A model‐based demand‐balancing control for dynamically divided multiple urban subnetworks

Lin, Shu; Kong, Qing; Huang, Qingming

doi:10.1002/atr.1389

Cited by 8 publications

(4 citation statements)

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“…Several studies (Xu (2019) [4,[29][30][31][32][33]. For large traffic networks consisting of multiple regional subnetworks, the strategy for controlling traffic at the boundaries between subnetworks is complex [34].…”

Section: Introductionmentioning

confidence: 99%

Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm

Ji,

Tang,

et al. 2023

Sustainability

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With continuous economic development, most urban road networks are facing unprecedented traffic congestion. Centralized traffic control is difficult to achieve, and distributed traffic control based on partitioning a road network into subnetworks is a promising way to alleviate traffic pressure on urban roads. In order to study the differences between different partitioning methods chosen for distributed traffic control, we used the normalization algorithm to partition a part of the road network in Changsha City, and we used the results of the Girvan–Newman algorithm and the manual empirical partitioning method as a control group. Meanwhile, an abstract road network was constructed using VISSIM simulation software based on realistic road network parameters. And then, the different partitioning results were applied to the simulated road network to analyze the control effect. The results of the simulation software show that different partitioning methods have different effects on traffic control at subnetwork boundaries and improve traffic pressure to different degrees. Partitioning the road network into four subnetworks provided the greatest degree of traffic improvement. Overall, the proposed distributed traffic control method effectively improved operational efficiency and alleviated the traffic pressure of the road network.

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Section: Introductionmentioning

confidence: 99%

Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm

Ji,

Tang,

et al. 2023

Sustainability

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“…Based on Macroscopic Fundamental Diagram (MFD) theory, Lin et al [14] designed a demand balance model. e traffic control subareas could be adjusted according to the actual traffic states in order to match the control strategy.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Control Subarea Division Based on Node Importance Evaluating

Tian

Liang

Feng

2021

Mathematical Problems in Engineering

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In order to optimize the existing control subarea division methods, a new dynamic subarea division method based on node importance evaluating is proposed for regional coordinated control. Firstly, considering the characteristics of road network and traffic flow between adjacent intersections, correlation degree model is established by calculating the correlation coefficients of traffic flow, signal cycle, and traffic state. Then, road traffic network is abstracted into a network topology structure graph. From the global perspective of the road network, intersection position information and the importance contribution between adjacent intersections are taken into account, and the correlation degrees between adjacent intersections are taken as the edge weights to construct intersection importance evaluation matrix. Finally, an actual road network is selected, and an improved Newman algorithm is employed to verify and analyze the method proposed in this paper. Results show that, compared with other methods, the control subarea division result of the new proposed method is more elaborate and more in line with the actual traffic flow characteristics. Moreover, dynamic subarea division can be realized according to the traffic characteristics of different periods, which can provide a good basis for the formulation of the signal control schemes in the next stage.

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“…Minimizing the queuing length in the network is another common optimization goal, and several methods have been applied to solve the problem, e.g., greedy-based MPC [17] and PID controller [16]. [42], [43] proposed a hierarchical control method, which decoupled the network into several sub-networks. In the upper layer, MPC controls the in and out traffic flow of sub-networks to maximize the traffic throughput, while in the lower layer, MPC controls the traffic SPAT in each sub-network based on the S model to minimize the travel time.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of Mixed Traffic Networks with Human-driven and Autonomous Vehicles

Xu¹,

Chen²,

Chang³

et al. 2021

Preprint

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The emergence of connected and automated vehicles (CAV) indicates improved traffic mobility in future traffic transportation systems. This study addresses the research gap in macroscopic traffic modeling of mixed traffic networks where CAV and human-driven vehicles coexist. CAV behavior is explicitly included in the proposed traffic network model, and the vehicle number non-conservation problem is overcome by describing the approaching and departure vehicle number in discrete time. The proposed model is verified in typical CAV cooperation scenarios. The performance of CAV coordination is analyzed in road, intersection and network scenario. Total travel time of the vehicles in the network is proved to be reduced when coordination are applied. Simulation results validate the accuracy of the proposed model and the effectiveness of the proposed algorithm.

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A model‐based demand‐balancing control for dynamically divided multiple urban subnetworks

Cited by 8 publications

References 50 publications

Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm

Distributed Traffic Control Based on Road Network Partitioning Using Normalization Algorithm

Dynamic Control Subarea Division Based on Node Importance Evaluating

Modeling and Analysis of Mixed Traffic Networks with Human-driven and Autonomous Vehicles

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