Maximum traffic

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Of IFT. In addition, our method incorporates the emergence probability of each subsystem, which relies on maximum platoon size and penetration rates. This unified method facilitates our analysis of both two types of IFT: “looking ahead” (MPF) and “looking behind” (MSL), in contrast to existing research that focuses on “looking ahead” only (Yu et al., 2023). In addition, while previous studies on platoon sizes address the case of pure-CAV platoons (Zhou and Zhu, 2021, Yao et al., 2023), our research provides the first insight into the influence of maximum platoon size for mixed platoons on the entire traffic flow.•Through extensive numerical studies and nonlinear traffic simulations, our results reveal that for IFT, compared to the prevalent choice of “looking ahead”, the “looking behind” could allow for further enhanced capabilities of CAVs in improving traffic stability at low CAV penetration rates. For maximum platoon size, it is revealed that increasing platoon sizes could bring better traffic flow stability, but with a diminishing improvement. These findings offer practical insights into how to identify the optimal maximum platoon size for mixed platooning with both CAVs and HDVs in mixed traffic flow. In addition, considering that some traditional HDVs (T-HDVs) lack communication capabilities, the performance of the mixed platoons in improving traffic flow stability is significantly reduced when using the “looking ahead” (MPF) IFT or the “looking behind” (MSL) IFT. However, this adverse effect is negligible when the CAV penetration rate reaches 50%.The rest of this paper is organized as follows. Section 2 introduces the definitions of IFT and maximum platoon size, partition of mixed traffic flow, and presents the emergence probability of each subsystem. Section 3 introduces the dynamical modeling of the mixed traffic system. The unified method for stability analysis is shown in Section 4, followed by numerical analysis in Section 5. Section 6 presents traffic simulations, and Section 7 concludes this paper.Section snippetsProblem statementThis paper considers a single-lane mixed traffic scenario led by a head vehicle, with CAVs, connected HDVs (C-HDVs), and traditional HDVs (T-HDVs) randomly distributed, as shown in Fig. 3. The head vehicle is indexed as 0, and other

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Vehicles are indexed from 1 to N against the moving direction, including m CAVs and N−m HDVs. Define Ω={1,2,…,N} as the index set of all the following vehicles, and Υ={i1,i2,…,im}⊆Ω as the index set of all the CAVs, with i1i2⋯im represent the indices (and alsoDynamical modeling of mixed traffic flowIn this section, three types of subsystems, including independent HDVs, independent CAVs, and mixed platoons, are modeled to describe the dynamics of the mixed traffic flow.Unified method for stability analysisIn this section, a unified method is proposed for the stability analysis of mixed traffic flow under different types of IFT and maximum platoon sizes. Then, specific models are selected for the three subsystems: independent HDVs, independent CAVs, and mixed platoons.Numerical studies on string stabilityIn this section, we first analyze the string stability of the three types of subsystems, with a particular focus on mixed platoons. Then, we investigate the influence of different types of IFT and maximum platoon sizes on the stability of the entire mixed traffic flow.Traffic simulationsIn this section, we conduct nonlinear traffic simulations to analyze the effects of IFT, maximum platoon size, and CAV penetration rate on the mixed traffic flow stability.ConclusionsThis paper introduces a unified evaluation method for mixed traffic flow stability, which explicitly incorporates the role of information flow topology and maximum platoon size for mixed platoons. Specifically, we evaluate MPF and MSL topologies, revealing that they outperform conventional PF topology regarding string stability. Notably, MSL emerges as a better option than MPF, highlighting the great potential of “looking behind” for CAVs in improving the entire mixed traffic performance.CRediT authorship contribution statementShuai Li: Writing – review & editing, Writing – original draft, Visualization, Methodology, Formal analysis, Software, Data curation, Conceptualization. Haotian Zheng: Writing – review & editing, Software, Data curation. Jiawei Wang: Writing – review & editing, Writing – original draft, Methodology, Conceptualization, Supervision, Project administration . Chaoyi Chen: Writing – review & editing, Resources. Qing Xu: Writing – review & editing, Supervision. Jianqiang Wang: Writing – review &AcknowledgmentsThe work of S. Li, H. Zheng, C. Chen, Q. Xu, J. Q. Wang and K. Li is

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Stability (Zhou et al., 2021, Yao et al., 2022, Yao et al., 2023). It is worth noting that these research (Talebpour and Mahmassani, 2016, Seraj et al., 2018, Zhu et al., 2021, Zhou et al., 2021, Yao et al., 2022, Yao et al., 2023) mostly focuses on the size of pure-CAV platoons, which is defined as the number of the CAVs that form a platoon, instead of the size of mixed platoons, which involves both CAVs and surrounding HDVs. A very recent paper (Yu et al., 2023) has introduced the concept of maximum platoon size for mixed platoons, and has analyzed the role of “looking ahead” IFT under the assumption of a fixed maximum platoon size. To our best knowledge, however, a comprehensive understanding of this critical factor in mixed traffic is lacking.To fill the aforementioned gaps, this paper analyzes the influence of two types of IFT (“looking ahead” and “looking behind”) and maximum platoon size on mixed traffic. Precisely, a dynamical modeling of the mixed traffic system is presented, which is decoupled into three subsystems: independent HDVs, independent CAVs and mixed platoons. Then, a unified stability criterion of mixed traffic flow is introduced, which incorporates the role of IFT and the emergence probability of different subsystems given the setup of maximum platoon size. Based on the proposed criterion, we proceed to apply specific control models for different subsystems and carry out numerical stability analysis at two levels: the mixed platoon itself and the entire mixed traffic flow. Finally, nonlinear traffic simulations are conducted for validation. Some preliminary results are presented in Li et al. (2023). The contributions of this paper are listed as follows.•This paper presents a unified method for evaluating mixed traffic stability, comprehensively considering both IFT and maximum platoon size. Unlike previous studies that mostly focus on independent CAVs with a PF topology (Qin and Wang, 2023, Talebpour and Mahmassani, 2016, Montanino and Punzo, 2021) or pure-CAV platoons (Zhou and Zhu, 2021, Yao et al., 2022, Yao et al., 2023), our method considers the coexistence of independent HDVs, independent CAVs and particularly mixed platoons with different types

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Fd98::/64 IPv6 subnet, you can specify a different IP address range for internal use by OVN-Kubernetes. You must ensure that the IP address range does not overlap with any other subnet used by your OpenShift Container Platform installation. The IP address range must be larger than the maximum number of nodes that can be added to the cluster. The default value is fd98::/64. Table 2.39. policyAuditConfig objectFieldTypeDescription rateLimit integer The maximum number of messages to generate every second per node. The default value is 20 messages per second. maxFileSize integer The maximum size for the audit log in bytes. The default value is 50000000 or 50 MB. maxLogFiles integer The maximum number of log files that are retained. destination string One of the following additional audit log targets: libc The libc syslog() function of the journald process on the host. udp:: A syslog server. Replace : with the host and port of the syslog server. unix: A Unix Domain Socket file specified by . null Do not send the audit logs to any additional target. syslogFacility string The syslog facility, such as kern, as defined by RFC5424. The default value is local0. Table 2.40. gatewayConfig objectFieldTypeDescription routingViaHost boolean Set this field to true to send egress traffic from pods to the host networking stack. For highly-specialized installations and applications that rely on manually configured routes in the kernel routing table, you might want to route egress traffic to the host networking stack. By default, egress traffic is processed in OVN to exit the cluster and is not affected by specialized routes in the kernel routing table. The default value is false. This field has an interaction with the Open vSwitch hardware offloading feature. If you set this field to true, you do not receive the performance benefits of the offloading because egress traffic is processed by the host networking stack. ipForwarding object You can control IP forwarding for all traffic on OVN-Kubernetes managed interfaces by using the ipForwarding specification in the Network resource. Specify Restricted to only allow IP forwarding for Kubernetes related traffic. Specify Global to allow forwarding of