost houses in Bauchi, are not affordable. Conclusively, these affordability elements should be upheld to ensure sustainable formal low cost housing affordability policy for the low income groups. The physical and socio-economic elements are the catalyst in the housing provision aspect. These elements can bridge the wide fissure being the basic features, essentials and the fundamentals of a good policy. Keywords: Affordability elements, formal low cost housing, housing policy issues, house ownershi