An integrated and personalized traveler information and incentive scheme for energy efficient mobility systems

Chenfeng Xiong, Mehrdad Shahabi, Jun Zhao, Yafeng Yin, Xuesong Zhou, Lei Zhang

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Recently, the employment of different types of incentives in transportation systems to form advanced transportation congestion management solutions has garnered significant attention. Instead of using presumed or fixed-amount incentives, this paper develops an integrated and personalized traveler information and incentive scheme to incentivize toward a more energy-efficient travel and mobility decisions. We have developed a behavior research and empirical modeling system to quantify the personalized monetary incentives. Then, it is integrated with a control optimizer for optimized incentive allocation. This scheme innovatively integrates behavioral modeling and optimization for travel incentive design. Through a demonstrative case study for a large-scale transportation system in the Washington D.C. and Baltimore regions, the capability of the proposed scheme is highlighted with significant system-level energy savings, reasonable insights on individual travel behavior responses, as well as superior computational efficiency.

Original languageEnglish (US)
Pages (from-to)57-73
Number of pages17
JournalTransportation Research Part C: Emerging Technologies
Volume113
DOIs
StatePublished - Apr 2020

    Fingerprint

Keywords

  • Control optimizer
  • Incentives
  • Monetary incentives
  • System model
  • Traveler information

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

Cite this