Author Type

Graduate Student

Date of Award

2023

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Kan, David

Abstract

Mainstream vehicles sold today are equipped with the Advanced Driver Assistance System (ADAS) known as Adaptive Cruise Control (ACC). ACC automatically adjusts speeds and maintains a safe following distance with the preceding vehicle. This enables partial automation by automating longitudinal car-following. Despite the ever-increasing market penetration, ACC-equipped vehicles will likely operate in a mixed environment with other human-driven vehicles first. However, the traffic flow impact of human driver behavior when following ACC-equipped vehicles is largely unknown, and it is uncertain whether this deserves special consideration when modeling human driver behavior near ACC enabled vehicles. This study conducted a preliminary real-world experiment on a freeway (a portion of Interstate 95) and an urban arterial (a portion of state route A1A) to investigate the human driver behavior with and without the presence of vehicles in ACC mode as the leaders. This unbiased experiment was conducted in naturalistic traffic conditions. Results from the field experiments demonstrate that in a mixed environment with ACC-equipped vehicles as leaders, the human driven vehicles as the follower adopt similar headway, spacing, and acceleration on both freeway and arterial, with no statistically significant difference. The only exception is when traveling at speeds below 15 mph on urban arterials, where human drivers adopt significantly larger spacing while following ACC-enabled vehicles. We expect that findings from these field experiments will provide important initial insights to future research on human driver car following models in a mixed traffic environment and dedicated lanes for automated vehicles.

Extent

91 p.

Comments

Includes bibliography.|Thesis (MS)--Florida Atlantic University, 2023.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00014190

Format

pdf

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