Paper ThAT11.1
Han, Xiao (Tongji University), Shao, Minhua (Tongji University), Sun, Lijun (Tongji University)
Coordinated Control of Green Waves and Vehicle Speed of High-Saturation Artery for Mixed Traffic Flow with CAV and HDV
Scheduled for presentation during the Regular Session "Road Traffic Control II" (ThAT11), Thursday, September 26, 2024,
10:30−10:50, Salon 19/20
2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada
This information is tentative and subject to change. Compiled on December 26, 2024
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Keywords Theory and Models for Optimization and Control, Road Traffic Control, Simulation and Modeling
Abstract
To address urban arterial congestion, enhancing road capacity and flow matching is crucial, achievable by increasing vehicle speed and improving headway. For the former, green wave coordination to boost vehicle speed, capacity and efficiency is common but limited by the inability of Human Driven Vehicles (HDV) to follow the green wave speed accurately. Recently Connected and Autonomous Vehicles (CAV) bring new prospects for control, accurately controlling speed and coordinating with signal, while improving the headway, thus comprehensively boosting capacity. Many proposed signal and vehicle coordination models for mixed flow with CAV, but few express capacity improvement principles directly and their applicability under high saturation is insufficient. This study proposes a coordinated control model of green wave and vehicle speed for mixed CAV and HDV flow, integrating vehicle speed control and headway improvement into two classic green wave models to maximize "flow×speed" for signal and speed optimization. Then these two models are tested under varying saturations, intersection spacings, and CAV penetration rates. The results demonstrate superior improvement effects in delay, speed, and flow compared to isolated control, even under high saturations. Moreover, increasing CAV permeability enhances the marginal benefits of improvement. This provides insights for establishing control rules across different CAV penetration rates, time, and regions within cities.
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