Related papers: FairFare: A Tool for Crowdsourcing Rideshare Data …

In this paper, we propose a novel, computational efficient, dynamic ridesharing algorithm. The beneficial computational properties of the algorithm arise from casting the ridesharing problem as a linear assignment problem between fleet…

In a hybrid cloud, individual cloud service providers (CSPs) often have incentive to use each other's resources to off-load peak loads or place load closer to the end user. However, CSPs have to keep track of contributions and gains in…

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of machine learning systems. Stringent parity constraints on…

Fair consensus building combines the preferences of multiple rankers into a single consensus ranking, while ensuring any group defined by a protected attribute (such as race or gender) is not disadvantaged compared to other groups. Manually…

Autonomous vehicles (AVs) have the potential of reshaping the human mobility in a wide variety of aspects. This paper focuses on a new possibility that the AV owners have the option of "renting" their AVs to a company, which can use these…

For drivers in ride-hailing companies, allocation within the city is paramount to get matched with rides. This decision depends on many factors, where some of them (such as demand and allocation of others) are unknown for the drivers, but…

In this paper we present a mobile crowdsourcing platform CrowdCafe, where people can perform microtasks using their smartphones while they ride a bus, travel by train, stand in a queue or wait for an appointment. These microtasks are…

Ubiquitous mobile computing have enabled ride-hailing services to collect vast amounts of behavioral data of riders and drivers and optimize supply and demand matching in real time. While these mobility service providers have some degree of…

Ridesplitting -- a type of ride-hailing in which riders share vehicles with other riders -- has become a common travel mode in some major cities. This type of shared ride option is currently provided by transportation network companies…

Millions of drivers worldwide have enjoyed financial benefits and work schedule flexibility through a ride-sharing economy, but meanwhile they have suffered from the lack of a sense of identity and career achievement. Equipped with social…

In collaborative data sharing and machine learning, multiple parties aggregate their data resources to train a machine learning model with better model performance. However, as the parties incur data collection costs, they are only willing…

The ridesharing economy is experiencing rapid growth and innovation. Companies such as Uber and Lyft are continuing to grow at a considerable pace while providing their platform as an organizing medium for ridesharing services, increasing…

Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulations. The CSCW and HCI communities increasingly turn to…

We consider a ridesharing problem where there is uncertainty about the completion of trips from both drivers and riders. Specifically, we study ridesharing mechanisms that aim to incentivize commuters to reveal their valuation for trips and…

We propose a Novel Fairness-Aware framework for Crowdsourcing Energy Services (FACES) to efficiently provision crowdsourced IoT energy services. Typically, efficient resource provisioning might incur an unfair resource sharing for some…

How do we create ethical and equitable experiences on global platforms? How might UX designers and developers incorporate reflexive practices--a continuous self-evaluation of one's assumptions and biases--to mitigate assumptions and…

Urban mobility systems face persistent challenges of congestion, underutilized vehicles, and rising emissions driven by private point-to-point commuting. Although ride-sharing platforms exist, their profit-driven incentive structures often…

Autonomous ridesharing systems (ARS) promise many societal and environmental benefits, including decreased accident rates, reduced energy consumption and pollutant emissions, and diminished land use for parking. To unleash ARS' potential,…

Uber has recently been introducing novel practices in urban taxi transport. Journey prices can change dynamically in almost real time and also vary geographically from one area to another in a city, a strategy known as surge pricing. In…

This paper provides efficient solutions to maximize profit for commercial ridesharing services, under a pricing model with detour-based discounts for passengers. We propose greedy heuristics for real-time ride matching that offer different…