Distributed Optimization and Coordination Algorithms for Dynamic Traffic Metering in Urban Street Networks

Mohebifard, Rasool; Hajbabaie, Ali

doi:10.1109/tits.2018.2848246

Cited by 30 publications

(9 citation statements)

References 43 publications

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“…These macroscopic traffic flow models can be classified into first-order, secondorder or higher-order models. Some models, such as the Lighthill-Whitham-Richards (LWR) [4] and cell transmission model (CTM) [5], are representative of first-order models, while the METANET model is a common second-order traffic flow model [6]. Since the speed variations of vehicles and the reaction time of drivers are not considered, capacity decreases and oscillations due to freeway congestion cannot be reflected in first-order models.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization

2021

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In order to solve the problem of traffic congestion and emission optimization of urban multi-class expressways, a robust dynamic nondominated sorting multi-objective genetic algorithm DFCM-RDNSGA-III based on density fuzzy c-means clustering method is proposed in this paper. Considering the three performance indicators of travel time, ramp queue and traffic emissions, the ramp metering and variable speed limit control schemes of an expressway are optimized to improve the main road and ramp traffic congestion, therefore achieving energy conservation and emission reduction. In the VISSIM simulation environment, a multi-on-ramp and multi-off-ramp road network is built to verify the performance of the algorithm. The results show that, compared with the existing algorithm NSGA-III, the DFCM-RDNSGA-III algorithm proposed in this paper can provide better ramp metering and variable speed limit control schemes in the process of road network peak formation and dissipation. In addition, the traffic congestion of expressways can be improved and energy conservation as well as emission reduction can also be realized.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization

2021

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“…This section presents a linearized formulation for the SODTA problem based on the CTM network loading concept. We have used the CTM in our previous work for signal timing optimization (Mehrabipour & Hajbabaie, ; Mehrabipour, ), speed harmonization (Tajalli & Hajbabaie, , ), and traffic metering (Mohebifard & Hajbabaie, , ; Mohebifard, Islam, & Hajbabaie, ). We first define the temporal and spatial distribution of the problem.…”

Section: Problem Formulationmentioning

confidence: 99%

A decomposition scheme for parallelization of system optimal dynamic traffic assignment on urban networks with multiple origins and destinations

Mehrabipour

Hajibabai

Hajbabaie

2019

Computer aided Civil Eng

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This paper presents a decomposition scheme to find near‐optimal solutions to a cell transmission model‐based system optimal dynamic traffic assignment problem with multiple origin‐destination pairs. A linear and convex formulation is used to define the problem characteristics. The decomposition is designed based on the Dantzig–Wolfe technique that splits the set of decision variables into subsets through the construction of a master problem and subproblems. Each subproblem includes only a single origin‐destination pair with significantly less computational burden compared to the original problem. The master problem represents the coordination between subproblems through the design of interactive flows between the pairs. The proposed methodology is implemented in two case study networks of 20 and 40 intersections with up to 25 origin‐destination pairs. The numerical results show that the decomposition scheme converges to the optimal solution, within 2.0% gap, in substantially less time compared to a benchmark solution, which confirms the computational efficiency of the proposed algorithm. Various network performance measures have been assessed based on different traffic state scenarios to draw managerial insights.

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“…Similarly, (Islam and Hajbabaie, 2017) required 40% CAVs to outperform actuated-coordinated signal system in their proposed distributed-coordinated algorithm. (Mohebifard and Hajbabaie, 2018) achieved a significant reduction in system-level delay of network traffic at 40% CAV market penetration rate.…”

Section: Findings From Existing Literaturementioning

confidence: 99%

Investigating the Impact of Connected Vehicle Market Share on the Performance of Reinforcement-Learning Based Traffic Signal Control

Aziz¹,

Hong²,

Young

et al. 2019

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Distributed Optimization and Coordination Algorithms for Dynamic Traffic Metering in Urban Street Networks

Cited by 30 publications

References 43 publications

Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization

Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization

A decomposition scheme for parallelization of system optimal dynamic traffic assignment on urban networks with multiple origins and destinations

Investigating the Impact of Connected Vehicle Market Share on the Performance of Reinforcement-Learning Based Traffic Signal Control

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