A Highway-Driving System Design Viewpoint Using an Agent-Based Modeling of an Affordance-Based Finite State Automata

Kasin Ransikarbum, Namhun Kim, Sangho Ha, Richard A. Wysk, Ling Rothrock

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

This paper presents an agent-based modeling framework for affordance-based driving behaviors during the exit maneuver of driver agents in human-integrated transportation problems. We start our discussion from one novel modeling framework based on the concept of affordance called the affordance-based finite state automata (AFSA) model, which incorporates the human perception of resource availability and action capability. Then, the agent-based simulation illustrates the validity of the AFSA framework for the highway-lane-driver system. Next, the comparative study between real driving data and agent-based simulation outputs is provided using the transition diagram. Finally, we perform a statistical analysis and a correlation study to analyze affordance-based driving behavior of driver agents. The simulation results show that the AFSA model well represents the perception-based human actions and drivers' characteristics, which are essential for the design viewpoint of control framework of human driver modeling. This paper is also expected to benefit a designed control for autonomous/self-driving car in the future.

Original languageEnglish (US)
Pages (from-to)2193-2205
Number of pages13
JournalIEEE Access
Volume6
DOIs
StatePublished - Dec 9 2017

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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