Gap setting control strategy for connected and automated vehicles in freeway lane‐drop bottlenecks

Author:

Chung Sungyong1ORCID,Ka Dongju12ORCID,Kim Yongju34ORCID,Lee Chungwon2ORCID

Affiliation:

1. Institute of Construction and Environmental Engineering Seoul National University Gwanak‐gu Seoul Republic of Korea

2. Department of Civil and Environmental Engineering Seoul National University Gwanak‐gu Seoul Republic of Korea

3. Institute of Engineering Research Seoul National University Gwanak‐gu Seoul Republic of Korea

4. Department of Civil and Environmental Engineering University of Wisconsin‐Madison Madison Wisconsin USA

Abstract

AbstractCommercial automated vehicles equipped with adaptive cruise control (ACC) systems offer multiple gap settings that determine their longitudinal behaviour. This study introduces two novel strategies—inflow control and combined control—that leverage the distinct driving behaviours associated with different gap settings in connected and automated vehicles. These strategies aim to enhance traffic efficiency in freeway lane‐drop bottlenecks, where capacity drops are common, by maintaining bottleneck occupancy at the target level using a proportional‐integral‐derivative controller. Simulation experiments were conducted using VISSIM to validate the proposed strategies. The results from a hypothetical lane‐drop bottleneck indicate that the proposed strategies enhanced both efficiency and safety across all simulated demand levels, with the combined control outperforming inflow control by redistributing the relative positions of vehicles before the mandatory lane changes using a new gap setting. Moreover, the proposed strategies were effective under all the simulated market penetration rates (MPRs), where better performances were demonstrated at higher MPRs. An evaluation of a calibrated real‐world network further demonstrated the potential of recommending gap settings to drivers of ACC‐equipped vehicles using variable message signs to enhance freeway efficiency in the near future.

Funder

National Research Foundation of Korea

Institute of Construction and Environmental Engineering, Seoul National University

Institute of Engineering Research, Seoul National University

Publisher

Institution of Engineering and Technology (IET)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3