Joint Deployment of Infrastructure-Assisted Traffic Management and Cooperative Driving around Work Zones

Evangelos Mintsis, L. Lücken, V. Karagounis, Kallirroi N. Porfyri, Michele Rondinone, A. Correa, Julian Schindler, E. Mitsakis
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引用次数: 2

Abstract

Highway work zones can induce significant delays and undermine traffic safety. The recent advent of connected and automated vehicles (CAVs) can pose an additional threat to traffic flow performance and safety around highway work zones. CAVs equipped with low – medium level automation systems that cannot reliably address work zone scenarios under all circumstances could induce control transitions and imminent Minimum Risk Manoeuvers (MRMs) that would result in significant traffic disruption and multiple safety critical events. The latter negative effects could be mitigated via the introduction of highly automated vehicles that could utilize sophisticated infrastructure assistance to traverse highway work zones without disengaging automation systems. This study develops novel and utilizes existing vehicle-driver models to simulate manual driving, mixed traffic and infrastructure-assisted highly automated traffic around highway work zones. Traffic operations are evaluated for the latter fleet mixes and three different traffic demand levels. Simulation results indicate that joint deployment of infrastructure-assisted traffic management and cooperative driving can ensure increased traffic efficiency and safety levels for high traffic intensity in a fully connected and automated road environment.
基础设施辅助交通管理与工作区周边协同驾驶的联合部署
高速公路工作区域可能造成严重延误,破坏交通安全。最近出现的联网和自动驾驶汽车(cav)可能会对高速公路工作区域周围的交通流性能和安全构成额外的威胁。配备中低水平自动化系统的自动驾驶汽车不能在所有情况下可靠地处理工作区域场景,可能会导致控制过渡和迫在眉睫的最小风险操纵(MRMs),从而导致严重的交通中断和多个安全关键事件。后一种负面影响可以通过引入高度自动化的车辆来减轻,这些车辆可以利用复杂的基础设施辅助,在不脱离自动化系统的情况下穿越高速公路工作区域。本研究开发并利用现有的车辆驾驶员模型来模拟高速公路工作区域周围的手动驾驶、混合交通和基础设施辅助的高度自动化交通。对后一种机队组合和三种不同的交通需求水平进行交通运营评估。仿真结果表明,在全互联、自动化道路环境下,基础设施辅助交通管理与协同驾驶的联合部署可以确保在高交通强度下提高交通效率和安全水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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