Smart space logistic service for real-time ridesharing

The paper describes a logistic service-based approach to real-time ridesharing based on smartspace concept. Smart-M3 information platform is used as smart space infrastructure for presented approach. The service is based on Smart-M3 RDF ontology which is formed by ontology slices of participants' mobile devices. The paper presents an algorithm for finding appropriate fellow- travelers for drivers as well as definition of acceptable pick-up and drop-off points for them

Essays of Platform Work and Changing Workplaces

The platform economy provides employment opportunities for many workers, offering benefits such as low entry and exit costs, and flexibility. However, it also represents a contemporary manifestation of nonstandard work, characterized by insecurity and inadequate labor protections. As platforms expand and become more often a full-time job to many, the contradictions between their benefits and precariousness intensify. Research has clarified the causes and implications of platform work, especially in the context of high-income countries. However, platform work is a global phenomenon, and its impacts are bound to differ across nations. Furthermore, as ridesharing became the poster child of the platform economy, it has received disproportional attention relative to other segments. Still, it is known that rules, outcomes, and experiences vary significantly across platforms. This dissertation comprises an overview introduction and three independent essays focusing on the platform economy. The first and second essays focus on the impacts of ridesharing on occupational demographics and job quality, taking advantage of the staggered entry of Uber in Brazil as a natural experiment. The first uncover general trends and compares drivers with workers in other arrangements, including formal and informal, while the second zooms in on women in distinct family configurations to investigate whether ridesharing – in providing a flexible job opportunity – has affected women differently. Findings reveal a surge in the number of people driving as their primary job with a marked decline in earnings and job security trends. Furthermore, the presence of children in the household and urban violence rates affect women’s decisions to become drivers differently than men. The third essay comprises an online experiment and a survey on a freelance platform to investigate United States-based worker preferences, contrasting individuals who rely on the platform as primary and supplemental income sources. Preliminary findings from a pilot study reveal that platform earnings play a significant role in covering essential family expenses, and there is a positive correlation between preference for flexibility and platform reliance. Workers prominently highlight flexibility and business-related benefits as the platform’s primary advantages, while identifying elements of precariousness and high fees as major drawbacks

Context-based access control for ridesharing service

The paper describes a context-based access control model for a ridesharing service. Ridesharing is a shared use of a car by the driver and one or more passengers for a joint trip. The service is based on the smart space concept. For this purpose the Smart-M3 platform is used. Currently the Smart-M3 platform doesn't have an appropriate access control mechanism meeting the following requirements: supporting a flexible, descriptive and well-defined policy language and taking into consideration the context information. Therefore, the usage of the context-based access control model has been proposed. This model is built as a combination of the role-based and attribute-based access control models. It uses roles, which are assigned dynamically based on the user's context, and meets the requirements to the access control in the smart space. An analysis of information transfer through the ridesharing service modules is used for defining the user's context. The model has been implemented within an access control broker, which controls the access to the smart space resources

Modeling Individual Activity and Mobility Behavior and Assessing Ridesharing Impacts Using Emerging Data Sources

Predicting individual mobility behavior is one of the major steps of transportation planning models. Accurate prediction of individual mobility behavior will be beneficial for transportation planning. Although previous studies have used different data sources to model individual mobility behaviors, they have several limitations such as the lack of complete mobility sequences and travel mode information, limiting our ability to accurately predict individual movements. In recent years, the emergence of GPS-based floating car data (FCD) and on-demand ride-hailing service platforms can provide innovative data sources to understand and model individual mobility behavior. Compared to the previously used data sources such as mobile phone and social media data, mobility data extracted of the new data sources contain more specific, detailed, and longitudinal information of individual travel mode and coordinates of the visited locations. This dissertation explores the potential of using GPS-based FCD and on-demand ride-hailing service data with different modeling techniques towards understanding and predicting individual mobility and activity behaviors and assessing the ridesharing impacts through three studies

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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Quantifying the benefits of vehicle pooling with shareability networks

Taxi services are a vital part of urban transportation, and a considerable contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort quantifiable in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad-hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that with increasing but still relatively low passenger discomfort, cumulative trip length can be cut by 40% or more. This benefit comes with reductions in service cost, emissions, and with split fares, hinting towards a wide passenger acceptance of such a shared service. Simulation of a realistic online system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets or when willingness to share is low.Comment: Main text: 6 pages, 3 figures, SI: 24 page

D3.3 Business models report

RECIPROCITY aims to transform European cities into climate-resilient and connected, multimodal nodes for smart and clean mobility. The project's innovative four-stage replication approach is designed to showcase and disseminate best practices for sustainable urban development and mobility. As part of this project, the present business model report (D3.3) provides an overview of innovative urban mobility business models that could be tailored to cities in the RECIPROCITY replication ecosystem. The work developed was based upon the work carried-out in WP1-2-4, and aimed to collect and derive the business model patterns for urban mobility and propose a business model portfolio that encourage cross-sector collaboration and create an integrated mobility system. This report is therefore addressed to cities and local authorities that have to meet mobility challenges (i.e. high costs and low margin, broad set of partners, competing with private car) by providing new services to activate and accelerate a sustainable modal shift. It also targets other stakeholders interested in business model concepts applied to cities