A model of informational nudging in transportation networks

Yijie Cheng, Cedric Langbort

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Building on an existing model of coupled traffic/ driver decision-making in transportation networks, this paper investigates a mechanism for influencing drivers' en route choices. We consider dynamical transportation networks in a framework where drivers' route choices are affected by their response to an announced global information, as well as by a myopic observation of the surrounding congestion levels. Such a behavior is modeled by a system of ordinary differential equations. Furthermore, a traffic recommender is introduced to provide possibly misleading global information to drivers so as to influence their route choices in a way consistent with Thaler and Sunstein's concept of (informational) nudge. Our main result shows that the traffic recommender can create and stabilize any desired equilibrium on transportation networks by assuming that drivers always tend to minimize their expected travel cost, conditional on their past experience and the announced global information.

Original languageEnglish (US)
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7598-7604
Number of pages7
ISBN (Electronic)9781509018376
DOIs
StatePublished - Dec 27 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

Name2016 IEEE 55th Conference on Decision and Control, CDC 2016

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
CountryUnited States
CityLas Vegas
Period12/12/1612/14/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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