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 journalConference articlepeer-review

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)160-179
Number of pages20
JournalTransportation Research Procedia
Volume38
DOIs
StatePublished - 2018
Event23rd International Symposium on Transportation and Traffic Theory, ISTTT 2019 - Lausanne, Switzerland
Duration: Jul 24 2018Jul 26 2018

Keywords

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

ASJC Scopus subject areas

  • Transportation

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