Framework for Simulating Vehicle Automation and Cooperation in Freeway Merging Operations

Authors

Hector Donaldo Mata, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Civil Engineering

First Advisor's Name

Mohammed Hadi

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Albert Gan

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Xia Jin

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Priyanka Alluri

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Florence George

Fifth Advisor's Committee Title

Committee member

Keywords

Autonomous Driving Systems, Cooperative Driving Automation, Autonomous Vehicles, Model Predictive Control, Cooperative Adaptive Cruise Control, Ramp Metering, Freeway Merging Operations, Adaptive Cruise Control, Simulation Framework

Date of Defense

6-30-2023

Abstract

Simulation and modeling are critical for testing and evaluating automated driving systems (ADS) and cooperative driving automation (CDA). Co-simulation platforms that integrate multiple simulation tools and models can consider and assess the impacts of elements like vehicle dynamics, sensor configurations, perception algorithms, and wireless communications. However, their high computational needs restrict them from focusing on individual vehicle dynamics and short simulation periods, limiting their ability to assess the wider systemic impacts of autonomous vehicles (AV) and CDA technologies. While microscopic simulation tools are commonly utilized for evaluating system-level effects, research and implementation of advanced algorithms for emulating AV or CDA within microsimulation models is limited, leaving the larger impacts on traffic flow insufficiently assessed.

Aiming to address the identified research gap, a holistic simulation modeling framework and methodology are introduced. The framework utilizes advanced control algorithms found in co-simulation platforms and adapts them for implementation in microsimulation software, allowing for a comprehensive evaluation of the broad impacts of AV and CDA on traffic systems.

The proposed framework emphasizes the evaluation of AV and CDA technologies in merging operations, including their interactions with ramp metering. It involves data collection from detectors, AV, and CDA vehicles to support the ramp metering algorithm within the developed framework. In addition, the framework involves the use of a model predictive control (MPC) algorithm to optimize the merging tasks and the incorporation of adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) to emulate the autonomous and cooperative behavior of AV and CDA vehicles. This dissertation then applies the framework to a case study to demonstrate its effectiveness in simulating freeway merging operations in the presence of AV and CDA technologies. This demonstration confirms the framework's ability to generate consistent and logical results.

This dissertation contributes to transportation research by thoroughly analyzing CDA, its infrastructure support, and developing a simulation framework to emulate AV and CDA behavior. As such, this study provides a robust framework that enhances the comprehension of AV and CDA technologies, their potential to improve traffic operations, and their interactions with infrastructure-based management strategies, thereby supporting future research in this field.

Identifier

FIDC011129

ORCID

https://orcid.org/0000-0002-8435-0635

Recommended Citation

Mata, Hector Donaldo, "Framework for Simulating Vehicle Automation and Cooperation in Freeway Merging Operations" (2023). FIU Electronic Theses and Dissertations. 5446.
https://digitalcommons.fiu.edu/etd/5446