Effective Green Time Research Articles

Understanding the Determinants of Lane Inefficiency at Fully Actuated Intersections: An Empirical Analysis

As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays and emissions and enhancing overall system efficiency. The optimal performance of these systems relies on effectively facilitating vehicle discharge at the saturation flow rate throughout the green period. This study introduces a new parameter, lane inefficiency, evaluating vehicle discharge effectiveness by comparing saturation flow rate with instantaneous discharge for each green period. It provides a comprehensive assessment of green utilization for specific lanes. This study also explores the impact of signal control system parameters and traffic flow characteristics on lane inefficiency using principal component analysis (PCA) and multiple linear regression models. This approach holistically evaluates how both signal control system and traffic flow parameters collectively influence efficient green period utilization. The findings emphasize the impact of critical factors on lane inefficiency, including green time, the proportion of total unused green time to green time, total unused green time, the percentage of heavy vehicles in departing traffic, the ratio of effective green time to cycle time, the total time headways of the first four vehicles, and queue length. Decision makers need to pay due attention to these parameters to enhance intersection performance and foster a more sustainable urban transportation network.

A preliminary analysis for determining passenger car equivalent value for motorcycle during first lost time and saturation time at pretimed signalized intersections

In Banda Aceh City, signalized intersections are a strategic approach to mitigate conflicts such as accidents and traffic congestion. This was achieved by efficiently managing the flow of vehicles passing through intersections, enhancing their overall capacity. Currently, the management of signalized intersections in Banda Aceh still adheres to the guidelines stipulated in the 1997 Indonesian Highway Capacity Manual (MKJI 1997). Given the considerable variation in driver behavior and vehicle composition, particularly motorcycles, within Banda Aceh, a need for updated practices arises. Therefore, this research determined the comparison of PCEs values at the initial and saturation time based on the PKJI 2023 and the new calculations. It was conducted at four-legged intersections, namely Pocut Baren, AMD, Lhong Raya, and Jambo Tape. The primary dataset comprised intersections geometry, effective green time, traffic flow composition captured through drone recordings, and signal configurations. Statistical analysis in this research used multiple linear regression analysis to estimate the Passenger Car Unit (PCU) model parameters using video data recorded at the four-legged intersections. The result showed that PCE values for motorcycles during the initial time was 0.16, higher than the average saturation time values of 0.08.

A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays

With strict enforcement of pedestrian right of way at all intersections, the inappropriate right-turn resource allocation from a spatial and temporal perspective will lead to a reduction in the operational efficiency of the intersection. In this paper, three spatiotemporal resource allocation schemes for right-turning vehicles are proposed, considering the vehicle and pedestrian traffic efficiency in all directions of the intersection. To minimize vehicle and pedestrian delay at the intersection individually, an optimization model is established with the effective green time of each phase and three schemes as decision variables. A right-turn vehicle and pedestrian conflict delay model is developed based on the pedestrian-vehicle interaction behavior as the constraints of the optimization model. The NSGA-II algorithm is used to solve the model, and the quantitative criteria for the exclusive right-turn lane and phase are obtained by sensitivity analysis. The results of this paper can be used as a guide for traffic design and for planning and controlling the operation of right-turning vehicles at intersections.

Modeling of Effective Parameters for Capacity Prediction at Signalized Intersection Lanes

Current capacity manuals do not allow comprehensively evaluating negative effects on lane capacity caused by undisciplined vehicle movements and lane utilization, such as failure to obey distance rules, lane blockage caused by roadside parking effect, formation of an extra lane using in the emergency lane, etc., which are mostly observed in undeveloped and developing countries. Irregularities of the traffic flow caused by undisciplined movements and lane utilization result in decreased capacity or traffic change on the urban lanes. To overcome this problem, a lane-based study was carried out to determine the relation among effective parameters and their effect on lane capacity. In order to model the impact of these parameters, a comprehensive study was conducted in two cities in Turkey. Two different methods (statistical analysis and metaheuristic search algorithm) were used for this purpose and new more reasonable lane capacity estimation models (ALLCEM-1 and ALLCEM-2) were developed by examining all local conditions. The results proved that both examined methods are effective in modelling lane capacity of signalized intersections. It was also found that such parameters as the type of intersection (either a roundabout or not), effective green time, saturation flow rate, traffic volume, heavy vehicle ratio, and the number of actively used lanes have a major impact on the accuracy of prediction of road capacity.

Simulation Modelling of Permitted Left-Turn Saturation Flow Rate Based on Opposing Through-Flow Degree of Saturation

This paper presents the modelling of the saturation flow rate of the permitted left-turn in an exclusive lane. In the proposed model, the total permitted left-turn saturation flow rate is determined as a sum of saturation flow rates during the effective green time and the intergreen period. Primarily, the permitted left-turn saturation flow rate during the effective green time is modelled based on the opposing through-flow degree of saturation and the number of opposing through-flow lanes. The relation between the permitted left-turn saturation flow during the effective green time and these variables was examined using data from the simulation experiments in VISSIM. To our knowledge, this is the first study of the permitted left-turn saturation flow modelling based on the opposing through-flow degree of saturation instead of the opposing through-flow rate and signal-timing parameters. The proposed model was validated based on data collected at seven intersections with a permitted left-turn served in an exclusive lane. The permitted left-turn saturation flow rate could be accurately determined based on the opposing through-flow degree of saturation and the number of opposing lanes according to the RMSE of 58.4 pcu/h.

Mitigation of Insufficient Capacity Problems of Central Bus Stops by Controlling Effective Green Time

Mitigation of Insufficient Capacity Problems of Central Bus Stops by Controlling Effective Green Time

Impact Assessment of Driver Distraction by Cellphone on Start-up Lost-time and Average Saturation Headway at Signalized Intersections Based on Vehicle Position in the Queue

Cellphone usage has a significant impact on signalized intersections' capacity and level of service. This study investigated the impact of cellphone usage on signalized intersection capacity and level of service in Dammam Metropolitan Area, Saudi Arabia. The data included 183 useful cycles and 2407 start-up lost time and average saturation headway values at cycles with cellphone usage and cycles without cellphone usage at 24 signalized intersections. The main hypothesis of the study is that cellphone usage increases the start-up lost time at signalized intersection capacity. The secondary hypothesis is that cellphone usage increases the average saturation headway at signalized intersections. Normal distribution and z-test were conducted to assess whether there is a significant increase in average saturation headway and start-up lost time. The study found a significant increase in start-up lost time of about 0.7 seconds but found no significant increase in average saturation headway due to cellphone usage. Also, start-up lost time increases as vehicles of cellphone users get closer to the stop line of the signalized intersections. Thus, cellphone usage decreases the progression of 13 vehicles per hour due to a reduction in effective green time, increases total delay, and deteriorates the level of service. The study can assist transportation and traffic officials to optimize signal operation to mitigate the impact of cellphone usage and improve urban transportation.

Smart Cities and Data Analytics for Intelligent Transportation Systems: An Analytical Model for Scheduling Phases and Traffic Lights at Signalized Intersections

This paper is intended to improve the performance of signalized intersections, one of the most important systems of traffic control explained within the scope of smart transportation systems. These structures, which have the main role in ensuring the order and flow of traffic, are alternative systems depending on the different methods and techniques used. Determining the operation principles of these systems requires an extremely careful and planned study, considering their important role. Performance outputs obtained from the queue analyses made in previous studies formed the input of this study. The most important techniques are used in the effective control of intersections, such as signal timing: in particular, the use of effective green time and order of the transitions between phases. In this research, a traffic-sensitive signalized intersection control system was designed with the suggested methods against these two problems. The sample intersections were selected from three cities with the highest population density as the case study area. In the analysis of the performance of the connection arms of the selected intersections, flow intensity data were taken into consideration, as well as the arrival and service rates. Based on this, the outputs of the two proposed models regarding the use of phase transitions and effective green durations were compared with two other adaptive control systems and their positive results were shared. The results showed that signalized intersections, operating with a well-planned and correctly chosen technique, better regulate density and queuing.

EFFICIENCY UTILIZATION OF GREEN TIME AT COUNTDOWN SIGNALIZED INTERSECTION

The use of countdown traffic signals, although not common in North America, is increasing in Asia and European countries. Past studies conducted albeit outside the United States have addressed some operational benefits and issues associated with the use of countdown traffic signals, including but are not limited to effect on saturation flow rate, and red light running. Experience from the successful use of pedestrian countdown signals at urban traffic intersections has engendered some local interest in the use of countdown traffic intersections has engendered some local interest in the use of countdown traffic signal devices in the United States. The purpose of this research was to analyse using driver behaviour survey the efficiency of green-time utilization rate at countdown traffic signal devices in the United States. Specifically, this research performed a comparative analysis based on the postulation that countdown traffic signal is associated with underutilized effective green time when compared to the scenario at intersections controlled by traditional (non-countdown) traffic signals. Binary regression models were developed, using data obtained from the driver behaviour survey, to estimate decision probabilities for different combinations of vehicle position (i.e. distance to the stop line) and available green time (i.e. time left before the transition to yellow phase). A comparison between the estimated decision probabilities (determined from deductive reasoning) for traditional traffic supported a pattern of underutilization of green time for the countdown signal scenario. The underutilization of green time was associated with the likelihood of drivers slowing down prematurely to stop in reaction to the visual display of available green time before the change of signal phase. Underutilization of effective green time before the change of signal phase. Underutilization of effective green time translates into a lower saturation flow rate and hence reduced intersection capacity. The findings of this research could motivate additional studies pertaining to the determination of net operational benefits or plausibility of using countdown signal devices at urban traffic intersection in the United States.

The effect of elimination the left-turn movements on the intersections Capacity-A simulation study

Left-turn movement is an important element to determine the capacity of intersections due to high conflicts points. Therefore, finding the alternatives for such left turn movements may increase the intersection throughput and make it safer. This study discusses the effect of eliminating the left turn movements on the intersection capacity by adding U-turn sections after each approach to apply the left turning away of the intersection. This means that the left turn traffic will pass the intersection using through movements, use the added U- turns and use the intersection again to reach the destination direction using right turns. To apply such scenario, traffic simulation has been applied as a tool using Paramics traffic simulator which is one of the most confident tools over the world. Simulation models have been developed using Paramics considering both signalized and un-signalized intersections with different effective green times. The results suggested that applying such alternatives will significantly increase the intersection capacity. However, further research is needed to examine the geometric layout that would be useful for such alternatives and to confirm the validity of the findings by validation the developed simulation models.

An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator

In the past, the Webster optimal cycle time formula was limited to calculate the optimal cycle from historical data for fixed-time traffic signal control. This paper focuses on the design of an adaptive traffic signal control based on fuzzy logic with Webster and modified Webster's formula. These formulas are used to calculate the optimal cycle time depending on the current traffic situation which applying in the next cycle. The alternation of the traffic condition between two successive cycles is monitored and handled through the fuzzy logic system to compensate the fluctuation. The obtained optimal cycle time is used to determine adaptively the effective phase green times i.e. is used to determine adaptively the maximum allowable extension limit of the green phase in the next cycle. The SUMO traffic simulator is used to compare the results of the proposed adaptive control methods with fuzzy logic-based traffic control, and fixed-time Webster and modified Webster-based traffic control methods. The proposed methods are tested on an isolated intersection. In this study, real field-collected data obtained from three, four, and five approaches intersections in Kilis/Turkey are used to test the performance of the proposed methods. In addition, to examine the efficiency of the proposed techniques at heavy demands, the arbitrary demands are generated by SUMO for a four approaches intersection. The obtained simulation results indicate that the proposed methods overperform the fixed time and fuzzy logic-based traffic control methods in terms of average vehicular delay, speed, and travel time.

The Extent of Capacity Loss Caused by Rainfall at Signalised Intersections

Background: Even though their physical characteristics exert a constant influence on capacity and saturation flows, signalized intersections are fixed facilities not affected by rainfall. Whilst traffic conditions with varying effects can be regulated, rainfall conditions cannot be regulated but compensated for by warning drivers to reduce speed. Speed reduction has an impact on signalised intersection capacity, whilst signalised intersection capacity is a function of saturation flow, effective green, and cycle time. In this paper, a capacity loss is the differential percentage between ‘with and without’ rainfall scenario. Aim: The paper investigated the extent of capacity loss caused by rainfall at signalised intersections. Methods: In Durban, South Africa, rainfall data were collected, collated, and correlated with traffic data in a 'with and without' rainfall intensity study. Rainfall intensity was classified according to the rate of precipitation as follows; rainfall intensity(i): light rain (i <2.5mm/h); Moderate rain (2.5mm/h ≤ i < 10mm/h), and heavy rain (10 ≤ i ≤ 50mm/h) as prescribed by the World Meteorological Society. Results: Empirical results show that rainfall intensity has an effect on road capacity at a signalised intersection. Generally, for the vehicles going straight, light rain caused a 4.25% capacity loss; moderate rain 9.18% while heavy rain caused an 11.53% capacity reduction. With right-turning vehicles, light rain caused 7.38% capacity loss; moderate rain caused 14.3%, while heavy rain accounted for 19.15% capacity reduction. Conclusion: The paper concluded that rainfall at signalised intersections would cause an anomalous capacity reduction. Since the database for the study is small, the paper advocates for further studies based on a broader database to include yellow interval time.

A Competitive Mechanism Multi-Objective Particle Swarm Optimization Algorithm and Its Application to Signalized Traffic Problem

In this paper, a modified Competitive Mechanism Multi-Objective Particle Swarm Optimization (MCMOPSO) algorithm is presented for multi-objective optimization. The algorithm consists of an improved leader selection scheme called multi-competition leader selection. Under this scheme, particles move to the winner among the elite particles for the social cognitive by comparing the nearest angle or the farthest angle of several randomly selected elite particles. Besides, as the inertia weight plays an important role in controlling the previous velocity of each particle, the competitive mechanism is applied to the inertia weight in order to investigate for the most suitable balance between the exploration and exploitation abilities of the algorithm during the search process. The experimental results show that the proposed algorithm outperforms four other popular multi-objective particle swarm optimization algorithms most of the time on thirty-seven benchmarks in terms of inverted generational distance. Furthermore, the proposed algorithm is applied to the signalized traffic problem to optimize the effective green time of each phase, and the proposed algorithm performs better than other MOPSO algorithms for the traffic problem in terms of hypervolume.

Multiple Objective Genetic Algorithms for Solving Traffic Signal Optimization Issue at a Complex Intersection: A Case Study in Taichung City, Taiwan

Background: In optimal traffic signal timing, some researchers proposed a single objective genetic algorithm to optimize the timing plan at an isolated intersection. However, the genetic algorithm belongs to a natural selection procession. It means that a suggested model might have a local, optimal result instead of global optimization. A few researchers have tried to avoid local optimization values by making many assumptions for the suggested model, these estimations lacked comprehensive theoretical bases in the transportation field. Objective: The objective of this study is to contribute a comprehensive optimization solution, by applying multiple objective genetic algorithms, to minimize the effective green time and cycle length at a complex urban intersection. Methods: First, the fitness function was established by the minimum issues of average control delay and queue length at the complex isolated intersection. Secondly, constraint functions were identified based on a scientific basis to provide a comprehensive hypothetical model. After running the hypothetical model with single and multiple objective genetic algorithms and real traffic flow data, the results were compared between the use of multiple genetic algorithms and the use of a single-objective genetic algorithm, between an existing traffic signal timing plan and a suggested traffic signal timing plan. Then, the traffic simulation model for the complex intersection was generated to validate the effectiveness of the suggested method. Results: After comparison, the suggested model was found to be more efficient than the existing traffic signal timing at the complex intersection. Conclusion: This study demonstrated multiple objective genetic algorithms that overwhelmed the single objective genetic algorithm in optimal traffic signal timing. The multiple objective genetic algorithms could be effectively used to handle traffic optimization at a complex large-scale intersection. Furthermore, a comprehensive solution of applying multiple genetic algorithms to deal with traffic signal optimization has been generated in this research.

Flashing green effects on traffic efficiency

Flashing green signal, as a part of the green traffic signal, indicates that the green signal is about to end. Drivers have more time to decide whether to stop or pass the intersection since they have prior information that the yellow signal will start. The application of flashing green at the end of the green signal is optional, hence, the question is how engineers could decide to use flashing green or not? The answer to the question should be based on researches on flashing green effects on traffic efficiency and safety at signalized intersections. The aim of this paper is to analyze the impact of flashing green on traffic efficiency by determining the value of effective green time. The research was conducted at two intersections in Belgrade, with and without a flashing green signal. Results indicate that effective green is shorter when flashing green is applied, due to the decreased utilization of the yellow signal.

MODELLING AND SENSITIVITY ANALYSIS OF UNCOORDINATED PAIRED INTERSECTIONS WITH LEFT-TURN BAYS

Left-turn bays are often installed on the road segment between paired intersections. Such left-turn bays may reduce the approach capacities and impact on one another. Four optimization models are put forward for uncoordinated paired intersections with left-turn bays. The phase effective green times and the left-turn bay lengths are the decision variables, maximizing the intersection capacities, minimizing the intersection delays and both of them are respectively regarded as different objective functions, and minimizing the total delay for paired intersections is viewed as another objective function. The total capacity-to-delay ratio is defined to evaluate the operations of paired intersections as a whole. Using the field data, the sensitivities of the optimized outcomes to the weighting factors of the objective functions are analysed. To clarify the influences of different scenarios on traffic stream operations, seven scenarios are tested using VISSIM. The interval estimation and hypothesis testing are used to analyse the simulated data. Three concrete models are recommended to apply in practice with the procedure of model application being provided. The achievements can be applied to optimally assign the temporal-spacial resources for paired intersections when left-turn bays need to be installed and coordinated signals do not need to be considered.

Comparative Analysis of Optimization Models for Paired Intersections with Left-Turn Bays

Left-turn bays may be provided at paired intersections when heavy left-turn demands exist on some approaches. Such left-turn bays may have significant effects on intersection operations. Considering the settings of left-turn bays, two single-objective optimization models are developed for paired intersections with uncoordinated and coordinated signals, respectively. Numerical examples are fulfilled to demonstrate and compare the formulated models, and the orthogonal simulation experiments are carried out. Assuming that the relevance of traffic flow exists, the results show that the optimized effective green times and left-turn bay lengths depend on traffic demand, whereas the optimized offset between paired intersections is sensitive to intersection spacing; the optimization model with coordinated signals outstrips that with uncoordinated signals at 99% confidence level when the distance between paired intersections is not too far and traffic demand is not too low, whereas the former may be inferior to the latter when traffic demand is low enough and intersection spacing is far enough.

ANALYSIS AND OPTIMIZATION OF TRAFFIC CONGESTION AT SINGLE INTERSECTION USING MATLAB AND ARENA SIMULATION

Traffic jam is one of the most widespread problems commonly seen all over the world that causes loss of billions of dollars and useful hours per annum. Traffic lights are used at the intersections to manage the traffic flow, but one problem of those traffic lights is that the color changes at constant intervals irrespective of the traffic density or time of the day. As a result, the measure fails to keep the optimal traffic flow throughout the day at every convergence. This study describes a possible and effective method to systemize traffic lights by considering the traffic density for a specific time of the day. The range of idle time or waiting time within the queue is identified as a function of cycle time, effective green time and traffic arrival rate. After plotting the values within the graph, the trend is observed for idle time with reference to these variables. The lower and upper bound for these independent variables like cycle time, effective green time and traffic arrival rate are decided from observed data sets. As the idle time comes in the form of a range, an estimation of traffic congestion at a particular time is yielded from the method. This traffic flow is analyzed using Arena. The result of idle time using Arena is analogous with the previously analyzed model using MATLAB. Also, at the end of the study, a simulation video is generated that gives practical visual experience.

Green Light Optimal Speed Advisory System Designed for Electric Vehicles Considering Queuing Effect and Driver’s Speed Tracking Error

The GLOSA (Green Light Optimal Speed Advisory) system provides speed advice to drivers so that drivers can pass through congested intersections at right instant with shorter time and lower energy consumption. Traditional GLOSA system only considers the SPaT (Signal Phase and Timing) of traffic light. However, two another important factors, namely queuing effect and actual tracking error of drivers, are seldomly considered, which degrades the actual performance of the GLOSA system. Intelligent connected vehicles based on V2I (Vehicle to Infrastructure) have great application potential in solving this problem. In this study, firstly, a vehicle queue length estimation method based on V2I technology is proposed to predict the effective green light time. Secondly, a hierarchical GLOSA system is developed, where the upper layer provides the global recommended optimal speed aiming at minimizing energy consumption, while the bottom layer provides the modified recommended speed considering the driver's tracking error. Finally, the tracking error of the driver when executing the recommended speed is derived based on the real-world experiment. Corresponding simulation and field test platforms are also established. Results show that compared with the traditional GLOSA system, the improved GLOSA system considering the vehicle queuing effect and driving error can effectively improve the energy-saving performance of the vehicle.

Intersection Traffic Control Based on Multi-Objective Optimization

Currently, most traffic control methods at intersections rely on the control of signal lights. However, most signal lights operate in the traditional fixed timing mode, which cannot adjust the timing based on the time-varying traffic flow. To solve the problem, this paper constructs a signal timing control model to optimize road capacity, delay time and the number of stops at the intersections, under the following constraints: cycle time, effective green light time and the maximum number of vehicles in each direction of intersection. To solve the model, the standard dragonfly algorithm (DA) was improved by a hybrid mutation operator, which ensures the diversity of solution set. The proposed model and algorithm were compared with the Webster model through simulations in an actual scene and on a virtual platform. The comparison fully proves the advantages of our model and algorithm.