Projects Social Mobility Sharing

Funding: MIT Institute of Data, System and Society (IDSS) Research Fund 2016

Traffic congestion, dominated by single-occupancy vehicles, reflects not only transportation system inefficiency and externality, but also a sociological state of human isolation. Advances in ICT are enabling the growth of real-time ride sharing—whereby passengers are paired up on car trips with similar Origin-Destinations and proximate time windows—to improve system efficiency by moving more people in fewer cars. Lesser known, however, are the opportunities of shared mobility as a tool to foster and strengthen human interactions. In contrast to typical social interactions in public or private space (meeting rooms, streets, pubic squares, living rooms, etc.) the nature of shared car rides is impromptu, captive for a considerable duration, and remarkably more intimate, representing a unique juxtaposition of spontaneity and intensity. It is also distinct from mass transit modes such as buses and trains, where most passengers refrain from engaging each other. Funded by MIT Institute of Data, System and Society, this research examines the bi-directional connections between shared mobility as a transportation technology, and as an emerging mode of human interaction: how the unique temporal-spatial setting of ride sharing may (a) contribute to or preclude its growth in travel mode share, and (b) affect the quality and quantity of meaningful human interactions in the urban environment. 

Currently, passenger matching algorithms are based upon the criterion of efficiency, namely maximizing occupancy and minimizing travel distance, while neglecting the sociological aspects of mobility sharing. In this IDSS research, we study mobility sharing from the perspective of human interactions, define and measure individuals’ preferences for fellow passengers, and develop matching algorithms that respect both the transportation network optimization and the individuals’ preferences (or lack of) for human interactions, in order to realize the societal benefits of interactions complementing the environmental and economic benefits of reduced congestion.

Mobility Sharing as a Preference Matching Problem, Zhang, Hongmou, and Zhao Jinhua , Transportation Research Part B, (Submitted)

Traffic congestion, dominated by single-occupancy vehicles, reflects not only transportation system inefficiency and negative externalities, but also a sociological state of human isolation. Advances in information and communication technology are enabling the growth of real-time ridesharing to improve system efficiency. While ridesharing algorithms optimize passenger matching based on efficiency criteria (maximum number of paired trips, minimum total vehicle-time or vehicle-distance... more

The Tradeoff Between Efficiency and Fellow Passenger Preference: a Preference-Based Ridesharing Model, Zhang, Hongmou, and Zhao Jinhua , Transportation Research Board 96th Annual Conference, Washington, D.C., (2017)

Advances in information technology are enabling the growth of real-time ridesharing—whereby passengers are paired up on car trips to improve system efficiency by using fewer cars. Lesser known, however, are the opportunities of shared mobility as a tool to foster and strengthen human interactions. The nature of shared car rides is impromptu, captive for a considerable duration, and remarkably more intimate, representing a unique juxtaposition of spontaneity and intensity. While ridesharing... more

User Identification of and Attitude Toward Dynamic Ridesourcing Services, Dawes, Margo, and Zhao Jinhua , Transportation Research Board 96th Annual Conference, Washington, D.C., (2017)

Media coverage of ridesourcing services such as Uber and Lyft has described a rivalry between new technology and the established taxi industry. Individual users and non-users of ridesourcing may have more nuanced perspectives, but policymakers have had little guidance on how to best represent these interests. This study uses a standardized questionnaire distributed across the United States by an online survey company to understand individual attitudes toward Uber, Lyft, and ridesourcing... more

Dynamic Pricing in Shared Mobility on Demand Service and its Social Impacts Master of Science in Transportation, Qiu, Han , Department of Civil and Environmental Engineering, 06/2017, Volume Master of Science in Transportation , Cambridge, MA, (2017)

In this thesis, we formulate and solve a profit maximization problem of shared mobility on demand service operations, and investigate the impact of such operations on performance of transportation system with a carefully designed case study. It is shown that our approach can generate much more profit than other basic strategies, though it has negative impacts on system performance, such as increasing congestion level and reducing capacity provided. We also consider possible regulation... more

Perspectives on the Ridesourcing Revolution : surveying individual attitudes toward Uber and Lyft to inform urban transportation policymaking, Dawes, Margo , Department of Urban Studies and Planning, Volume MCP, Cambridge, MA, (2016)

Media coverage of ridesourcing services such as Uber and Lyft has described a rivalry between new technology and the established taxi industry. Individual users and non-users of ridesourcing, however, may have more nuanced perspectives, but policymakers have little guidance on how to best represent these interests. This thesis uses a standardized questionnaire distributed across the United States by an online survey company to understand individual attitudes toward Uber, Lyft, and... more

Humanizing Travel: How E-hail Apps Transform Stakeholder Relationships in Taxi Services, Li, Corinna, and Zhao Jinhua , Transportation Research Board 94th Annual Meeting, Washington, D.C., (2015)

Efficiency benefits of the increasingly popular taxi-hailing (e-hailing) apps have been widely discussed - reduction of search time, convenience for passengers, and higher income for drivers. However the project proposes that there is a qualitative difference that e-hailing apps are engendering in the United States (U.S.) taxi industry above and beyond their quantitative impacts. E-hailing establishes direct connections between drivers and passengers, making ride requests person-to-person... more