A Micro-simulation Framework for Studying CAVs Behavior and Control Utilizing a Traffic Simulator, Chassis Simulation, and a Shared Roadway Friction Database

Liming Gao, Srivenkata Satya Prasad Maddipatla, Craig Beal, Kshitij Jerath, Cindy Chen, Lorina Sinanaj, Hossein Haeri, Sean Brennan

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

Abstract

The ability of connected and autonomous vehicles (CAVs) to share information such as road friction and geometry has the potential to improve the safety, capacity, and efficiency of roadway systems, and the study of these systems often necessitates synergistic investigation of the vehicle, traffic behavior, and road conditions. This paper presents a micro-simulation framework for studying CAVs behavior and control utilizing a traffic simulator, chassis simulation, and a shared roadway friction database. The simulation utilizes three levels of data representations: 1) a traffic representation that explains how vehicles interact with each other and follow location-specific rules of the road, 2) a vehicle dynamic representation of the Newtonian response of the vehicle to driver inputs interacting with the vehicle which in turn interacts with the pavement, and finally 3) a road surface representation that represents how friction of roadway changes with space and time. The interactions between these representations are mediated by a spatiotemporal database. The framework is demonstrated through a CAVs application example showing how the mapping of road friction enables advanced vehicle control by allowing the database-mediated preview of road friction. This framework extends readily to real-time implementation on actual CAVs systems, providing great potential for improving CAVs control performance and stability via database-mediated feedback systems, not only in simulation, but also in practice.

Original languageEnglish (US)
Title of host publication2021 American Control Conference, ACC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1650-1655
Number of pages6
ISBN (Electronic)9781665441971
DOIs
StatePublished - May 25 2021
Event2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States
Duration: May 25 2021May 28 2021

Publication series

NameProceedings of the American Control Conference
Volume2021-May
ISSN (Print)0743-1619

Conference

Conference2021 American Control Conference, ACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans
Period5/25/215/28/21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Micro-simulation Framework for Studying CAVs Behavior and Control Utilizing a Traffic Simulator, Chassis Simulation, and a Shared Roadway Friction Database'. Together they form a unique fingerprint.

Cite this