Physica A: Statistical Mechanics and its Applications最新文献_第2页

Study on pedestrian evacuation simulation model considering group behavior 考虑群体行为的行人疏散模拟模型研究

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-09 DOI: 10.1016/j.physa.2024.130138

As a crowded place on the university campus, the cafeteria inevitably has many safety hazards, such as fire accidents caused by open flames and large appliances, stampede accidents caused by overcrowding during peak dining hours, etc. Therefore, studying pedestrian evacuation in university campus cafeterias is particularly necessary. Pedestrians on campus mostly travel in groups. Previous studies mainly used continuous models to discuss pedestrian group evacuation behavior. In this study, based on the cellular automaton pedestrian evacuation simulation model, the floor field calculation method was improved. A cellular automaton pedestrian evacuation simulation model considering group behavior was established and applied to the evacuation scenario of students in a university campus cafeteria. The study found that under the different group configurations, the pedestrian ratios, and the pedestrian densities, the pedestrian evacuation efficiency had significant differences. The results showed that when the different group configurations existed in the scenario, the higher the proportion of the pedestrians with three-person front-to-back group configurations, the higher the evacuation efficiency. When only one type of the group configuration existed in the scenario, at low pedestrian density, the evacuation efficiency of the individual pedestrian groups was higher compared to the other six group configurations. While at high pedestrian density, the evacuation efficiency of the three-person front-to-back group configurations was higher. These findings provided important references for pedestrian evacuation in university campus cafeterias and provided insights for the simulation research of group pedestrian evacuation models, contributing to enhancing campus safety management and ensuring the safety of teachers, students, and staff.

食堂作为大学校园中的人员密集场所，不可避免地存在着许多安全隐患，如明火和大型电器引发的火灾事故、就餐高峰期因拥挤引发的踩踏事故等。因此，研究大学校园食堂的行人疏散问题尤为必要。校园内的行人多为集体出行。以往的研究主要采用连续模型来讨论行人群体疏散行为。本研究以蜂窝自动机行人疏散模拟模型为基础，改进了楼层场计算方法。建立了考虑群体行为的蜂窝自动机行人疏散仿真模型，并将其应用于大学校园食堂的学生疏散场景。研究发现，在不同的群体配置、行人比例和行人密度下，行人疏散效率存在显著差异。结果表明，当场景中存在不同的群体配置时，三人前后群体配置的行人比例越高，疏散效率越高。当场景中只存在一种群体配置时，在行人密度较低的情况下，与其他六种群体配置相比，单个行人群体的疏散效率较高。而在行人密度较高的情况下，三人前后分组配置的疏散效率较高。这些研究结果为大学校园食堂的行人疏散提供了重要参考，也为群体行人疏散模型的模拟研究提供了启示，有助于加强校园安全管理，保障师生员工的安全。

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引用次数: 0

Pattern recognition of drying lysozyme–glucose droplets using machine learning classifiers 利用机器学习分类器对干燥溶菌酶-葡萄糖液滴进行模式识别

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-09 DOI: 10.1016/j.physa.2024.130141

Out-of-equilibrium processes, such as sessile droplet drying, often result in distinctive macroscopic residual patterns in systems containing molecules, proteins, and colloids. Protein–glucose mixtures are particularly effective models for studying the behavior of complex fluids containing biomolecules. This study investigates the drying patterns of lysozyme droplets with varying initial glucose concentrations. Without glucose, the crack patterns are chaotic and dispersed throughout the droplet. Interestingly, cracks predominantly form around the droplet edges at intermediate glucose concentrations, while the deposits become uniform and crack-free at high glucose concentrations. To understand and classify the unique patterns related to the initial compositional changes, we developed an automated pattern recognition pipeline. We used two methods for analyzing images captured throughout the drying process. The first method involved extracting statistical textural parameters from the images as quantitative features for machine learning classifiers. The second method utilized a neural network-based classifier to directly classify the images, achieving an accuracy of 97%. The results demonstrate the effectiveness of using images from the entire drying process, not just the final images, for pattern classification. This approach may be useful in gaining a fundamental understanding of unique crack pattern that emerge when glucose is added to a protein solution.

在含有分子、蛋白质和胶体的系统中，失衡过程（如无柄液滴干燥）通常会导致独特的宏观残留模式。蛋白质-葡萄糖混合物是研究含有生物分子的复杂流体行为的特别有效的模型。本研究调查了不同初始葡萄糖浓度的溶菌酶液滴的干燥模式。在不含葡萄糖的情况下，裂纹模式是混乱的，并且分散在整个液滴中。有趣的是，在中等葡萄糖浓度下，裂纹主要在液滴边缘形成，而在高葡萄糖浓度下，沉积物变得均匀且无裂纹。为了了解与最初成分变化有关的独特模式并对其进行分类，我们开发了一种自动模式识别管道。我们使用了两种方法来分析整个干燥过程中捕获的图像。第一种方法是从图像中提取统计纹理参数，作为机器学习分类器的定量特征。第二种方法利用基于神经网络的分类器直接对图像进行分类，准确率达到 97%。结果表明，使用整个干燥过程中的图像（而不仅仅是最终图像）进行模式分类非常有效。这种方法可能有助于从根本上了解在蛋白质溶液中添加葡萄糖时出现的独特裂纹模式。

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引用次数: 0

Assessing movement-specific resilience of a signalized road network under lane-level cascading failure 评估信号灯路网在车道级连环故障下的特定运动弹性

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-09 DOI: 10.1016/j.physa.2024.130154

Accurately assessing the resilience of the road network is crucial for responding to emergencies and enhancing public safety. Signal control plays a significant role in managing traffic flow. However, its impact is often overlooked in resilience assessments, where traffic flow and signal control are usually considered separately. A Movement-Specific Resilience (MSR) assessment model is proposed to integrate signal timing into resilience analysis. To accurately represent traffic flow paths under phase control, a dual graph is used to depict the topological network, allowing the assessment of relationships among all movements at an intersection. Based on this, a cascading failure model is developed to analyze the impact of signal control on traffic flow reassignment, reflecting how signal timing influences traffic flow propagation after failures. The method is validated using data collected from a sub-road network in Xi’an city. Results reveal the cumulative resilience of single lanes is not equivalent to the resilience of road segments. The MSR is higher when the network’s failure degree is low and decreases as the failure level increases. Furthermore, road saturation is inversely related to MSR, while MSR is proportional to capacity. MSR remains unaffected by failures and oversaturation when capacity exceeds a certain threshold. These insights could be a theoretical foundation for bolstering resilience via signal control adjustments.

准确评估道路网络的恢复能力对于应对紧急情况和加强公共安全至关重要。信号控制在管理交通流量方面发挥着重要作用。然而，在复原力评估中，交通流和信号控制通常被分开考虑，其影响往往被忽视。本文提出了一种特定运动复原力（MSR）评估模型，将信号配时纳入复原力分析中。为了准确表示相位控制下的交通流路径，采用了二元图来描述拓扑网络，从而可以评估交叉口所有运动之间的关系。在此基础上，开发了一个级联故障模型，用于分析信号控制对交通流重新分配的影响，反映信号配时如何影响故障后的交通流传播。该方法利用从西安市子路网收集的数据进行了验证。结果表明，单车道的累积恢复能力并不等同于路段的恢复能力。当路网的故障程度较低时，MSR 较高，随着故障程度的增加，MSR 降低。此外，道路饱和度与 MSR 成反比，而 MSR 与通行能力成正比。当容量超过一定阈值时，MSR 不受故障和过饱和的影响。这些见解可以作为通过信号控制调整来增强弹性的理论基础。

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引用次数: 0

Multimodal adversarial Informer for highway vehicle lane-changing trajectory prediction 用于公路车辆变道轨迹预测的多模式对抗信息器

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-09 DOI: 10.1016/j.physa.2024.130158

To enhance the perception of vehicle trajectory information and lane-changing decision-making capabilities in intelligent connected vehicles during multivehicle interaction scenarios, we propose a novel method based on a Multimodal Adversarial Informer (MAI) for highway multivehicle lane-changingrajectory prediction. This method achieves spatiotemporal features of target and surrounding vehicles through graph learning of temporal features and spatial adjacency matrices. Considering the heading angle and vehicle local X-axis displacement, the vehicle trajectory samples are categorized for training and validation of the multimodal Informer. A multi-criterion discriminator is utilized to judge whether the generated trajectory fits the requirements of accuracy and rationality. After adversarial learning, the optimal vehicle lane-changing trajectory prediction is obtained using the proposed MAI. Experiments conducted with the NGSIM dataset demonstrate the comparative performance of baseline models on three different noise-added testing datasets using MAE, RMSE, and R² metrics. The MAI model consistently outperforms the others, achieving the lowest MAE and RMSE and the highest R² values across all datasets, indicating superior predictive accuracy and fit. Furthermore, the results show that the proposed MAI framework maintains a relatively low prediction error over both short-term and long-term horizons compared to baseline models.

为了增强智能网联汽车在多车交互场景中对车辆轨迹信息的感知和变道决策能力，我们提出了一种基于多模态对抗信息器（MAI）的高速公路多车变道轨迹预测新方法。该方法通过对时间特征和空间邻接矩阵的图学习，获得目标车辆和周围车辆的时空特征。考虑到航向角和车辆局部 X 轴位移，对车辆轨迹样本进行分类，以便对多模态信息器进行训练和验证。利用多标准判别器来判断生成的轨迹是否符合准确性和合理性的要求。经过对抗学习后，利用所提出的 MAI 获得最佳车辆变道轨迹预测。使用 NGSIM 数据集进行的实验表明，在三个不同的噪声添加测试数据集上，基线模型使用 MAE、RMSE 和 R² 指标进行了性能比较。MAI 模型的性能始终优于其他模型，在所有数据集上都获得了最低的 MAE 和 RMSE 值以及最高的 R² 值，表明其预测准确性和拟合度都非常出色。此外，结果表明，与基线模型相比，拟议的 MAI 框架在短期和长期范围内都能保持相对较低的预测误差。

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引用次数: 0

Impact of Black Swan Events on Ethereum blockchain ERC20 token transaction networks 黑天鹅事件对以太坊区块链 ERC20 代币交易网络的影响

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-05 DOI: 10.1016/j.physa.2024.130129

The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system’s dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader’s behavior during the Black Swan Events – 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals an increase in diverse interaction among the traders and a greater adoption of ERC20 tokens in a maturing Ethereum ERC20 financial ecosystem after the Crypto Crash 2018 and the COVID-19 pandemic. Before the crash and the COVID-19 pandemic, most traders interacted with other traders in an isolated or restricted manner, with each trader focusing solely on either buying or selling activities. However, after the crash and during the pandemic, most traders diversely interacted among themselves by participating in both buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.

以太坊区块链及其 ERC20 代币标准彻底改变了数字资产和去中心化应用的格局。ERC20代币是可编程、可互操作的代币，支持各种应用和代币经济。交易图代表了以太坊网络中钱包之间的价值流动，在理解系统动态（如代币转移和交易者行为）方面发挥了至关重要的作用。在此，我们探索了ERC20代币交易的每日交易图的演变，这揭示了交易者在黑天鹅事件--2018年加密货币崩盘和COVID-19大流行期间的行为。通过使用网络科学和微分几何的工具，我们分析了从 2015 年 11 月到 2023 年 1 月的 0.98 亿 ERC20 代币交易数据。我们的分析表明，在2018年加密货币崩盘和COVID-19大流行之后，交易者之间的多样化互动增加，在成熟的以太坊ERC20金融生态系统中，ERC20代币的采用率更高。在崩盘和 COVID-19 大流行之前，大多数交易者以孤立或受限的方式与其他交易者互动，每个交易者只专注于买入或卖出活动。然而，在股灾后和大流行期间，大多数交易商通过参与买卖活动进行了多样化的互动。此外，我们观察到 COVID-19 大流行对金融生态系统中的用户行为没有明显的负面影响。

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引用次数: 0

Node classification based on Attribute Fuse Edge Features and Label Adaptive Adjustment 基于属性融合边缘特征和标签自适应调整的节点分类

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-05 DOI: 10.1016/j.physa.2024.130131

Most of existing graph representation learning methods only extract information from nodes and ignore the hidden information of edges. Nodes carry weak structural information thus affecting the specificity of node embeddings. To solve these problems, this paper proposes a node classification algorithm based on Attribute Fuse Edge Features and Label Adaptive Adjustment (AFEF_LAA). Firstly, Intimate-Relationship-Attribute of node is designed based on edge embeddings. Rz-Cos rule is constructed to perform the similarity metric between nodes and their neighbors to select intimate neighbor nodes. After that Reverse-TransE is constructed to encode embedding vectors of the edges connected to intimate neighborhood nodes. Secondly, a multi-fusion method based on smoothed neighborhood information is constructed. Each node in the original graph is smoothed together with its neighbor nodes. The smoothed original graph is multi-fused with multiple twin graphs. Finally, a strategy of label adaptive adjustment is proposed to select the label embedding vectors for input to the next-generation trainer by comparing accuracy. This strategy can improve the quality of graph embeddings while effectively avoiding the overfitting problem when processing high-dimensional data. AFEF_LAA is compared with the state-of-the-art algorithms on six graph datasets. Experimental results show that AFEF_LAA can achieve higher node classification accuracy.

现有的图表示学习方法大多只提取节点信息，而忽略了边的隐藏信息。节点携带的结构信息较弱，从而影响了节点嵌入的特异性。为了解决这些问题，本文提出了一种基于属性融合边缘特征和标签自适应调整（AFEF_LAA）的节点分类算法。首先，基于边缘嵌入设计节点的亲密关系属性（Intimate-Relationship-Attribute）。构建 Rz-Cos 规则来执行节点与其邻居之间的相似度量，从而选择亲密的邻居节点。然后，构建 Reverse-TransE 来编码与近邻节点相连的边的嵌入向量。其次，构建基于平滑邻域信息的多重融合方法。原始图中的每个节点都与其邻近节点一起进行平滑处理。平滑后的原始图与多个孪生图进行多重融合。最后，提出了一种标签自适应调整策略，通过比较准确性来选择标签嵌入向量，作为下一代训练器的输入。这种策略可以提高图嵌入的质量，同时有效避免处理高维数据时的过拟合问题。AFEF_LAA 在六个图数据集上与最先进的算法进行了比较。实验结果表明，AFEF_LAA 可以获得更高的节点分类准确率。

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引用次数: 0

Quantum Representation based Preference Evolution Network for E-commerce recommendation 基于量子表示的偏好演化网络用于电子商务推荐

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-05 DOI: 10.1016/j.physa.2024.130155

Quantum theory, originally developed to explain microscopic physical systems, has recently emerged as a novel conceptual and mathematical framework in information science. This paper applies quantum theory to address challenges in E-commerce recommendation, specifically those involving sequential behavior, aiming to mine effective patterns of preference evolution and more accurately predict user interests. Current recommender systems are limited by the sequence length and underutilize side information such as item attributes. To address these issues, we propose a Quantum Representation-based Preference Evolution Network (QRPEN) for E-commerce recommendations. Unlike traditional methods that focus solely on item-ID, our approach integrates a comprehensive set of side information, including both item-ID and attribute data, at each timestamp. We represent item attributes using quantum superposition states and employ density matrices to describe the probability distribution of same-type attributes. These matrices are then transformed into vectors through a quantum measurement-inspired process and fed into a Quasi-RNN model, enabling parallelization and the modeling of longer sequences. This approach effectively captures the dynamic evolution of user preferences. Experiments on public E-commerce datasets demonstrate that QRPEN achieves competitive performance.

量子理论最初是用来解释微观物理系统的，最近已成为信息科学中一种新颖的概念和数学框架。本文应用量子理论来应对电子商务推荐中的挑战，特别是那些涉及序列行为的挑战，旨在挖掘有效的偏好演变模式，更准确地预测用户兴趣。当前的推荐系统受到序列长度的限制，并且没有充分利用商品属性等附带信息。为了解决这些问题，我们提出了一种用于电子商务推荐的基于量子表征的偏好演化网络（QRPEN）。与只关注商品 ID 的传统方法不同，我们的方法在每个时间戳整合了一整套侧信息，包括商品 ID 和属性数据。我们使用量子叠加态来表示物品属性，并采用密度矩阵来描述同类属性的概率分布。然后，通过量子测量启发过程将这些矩阵转换为向量，并输入准 RNN 模型，从而实现并行化和更长序列的建模。这种方法能有效捕捉用户偏好的动态演变。在公共电子商务数据集上的实验证明，QRPEN 实现了具有竞争力的性能。

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引用次数: 0

Activity centrality-based critical node identification in complex systems against cascade failure 基于活动中心性的复杂系统关键节点识别，防止级联失效

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-05 DOI: 10.1016/j.physa.2024.130121

Identifying critical nodes in the network has been a concern permanently. Cascading failure would cause catastrophic events, and in the field of cascading failure in complex networks, the structure and dynamics are considered as the key in the process of cascading failure. It is vital to have an applicable centrality to find critical nodes that could control and prevent the cascading failure. In this paper, we propose a steady-state activity centrality to evaluate the importance of each node, and the proposed centrality is related to the degree of each node and the activity of its neighbor nodes. The giant component, the average activity, and the tipping point under different attack strategies are introduced to compare the attack effect of these three centralities including steady-state activity centrality, betweenness centrality and closeness centrality. The results show that the attack effect under the proposed centrality is better than the effect under the other two centralities. In particular, for the network with the SIS and gene regulation dynamic, the attack effect under the steady-state activity centrality driven strategy is obviously better than the effect under the betweenness centrality driven strategy when the network is heterogeneous.

识别网络中的关键节点一直是人们关注的问题。级联失效会导致灾难性事件，而在复杂网络的级联失效领域，结构和动力学被认为是级联失效过程中的关键。要找到能控制和防止级联失效的关键节点，关键是要有一个适用的中心度。本文提出了一种稳态活动中心度来评估每个节点的重要性，所提出的中心度与每个节点的度和其相邻节点的活动相关。通过引入不同攻击策略下的巨分量、平均活跃度和临界点，比较了稳态活动中心度、间度中心度和接近度中心度等三种中心度的攻击效果。结果表明，建议中心度下的攻击效果优于其他两种中心度下的效果。特别是对于具有 SIS 和基因调控动态的网络，在网络异质性的情况下，稳态活动中心性驱动策略下的攻击效果明显优于间度中心性驱动策略下的效果。

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引用次数: 0

Self-oscillating open quantum systems 自振荡开放量子系统

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-05 DOI: 10.1016/j.physa.2024.130139

Evolution of occupation number is studied for a bosonic oscillator (with one and two degrees of freedom) linearly fully coupled to fermionic and bosonic heat baths. The lack of equilibrium in this oscillator is discussed in the light of the creation of an energy source. The connection of such a system with known nonlinear self-oscillating systems is shown.

研究了与费米子和玻色子热浴线性完全耦合的玻色子振荡器（具有一个和两个自由度）的占位数演变。从能量源的产生角度讨论了该振荡器缺乏平衡的问题。还展示了这种系统与已知非线性自振荡系统的联系。

引用次数: 0

Study on mixed traffic characteristics around highway on-ramp bottleneck using a microscopic simulation model 利用微观模拟模型研究高速公路匝道瓶颈附近的混合交通特征

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2024-10-03 DOI: 10.1016/j.physa.2024.130134

In the early mixed traffic environment, connected and automated vehicles (CAVs) tend to follow simple control rules for the sake of traffic safety and stability. Comprehensive analysis of overall mixed traffic performance and vehicle to vehicle interactions around highway on-ramp bottleneck is a basis for further traffic management and control. And yet CAVs in existing researches are mainly in the form of cooperative vehicular platoon, and mixed traffic scenarios within simulation software are not applicable for in-depth investigation. The purpose of this paper is to develop a microscopic simulation model to study in detail lane-based mixed traffic performance around the highway on-ramp. This model firstly considers vehicle characteristics of individual human vehicles (HVs) and CAVs by combining different microscopic traffic models. After the hypothetical on-ramp bottleneck structure is constructed, various simulation scenarios are developed under varying traffic volumes and changing market penetration rates (MPRs) of CAVs. Simulation results show that mixed traffic flow is improved in terms of congestion patterns and traffic capacity. For oscillating and nearly homogeneous congested traffic, congestion degrees are greatly reduced when CAV MPR above 30 % and 50 % respectively. Mixed traffic capacity is increased by 19.3 % when a smaller desired time gap set for CAVs, while it shows no significant change in a larger value. In the HV-HV interactions, traffic conflicts are slightly influenced by CAVs. Comparatively, conflict situations in HV-CAV interactions get worse, the proportion of time to collision (TTC) greater than 2 s monotonically declining with the rise in CAV MPR. It is concluded that traffic characteristics overall show a good momentum when MPR of CAV and the desired time gap of CAVs in mixed traffic are appropriate.

在早期的混合交通环境中，出于交通安全和稳定性的考虑，联网和自动驾驶车辆（CAV）倾向于遵循简单的控制规则。综合分析高速公路匝道瓶颈周围混合交通的整体表现和车与车之间的相互作用，是进一步进行交通管理和控制的基础。然而，现有研究中的 CAV 主要以合作车辆排的形式出现，仿真软件中的混合交通场景并不适用于深入研究。本文旨在开发一种微观仿真模型，详细研究高速公路匝道周边基于车道的混合交通性能。该模型首先通过结合不同的微观交通模型，考虑了单个人类车辆（HV）和 CAV 的车辆特性。在构建了假设的匝道瓶颈结构后，在不同的交通流量和不断变化的 CAV 市场渗透率（MPRs）条件下开发了各种模拟场景。模拟结果表明，混合交通流在拥堵模式和交通容量方面都得到了改善。对于振荡和近乎均匀的拥堵交通，当 CAV MPR 分别超过 30% 和 50% 时，拥堵程度会大大降低。当为 CAV 设定的期望时间间隙较小时，混合交通容量增加了 19.3%，而当设定的期望时间间隙较大时，混合交通容量则没有明显变化。在 HV-HV 的相互作用中，交通冲突受到 CAV 的轻微影响。相对而言，HV-CAV 相互作用中的冲突情况更严重，碰撞时间（TTC）大于 2 秒的比例随着 CAV MPR 的增加而单调下降。结论是，当 CAV 的 MPR 和混合交通中 CAV 所需的时间间隙合适时，交通特征总体上呈现出良好的势头。

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引用次数: 0