Augmented driver behavior models for high-fidelity simulation study of crash detection algorithms

Ahura Jami, Mahdi Razzaghpour*, Hussein Alnuweiri, Yaser P. Fallah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Developing safety and efficiency applications for Connected and Automated Vehicles (CAVs) requires a great deal of testing and evaluation. The need for the operation of these systems in critical and dangerous situations makes the burden of their evaluation very costly, possibly dangerous, and time-consuming. As an alternative, researchers attempt to study and evaluate their algorithms and designs using simulation platforms. Modeling the behavior of drivers or human operators in CAVs or other vehicles interacting with them is one of the main challenges of such simulations. While developing a perfect model for human behavior is a challenging task and an open problem, a significant augmentation of the current models used in simulators for driver behavior is presented. In this paper, a simulation framework for a hybrid transportation system is presented that includes both human-driven and automated vehicles. In addition, the human driving task is decomposed and a modular approach is offered to simulate a large-scale traffic scenario, allowing for a thorough investigation of automated and active safety systems. Such representation through Interconnected modules offers a human-interpretable system that can be tuned to represent different classes of drivers. Additionally, a large driving dataset is analyzed to extract expressive parameters that would best describe different driving characteristics. Finally, a similarly dense traffic scenario is recreated within the simulator and a thorough analysis of various human-specific and system-specific factors is conducted, studying their effect on traffic network performance and safety.

Original languageEnglish
Pages (from-to)436-449
Number of pages14
JournalIET Intelligent Transport Systems
Volume18
Issue number3
DOIs
Publication statusPublished - Mar 2024
Externally publishedYes

Keywords

  • driver behavior model
  • driver reaction
  • intelligent transportation systems
  • traffic simulation
  • vehicular safety simulation

Fingerprint

Dive into the research topics of 'Augmented driver behavior models for high-fidelity simulation study of crash detection algorithms'. Together they form a unique fingerprint.

Cite this