Green Wave Control Research Articles

Green Wave Control Model Simultaneously Considering Passenger Cars and Buses in Closed Road Networks

Existing green wave control methods for passenger cars and buses mainly focus on maximizing bandwidths at the arterial level. There is little research on green wave control for both at the closed road network level, which makes it difficult to improve the efficiency of the entire area. To address this, a green wave control model that considers both passenger cars and buses in closed road networks is presented in this paper. The objective function of the model is to maximize the sum of the weighted bandwidths of passenger cars and buses on each segment of the road network. The relationships between car green bands, bus green bands, offsets, phase sequences, red time, green time, etc. are analyzed on the level of arterials and road networks, respectively, using time–space diagrams. Based on these analyses, the key constraints of the model are constructed accordingly. In addition, 0/1 variables and a sufficiently large positive number M are introduced to relax some of the constraints to ensure that the presented model has feasible solutions. The results of the numerical example demonstrate that compared with the fixed phase sequence schemes 1, 2, and 3, the total weighted bandwidth generated by the presented model increased by 9.5%, 16.4%, and 17%, respectively. Compared with the model without constraint relaxation, the presented model can still find a global, optimal solution when the common cycle time is fixed, while the model without constraint relaxation has no feasible solution.

Identification of Factors Influencing the Operational Effect of the Green Wave on Urban Arterial Roads Based on Association Analysis

Green wave control is an important technology that synchronizes traffic signals to improve traffic flow on urban arterial roads. Current research has focused on optimizing and evaluating control schemes; however, their operational effect is easily affected by a variety of traffic and travel factors. This means it is important to study methods to identify the factors influencing the operational effect of the green wave on arterial roads. In this study, we conducted innovative research to identify these factors and made breakthroughs in optimizing and evaluating schemes of green wave control. We use the number of stops, travel time, and delays as representative evaluation indicators to assess the effects of four influencing factors: design speed, signal timing, pedestrian crossing, and heavy vehicles. An association analysis that combines sensitivity analysis and grey relational analysis was used to rank these factors in their degree of correlation. A case study was conducted based on the traffic data on Eshan Road in Wuhu City to verify the proposed method. The results of simulations in Vissim 7.0 showed that pedestrian crossing and heavy vehicles were the more important factors influencing the operational effect of the green wave. Moreover, implementing measures related to traffic management helped improve the effect to an extent greater than by optimizing the scheme for green wave control alone. Additionally, optimizing control schemes in the context of implementing measures related to traffic management significantly improved the operational effect of the green wave.

Collaborative Control Optimization on Reversible Lanes in Intersection Group under Intelligent Vehicle Infrastructure Cooperative System

Based on the Intelligent Vehicle Infrastructure Cooperative System (IVICS), the paper firstly analyzes the operating characteristics of the intersection group under real-time reversible lanes from the capacity; secondly, the signal phase sequence and signal timing parameters of the intersection are designed, and the green wave control is designed based on the phase difference model. The scheme provides traffic flowing in this section with a continuous green light signal. Finally, taking the intersection of Yongle East Road in Wuxi, Jiangsu Province as an example, it optimizes and controls the green wave of the intersection group and verifies the effectiveness of the phase difference model using the evaluation indicators of the number of stops, green wave speed, traffic capacity, and saturation flow. The results show that the optimization of the number of stops is 9.5% and the vehicle speed is optimized by 5.3%. The intersection capacity and saturation flow are greatly improved.

An integrated arterial coordinated control model considering green wave on branch roads and pedestrian crossing time at intersections

Urban fine management needs scientific traffic management methods and efficient signal control programs. Green wave control is usually used to facilitate the unban traffic. However, maximum bandwidth optimization on arterial traffic signal timing is usually yielded from the sacrifice of the branch road. The green wave on branch roads and pedestrian crossing time at intersections are often neglected. In this paper, an extended integrated green wave control method is presented to solve the coordinated control issue, which considers green time constraints to ensure necessary time for vehicles on branch roads and pedestrian crossing time at intersections. Non-coordinated phase saturation is first introduced to describe the green time on branch roads. Next, the arterial roads are partitioned to enlarge the green wave bandwidth and an extended green wave optimization model with green time constraints is proposed. Combined with the green wave searching method, an improved genetic algorithm is applied. Finally, a real-world case study in Shenzhen, China, is employed to assess the model. Results show the proposed model can (1) reach the same public green time as in the traditional method and (2) increase the average sub-green wave bandwidth to improve the signal control.

Multi-junction traffic light optimization during holiday based on improved green wave band control

In recent years, urban car ownership has increased with rapid economic development, and urban traffic congestion has become more and more serious. Especially during the holidays, the number of people traveling by car has increased, the pressure on traffic is greater, and the traditional traffic lights are fixed. Far from meeting the needs of the current road conditions. The traditional green wave control is improved, and the intelligent algorithm such as fuzzy algorithm and genetic algorithm is used to solve the green wave period and signal timing. Taking Wuhan as an example, using VISSIM to simulate, the results show that the method effectively reduces vehicle delay and average number of stops, and improves the fluency of urban multi-junction traffic.

Traffic Signal Coordination for Tramlines with Passive Priority Strategy

Prioritizing traffic signals for trams crossing intersections without stops can increase the service punctuality and travel speed of trams, but it may also increase the delays of other vehicles at intersections. This paper presents a model on coordinated control of traffic signals among successive intersections along the tramline, taking into account driving characteristics of trams and vehicles. The objective is maximizing the valid bandwidth of vehicle green wave to reduce vehicle delays, while the trams cross intersections without stops. Linear Interactive and General Optimizer (LINGO) is applied to solve the proposed model and VISSIM simulation software is adopted to assess the solutions attained by the proposed model and the previous TRAMBAND model. Case studies show that the solutions given by the proposed model facilitate trams to go through all intersections along the tramline without stops. In comparison with the TRAMBAND model, the proposed model reduces tram delay by 13.14 s/pcu and increases the throughput of vehicles at intersections by 4.45% and reduces vehicle delays by 2.22%. Extensive simulations have verified that the performance of the proposed model is stable under different tram headways, dwell time, and traffic volumes. It is also found that the tram headway must be multiple of traffic signal cycle time to completely realize green wave control of all trams at all intersections along the tramline.

Optimization Method of Intersection Signal Coordinated Control Based on Vehicle Actuated Model

Traditional timing green wave control with predetermined cycle, split, and offset cannot adapt for dynamic real-time traffic flow. This paper proposes a coordinated control method for variable cycle time green wave bandwidth optimization integrated with traffic-actuated control. In the coordinated control, green split is optimized in real time by the measured presence of arriving and/or standing vehicles in each intersection and simultaneously green waves along arterials are guaranteed. Specifically, the dynamic bound of green wave is firstly determined, and then green early-start and green late-start algorithms are presented respectively to accommodate the fluctuations in vehicle arrival rates in each phase. Numerical examples show that the proposed method improves green time, expands green wave bandwidth, and reduces queuing.

Applications of Dynamic Partitioning of Intersection Group

An urban intersection group consists of a set of intersections which are geographically adjacent and strongly correlated with each other [1]. It is the minimal network for traffic control and coordination control. In this paper, based on the dynamic partitioning results of the intersection group provided by the software and data collected by traffic flow detectors, the features of dynamic partitioning software for intersection group are further explored from two aspects: traffic control and emergency response to traffic accidents, using the method of green-wave control and traffic guidance respectively.

Development and Evaluation of a Green Wave Control Algorithm Based on Two-Way Bandwidth Maximization for Transit Signal Priority

A good traffic signal design is one of the key solutions to many transportation problems. A two-way green wave control strategy for transit signal priority is reviewed and evaluated in this paper. Considering the traffic tidal phenomenon along the arterial roads during rush hours, a directional transit signal priority algorithm depend on the passenger flow has been developed for the coordination in signalized intersections. The algorithm provides signal timing plans for each intersection and the optimal bus speed along each section based on two-way bandwidth maximization. The strategy was designed to provide sectional control on transits, using electric signs and existing traffic control devices. In this paper, the strategys efficiency was evaluated using VISSIM micro-simulation along an arterial road which contains five intersections and serves more than ten bus lines. Actual data was used in the simulation. The simulation results show that the presented algorithm can effectively improve the operation efficiency of the transit system. This green wave control strategy reduced the number of stops by 34 % to 47 % and travel delay time by 27 % to 30% of the transit, while restricting the impact on vehicular traffic to the minimum. Moreover, the number of stops and travel delay time of vehicular traffic actually got a slight decrease. The algorithm shows promising results, and with minor upgrades, it can be applied to any type of intersection.

Research and Design of Green Wave Control in Urban Emergency Traffic

When a disaster occurred in a city, the most important thing is succors and equipment of rescuing arriving at the disaster spot rapidly. We bring up a method of emergency traffic commanding based on GIS and GPS in this paper. The wrecking car installed mobile information terminal transmits the GPS real-time position information to the command center. The command center setups GIS platform, and sends an optimum route of arriving at the disaster spot to the wrecking car based on the condition of real-time traffic, then sends the signal controlling sequence to the traffic signal light of intersection on this optimum route in turn, in order to create “Green Wave” for wrecking car and make it arrive at the disaster spot rapidly.

Train Control to Reduce Delays upon Service Disturbances at Railway Junctions

Train delay is one of the most important indexes to evaluate the service quality of the railway. Because of interactions among different trains, a delayed train may hinder subsequent trains scheduled on other lines at junction area. Trains may be forced to stop or decelerate, which consequently leads to the loss of run-time. This paper proposes a time-saving control method to recover the train delay as much as possible. In the proposed method, golden section search is adopted to identify the optimal train speed at the time of signal upgrade in the conflicting area, which enables the train to depart from the conflicting area as soon as possible. A heuristic method is then developed to attain the train control scheme to realize the optimal train speed at the time of signal upgrade in the conflicting area. Simulation study indicates that the proposed method enables the train to across the conflicting area with smaller run-time and therefore leads to larger delay reduction, in comparison with the traditional maximum speed control method and the green wave control method.

Two-Direction Green Wave Control of Traffic Signal Based on Particle Swarm Optimization

This paper proposes a two-direction green wave control algorithm of traffic signal based on particle swarm optimization. The traffic flow model of queuing length and two-direction green wave control object function were built. The signal split and the phase offset were optimized by particle swarm optimization. The simulation result with traffic data collected from Liansheng Road in Dongguan City proved this method was effective and practical. Compared with graphical method and actuate signal control, the proposed algorithm could effectively reduce delaying time and shorten queuing length.