Modelling the fundamental diagram of traffic flow mixed with connected vehicles based on the risk potential field

IF 2.3 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Jiacheng Yin, Peng Cao, Zongping Li, Linheng Li, Zhao Li, Duo Li
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引用次数: 0

Abstract

The fundamental diagram (FD) of traffic flow can effectively characterize the macroscopic characteristics of traffic flow and provide a theoretical foundation for traffic planning and control. The rapid development of connected vehicles (CVs) has led to changes in traffic flow characteristics. However, research on the FD of traffic flow involving CVs and non-connected vehicles (NCVs) is still in its early stages. Most FDs do not well characterize the motion behaviour of different vehicles, nor do they study the interaction between mixed vehicles. Therefore, in this study, the FD of mixed traffic flows (i.e. with CVs and NCVs) was constructed within a unified framework. First, the car-following behaviours of CVs and NCVs were modelled based on risk potential field theory. Subsequently, the FD of mixed traffic flows was derived based on the relationship between car-following behaviour and the macroscopic traffic flow under steady-state conditions. To validate the model, rigorous verifications were conducted via numerical experiments using the Monte Carlo method. The results indicate significant agreement between the scatter plots obtained from the experiments and the theoretical curves for different penetration rates. The proposed FD has a unified framework and a more rigorous mathematical structure.

Abstract Image

基于风险潜势场的互联车辆混合交通流基本图建模
交通流基本图(FD)能有效描述交通流的宏观特征,为交通规划和控制提供理论基础。联网汽车(CVs)的快速发展导致交通流特征发生变化。然而,涉及 CV 和非联网车辆(NCV)的交通流 FD 研究仍处于早期阶段。大多数 FD 没有很好地描述不同车辆的运动行为,也没有研究混合车辆之间的相互作用。因此,本研究在一个统一的框架内构建了混合交通流(即有 CV 和 NCV 的混合交通流)的 FD。首先,根据风险势场理论对 CV 和 NCV 的跟车行为进行建模。随后,根据稳态条件下汽车跟随行为与宏观交通流之间的关系,推导出混合交通流的 FD。为了验证该模型,使用蒙特卡罗方法通过数值实验进行了严格验证。结果表明,实验得到的散点图与不同渗透率下的理论曲线之间存在明显的一致性。所提出的 FD 具有统一的框架和更严格的数学结构。
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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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