Towards a collaborative connected, automated driving environment: A game theory based decision framework for unprotected left turn maneuvers

Yalda Rahmati, Alireza Talebpour

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

Abstract

Connectivity and automation provide the opportunity to enhance safety and mitigate congestion in transportation systems. In fact, these technologies can enhance the efficiency of drivers/vehicles' decision-making by managing and coordinating the interactions among human-driven and connected, automated vehicles. Such management and coordination can lead to developing a collaborative connected, automated driving environment. Game theory, as a methodology to model the outcome of the interactions among multiple players, is a perfect tool to characterize the interaction between these vehicles. One of the most challenging maneuvers to model is drivers/vehicles' tactical decisions at intersections. Focusing on unprotected left turn maneuvers, this study aims at developing a game theory based framework to characterize driver behavior in unprotected left turn maneuvers in a connected, automated driving environment. A two-person non-zero-sum non-cooperative game under complete information is selected to model the underlying decision-making. NGSIM data is used to calibrate the payoff functions based on Maximum Likelihood Estimation. Validation results indicate that this framework can effectively capture vehicle interactions when performing conflicting turning movements while achieving a relatively high accuracy in predicting vehicles' real choice.

Original languageEnglish (US)
Title of host publicationIV 2017 - 28th IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1316-1321
Number of pages6
ISBN (Electronic)9781509048045
DOIs
StatePublished - Jul 28 2017
Externally publishedYes
Event28th IEEE Intelligent Vehicles Symposium, IV 2017 - Redondo Beach, United States
Duration: Jun 11 2017Jun 14 2017

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Other

Other28th IEEE Intelligent Vehicles Symposium, IV 2017
Country/TerritoryUnited States
CityRedondo Beach
Period6/11/176/14/17

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Modeling and Simulation

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