Cooperative traffic signal and perimeter control in semi-connected urban-street networks

Mohebifard, Rasool; Islam, S M A Bin Al; Hajbabaie, Ali

doi:10.1016/j.trc.2019.05.023

Cited by 52 publications

(20 citation statements)

References 40 publications

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“…The problem formulation utilizes the CTM network loading concept that is introduced by Daganzo [9], [36] and used in other traffic control studies [37]- [39]. CTM divides a network link into homogeneous segments and discretizes the study period to short time steps.…”

Section: Problem Formulationmentioning

confidence: 99%

Network-Level Coordinated Speed Optimization and Traffic Light Control for Connected and Automated Vehicles

Tajalli

Mehrabipour

Hajbabaie

2021

IEEE Trans. Intell. Transport. Syst.

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This study develops a methodology for coordinated speed optimization and traffic light control in urban street networks. We assume that all vehicles are connected and automated. The signal controllers collect vehicle data through vehicle to infrastructure communications and find optimal signal timing parameters and vehicle speeds to maximize network throughput while harmonizing speeds. Connected and automated vehicles receive these dynamically assigned speeds, accept them, and implement them. The problem is formulated as a mixed-integer non-linear program and accounts for the trade-offs between maximizing the network throughput and minimizing speed variations in the network to improve the network operational performance and at the same time smoothen the traffic flow by harmonizing the speed and reducing the number of stops at signalized intersections. A distributed optimization scheme is developed to reduce the computational complexity of the proposed program, and effective coordination ensures nearoptimality of the solutions. The case study results show that the proposed algorithm works in real-time and provides nearoptimal solutions with a maximum optimality gap of 5.4%. The proposed algorithm is implemented in Vissim. The results show that coordinated signal timing and speed optimization improved network performance in comparison with cases that either signal timing parameters or average speed of vehicles are optimized. The coordinated approach reduced the travel time, average delay, average number of stops, and average delay at stops by 1.9%, 5.3%, 28.5%, and 5.4%, respectively compared to the case that only signal timing parameters are optimized.

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Section: Problem Formulationmentioning

confidence: 99%

Network-Level Coordinated Speed Optimization and Traffic Light Control for Connected and Automated Vehicles

Tajalli

Mehrabipour

Hajbabaie

2021

IEEE Trans. Intell. Transport. Syst.

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“…As such, it is noticeable that the current signal control strategies that solely relied on CV data required 20% to 50% CV penetration rates to outperform the state-of-the-art signal systems ( 8 , 17 , 20 , 21 ). This high requirement of CV penetration rate is not achievable in the near future; thus, several studies integrated a secondary data source such as detector data ( 21 – 23 ) or historical traffic data ( 24 ) with the available CV data to compensate for the limited data in low CV penetration rate. Lee et al ( 21 ) utilized loop detector and CV data to count total vehicles and cumulative travel time respectively within an approach.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They showed a 2% reduction in travel time at 30% CV penetration rates compared with actuated signal control systems. Mohebifard et al ( 23 ) showed a gradual improvement in delay and travel time with more than 20% penetration rate by integrating detector data. Furthermore, fusing loop detector data in a CV-based signal control strategy allowed Islam et al ( 16 ) to reduce the required CV penetration rate from 40% to 10%.…”

Section: Literature Reviewmentioning

confidence: 99%

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Islam

Tajalli

Mohebifard

et al. 2021

Transportation Research Record

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The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.

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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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Cooperative traffic signal and perimeter control in semi-connected urban-street networks

Cited by 52 publications

References 40 publications

Network-Level Coordinated Speed Optimization and Traffic Light Control for Connected and Automated Vehicles

Network-Level Coordinated Speed Optimization and Traffic Light Control for Connected and Automated Vehicles

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

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

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