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


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
StatePublished - Apr 2020



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

ASJC Scopus subject areas

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

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