Signal Cooperative Control With Traffic Supply and Demand on a Single Intersection

Li, Zhihui; Cao, Qian; Zhao, Yanyun; Zhou, Rui

doi:10.1109/access.2018.2870172

Cited by 16 publications

(13 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies of signal optimization usually adopt a phasebased signal structure. The movement of vehicles from several approach lane are combined into phases, such as the orderfixed four-phase structure [12], [17], [18], [19], order-unfixed four-phase structure [15], [20], and the standard North American NEMA dual-ring, eight-phase control system [21]- [23]. These signal structures limit the flexibility of phase sequence optimization.…”

Section: ) Model Objectivementioning

confidence: 99%

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Long

Jiang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

Section: ) Model Objectivementioning

confidence: 99%

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Long

Jiang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…We regard formula (12) which represents the total time spent as the optimization objective to obtain preferable green time splits ( ), where is the prediction horizon which reflects the number of time steps of the prediction model.…”

Section: Model-based Signal Controlmentioning

confidence: 99%

“…Castro et al [11] proposed an adaptive biologically-inspired neural network method to control urban traffic. However, they function ineffectively under oversaturated condition [12].…”

Section: Introductionmentioning

confidence: 99%

Integration of Model‐Based Signal Control and Queue Spillover Control for Urban Oversaturated Signalized Intersection

Chen

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

An improved model-based predictive control approach integrating model-based signal control and queue spillover control is proposed in this paper, which includes three modules: model-based signal control, queue spillover identification, and spillover control to deal with the problem of traffic congestion for urban oversaturated signalized intersection. The main steps are as follows. First of all, according to the real-time traffic flow data, the green time splits for all intersections will be solved online by the modelbased signal control controller whose optimization model is based on model-predictive control (MPC) strategy. Second, the queue spillover identification module will be used to detect the potential queue spillover. If potential queue spillover is detected, the spillover control module will be activated to prevent vehicles from the upstream link of the link with possible spillover from entering the downstream link to avoid traffic congestion. The experiment is performed on a simulated road network. The results verify that the proposed scheme can significantly decrease the delay which reflects the overall performance of the studied intersection.

show abstract

“…As a novel control style, CCSD, proposed by our research team, realizes the cooperation between traffic supply and demand, and decision tree was used to solve the optimization problem [16], but the optimization process of decision tree cannot meet the real-time requirements of signal control system for exhaustive search. Due to the cooperation between multi-road time-varying traffic supplies and demands, the optimization problem of CCSD will be a timevarying M-N mathematical programming problem.…”

Section: Related Workmentioning

confidence: 99%

“…Aiming at this problem, the downstream capacity of intersection (termed as traffic supply) is taken into account, such as traffic gating/metering control [12], [13], Capacity-Aware Back-Pressure (CABP) control [14], coordinated control of arterials [15] and so on. In order to coordinate traffic supply and demand, CCSD [16] (signal Cooperative Control with traffic Supply and Demand) was proposed recently by our research team, in which traffic supplies and demands are taken as integration and cooperate with each other, and it could satisfy the control requirements under unsaturated, saturated and oversaturated conditions.…”

Section: Introductionmentioning

confidence: 99%

Krill Herd Algorithm for Signal Optimization of Cooperative Control With Traffic Supply and Demand

Cao

Zhao

et al. 2019

IEEE Access

Self Cite

View full text Add to dashboard Cite

As a novel signal control method, signal Cooperative Control with traffic Supply and Demand (CCSD) is superior to the traditional control methods and could satisfy the control requirements under all traffic conditions. However, the optimization solution of CCSD cannot meet the real-time control requirement for its exhaustive search. To overcome the problem, in this paper, the optimization problem of CCSD is reconstructed by the time-varying traffic supply and demand, and the problem is reduced as a problem of space search. Then, the krill herd (KH) algorithm is introduced and employed to realize the fast solution of CCSD (named KH-CCSD). During the process of optimization, the search space representation and fitness function for the KH algorithm are constructed to satisfy the solution of CCSD. The optimal signal timing plan is obtained by an iterated search of krill swarm in a multi-dimensional time-varying space cooperatively constrained by traffic supplies and demands. The convergence and effectiveness of KH-CCSD are validated by comparing experiments, in which the convergence of KH-CCSD is tested by different initializations and KH-CCSD is compared with the Webster method and capacity-aware backpressure (CABP) control under unsaturated, saturated, and oversaturated conditions. The experiments results show that KH-CCSD performs a fast convergence and KH-CCSD is superior to the Webster method and CABP. As a result, KH-CCSD could satisfy the application of CCSD under all traffic conditions. INDEX TERMS KH-CCSD, krill herd algorithm, signal cooperative control, traffic supply and demand.

show abstract

Signal Cooperative Control With Traffic Supply and Demand on a Single Intersection

Cited by 16 publications

References 29 publications

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Integration of Model‐Based Signal Control and Queue Spillover Control for Urban Oversaturated Signalized Intersection

Krill Herd Algorithm for Signal Optimization of Cooperative Control With Traffic Supply and Demand

Contact Info

Product

Resources

About