carpooling

To validate their approach, the authors construct test cases based on the New York City taxicab dataset.

This data repository provides the data used in the following research project supported by an NCST (UTC) grant: Evaluating the Sustainability Impacts of Intelligent Carpooling Systems for SOV Commuters in the Atlanta Region.

Community-based carpooling has the potential to alleviate traffic congestion and reduce the transportation carbon footprint. One of the major barriers to implementation is the difficulty of optimizing carpool formation in large systems. This study utilizes two different methods to solve the carpooling optimization problem: 1) bipartite algorithm and 2) integer linear programming.

This study explores the factors that affect the use of ridehailing services as well as the adoption of shared (pooled) ridehailing using data collected in California in fall 2018 using a cross-sectional travel survey.

This research explicitly models taste heterogeneity towards pooled ridehailing. In addition, unlike existing studies either at the person level or employing stated-preference data, a trip-level analysis is performed in connection with revealed preferences, which generates more realistic and relevant implications to policy and practice.

The goal of the 2023 Atlanta Metropolitan Area Northwest Corridor Commuter Survey is to gather information from metropolitan area residents about changes in their commute travel to work on the I-75 Northwest Corridor (NWC) over time. The survey looks at commute travel before and after the NWC Express Lanes opened, during the height of the COVID-19 pandemic, and finally at anticipated changes after the pandemic is behind us.