Award Abstract # 2052337
Collaborative Research: Economic Modeling and Control Methods for Next Generation Carpool Services

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: THE PENNSYLVANIA STATE UNIVERSITY
Initial Amendment Date: April 22, 2021
Latest Amendment Date: April 22, 2021
Award Number: 2052337
Award Instrument: Standard Grant
Program Manager: Daan Liang
dliang@nsf.gov
 (703)292-2441
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: May 1, 2021
End Date: October 31, 2025 (Estimated)
Total Intended Award Amount: $200,309.00
Total Awarded Amount to Date: $200,309.00
Funds Obligated to Date: FY 2021 = $200,309.00
History of Investigator:
  • Vikash Gayah (Principal Investigator)
Recipient Sponsored Research Office: Pennsylvania State Univ University Park
201 OLD MAIN
UNIVERSITY PARK
PA  US  16802-1503
(814)865-1372
Sponsor Congressional District: 15
Primary Place of Performance: Penn State University
231L Sackett Building
University Pk
PA  US  16802-1503
Primary Place of Performance
Congressional District:
15
Unique Entity Identifier (UEI): NPM2J7MSCF61
Parent UEI:
NSF Program(s): CIS-Civil Infrastructure Syst
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 029E, 1057
Program Element Code(s): 163100
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

This NSF grant will contribute to the sustainability of the nation's future green transportation by exploring the dynamics of carpooling in urban transportation systems, considering that an individual?s choice to use a carpooling service depends on how many others choose to do so as well. The research will model new mechanisms of positive feedback in a range of settings, validate these results using data from public agencies and private firms, and leverage this information for improved control of pooled transportation systems. The knowledge obtained can be used to develop and refine pricing, taxation, and other policy strategies that can both promote pooling and reduce urban traffic congestion. Improving carpool options can also improve environmental outcomes, by reducing vehicle travel, and social equity, by providing reasonable travel times to those who cannot buy or drive a car but who do not live close to convenient transit options. The education and outreach plan includes recruiting students, especially those from underrepresented groups, to work on the research tasks and provide them with opportunities to mentor junior colleagues on research activities. The research will develop interactive web modules to describe these carpooling behaviors to a wide audience.

The research will specifically focus on two mechanisms of positive feedback in carpooling. The first is hyperdemand, whereby the share of people choosing to carpool both depends on and affects traffic congestion. The second are matching externalities, whereby the quality of matches among carpoolers increases as more choose to carpool. The research will break new ground by bringing to bear tools from dynamical systems, search/matching theory and network-level traffic relations to build a robust theory of carpooling. To validate the theory, the research team will use empirical data collected from open data sources, as well as our industry partners. In addition, case studies of real policies to promote carpooling will inform the research and provide an evidence base for future work. The research activities will provide a new paradigm for modeling carpooling services and ride-hailing systems that will have significant impacts for the next generation of urban transportation systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

Dong, Xin and Liu, Hao and Gayah, Vikash V "An analytical model of many-to-one carpool system performance under cost-based detour limits" International Journal of Transportation Science and Technology , 2024 https://doi.org/10.1016/j.ijtst.2024.05.007 Citation Details
Dong, Xin and Liu, Hao and Gayah, Vikash V. "An analytical model of many-to-one carpool system performance under cost-based detour limits" 103rd Annual Meeting of the Transportation Research Board , 2024 Citation Details
Lehe, Lewis and Gayah, Vikash V. and Pandey, Ayush "Increasing Returns to Scale in Carpool Matching: Evidence from Scoop" Transport findings , 2021 https://doi.org/10.32866/001c.25093 Citation Details
Liu, H. "Scale effects in ridesplitting: A case study of the city of Chicago" 102nd Annual Meeting of the Transportation Research Board , 2023 Citation Details
Liu, Hao and Devunuri, Saipraneeth and Dong, Xin and Lehe, Lewis and Gayah, Vikash V. "Impact of competition on the scale effects in ridesplitting: A case study of Manhattan" 103rd Annual Meeting of the transportation Research baord , 2024 Citation Details
Liu, Hao and Devunuri, Saipraneeth and Lehe, Lewis and Gayah, Vikash V. "Scale effects in ridesplitting: A case study of the City of Chicago" Transportation Research Part A: Policy and Practice , v.173 , 2023 https://doi.org/10.1016/j.tra.2023.103690 Citation Details
Pandey, A. and Lehe, L. and Gayah, V.V. "Equilibrium stability for multi-modal traffic in an urban zone" 102nd Annual Meeting of the Transportation Research Board , 2023 Citation Details
Pandey, Ayush and Lehe, Lewis J. and Gayah, Vikash V. "Local stability of traffic equilibria in an isotropic network" Transportation Research Part B: Methodological , v.179 , 2024 https://doi.org/10.1016/j.trb.2023.102873 Citation Details

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page