Traffic Signal Coordination Research Articles

A Signal Timing Method to Reduce the Emissions in Arterials (Case Study: Enghelab Avenue in Ahvaz)

Actuated signal control is very efficient for isolated intersections, but along arterials it lacks the means to synchronize signals, leading to high delays and frequent stops which produce high emissions and fuel consumption. This research aims to use new paradigms based on actuated control that can lead signals to synchronize with their neighboring intersections resulting in reduction of emissions, fuel consumption and travel time in the arterials. In this research, traffic signal coordination software Synchro 8 was used to coordinate the signals on closely spaced intersections in Enghelab avenue in Ahvaz. In order to evaluate the effectiveness of proposed control logic, a simulation test bed was developed in the traffic simulation model SimTraffic 8 and 3D viewer 8.The Proposed logic resulted in total travel time, emissions and fuel consumption reductions of up to 25.6 %, 12.61% and 16.4% respectively compared to current condition logic in Enghelab avenue.

Design & Coordination of Traffic Signals of Two Adjacent Roundabouts of Chandigarh

Design & Coordination of Traffic Signals of Two Adjacent Roundabouts of Chandigarh

AM-Band: An Asymmetrical Multi-Band model for arterial traffic signal coordination

MAXBAND and MULTIBAND are two well-recognized methods for arterial signal control. In this paper, an Asymmetrical Multi-BAND (AM-BAND) model is developed by relaxing the symmetrical progression band requirement in MULTIBAND. Such a relaxation allows the AM-BAND model to better utilize the available green times in each direction and to provide additional opportunities for vehicular progression. Similar to MULTIBAND, the proposed AM-BAND model is formulated as a mixed-integer linear program. However, in AM-BAND the green bands in each directional section of the arterials do not have to be symmetrical with respect to the progression line. The performance of the AM-BAND model is evaluated for two arterial network data using the AIMSUN microscopic traffic simulation tool. The optimal signal coordination plans are computed by the IBM CPLEX Optimization Studio and compared with signal timing plans generated by AM-BAND, MULTIBAND, and MAXBAND. Simulation results indicate that the traffic signal coordination plans generated by AM-BAND can provide significant benefits compared to those generated by MAXBAND and MULTIBAND.

Traffic signal optimization using cyclically expanded networks

Traditionally, the coordination of multiple traffic signals and the traffic assignment problem in an urban street network are considered as two separate optimization problems. However, it is easy to see that the traffic assignment has an influence on the optimal signal coordination and, vice versa, a change in the signal coordination changes the optimal traffic assignment. In this article, we present a cyclically time‐expanded network and a corresponding mixed integer linear programming formulation for simultaneously optimizing both the coordination of traffic signals and the traffic assignment in an urban street network. Although the new cyclically time‐expanded network provides a model of both traffic and signals close to reality, it still has the advantage of a linear objective function. Using this model, we compute optimized signal coordinations and traffic assignment on real‐world street networks. To evaluate the practical relevance of the computed solutions, we conduct extensive simulation experiments using two established traffic simulation tools that reveal the advantages of our model. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 65(3), 244–261 2015

Implementation of Real-Time Offset-Tuning Algorithm for Integrated Corridor Management

Integrated corridor management (ICM) has been proved to relieve recurrent and nonrecurrent congestion effectively in a transportation network. Traffic signal coordination is an effective approach for improving travel speed and decreasing delays. The incorporation of traffic signal coordination into ICM further improves the benefits of ICM strategies. However, traffic signal coordination is applied on the basis of commuter traffic, and detour traffic is not considered. A real-time and proactive offset-tuning algorithm is proposed to reduce the delays of detour traffic without disrupting existing traffic. The algorithm explicitly incorporates diverted traffic and diverted traffic patterns into the existing traffic. The offsets of each coordinated intersection are fine-tuned and updated every 10 cycles to provide smooth progression for upcoming traffic. A case study was conducted to prove the effectiveness of the proposed algorithm. The benchmark case was TRANSYT-7F coordinated traffic signal timing plans. The simulation statistics indicated that the proposed approach created a saving of 8.8% in travel time and 8.3% in control delay in the direction of the diversion. The proposed algorithm did not sacrifice the traffic conditions in the opposite direction of the detour. The statistical analysis proved that the average control delay for both the direction of the diversion and the opposite direction, for all intersections, decreased by 5.6%, with a lower control delay at the 95% confidence interval. The diversion contributed to a gain of 9.22 mph or 18.96% in average speed on the freeway.

Intersection Group Dynamic Subdivision and Coordination at Intraregional Boundaries in Sudden Disaster

This paper aims at the traffic flow agglomeration effect characteristics and rapid evacuation requirement in sudden disaster; operation time of intraregional boundaries traffic signal coordination was presented firstly. Then intraregional boundaries intersection group dynamic subdivision and consolidation method based on relative similarity degree and similarity coefficient of adjacent intersections was put forward. As to make the traffic control strategy adapt to traffic condition of different intraregional boundaries intersection groups, this paper proposes an intraregional boundaries traffic signal coordination and optimization technology based on organic computing theory. Finally, this paper uses Delphi 7.0, MapX, and Oracle developing a software package, combined with Paramics V6 Simulator to validate the methods of this paper. The result shows that it can obviously improve disaster affected regional traffic signal control efficiency which reduces average traffic delay by 30–35%, decreases vehicle queue by more than 20% and reduces evacuation time more than 13.06%.

Review of Greenlight Pinellas

Under its “Greenlight Pinellas” proposal, the Pinellas Suncoast Transit Authority (PSTA), which serves Pinellas County, FL, wants to switch its major funding source from a property tax to a sales tax at a rate that will more than double its local tax revenues, and use the added money to build a 24-mile light-rail line and expand bus service. This proposal is extremely and unnecessarily expensive given that buses can provide a superior service to light rail, carrying more passengers more comfortably to more destinations at a far lower cost.PSTA has already shown its inability to predict short-term travel patterns. Between 1991 and 2005, it increased bus service by 46 percent yet gained essentially no new riders and actually saw a 17 percent reduction in passenger miles. The result was that average occupancies of PSTA buses, which were already emptier than the national average, fell by 44 percent.Compared with bus-rapid transit, the proposed light-rail line would be so costly and attract so few new riders that it would be less expensive to give every new round-trip commuter who was attracted to the light rail a new Toyota Prius every single year for 30 years than to build the light rail. Yet the specific bus-rapid transit alternative that was nominally considered by PSTA is itself phenomenally expensive, costing nearly $50 for every hour of transit riders’ time that it would save.In addition, PSTA has failed to reveal the effects of the proposed light-rail line on traffic congestion. Light rail often increases congestion when it crosses streets and disrupts traffic signal coordination systems. Although Greenlight Pinellas documents indicate that PSTA calculated the effects of light rail on congestion, it did not publish its results, suggesting that it did not want the public to know that it would make congestion worse.As an alternative to light rail and a tax increase, this paper proposes that PSTA introduce eight new rapid bus routes that would provide better bus service to residents throughout the region. These new routes would be funded by contracting out all PSTA bus routes to private operators, which would save taxpayers at least 31 percent per route and probably more. This way, instead of spending more money on poorer quality transportation, as Greenlight Pinellas proposes, taxpayers will get better transit at no greater cost.

Review of Project Connect

Project Connect — a planning consortium sponsored by the City of Austin, Capital Metro, the Capital Area Metropolitan Planning Organization, and Lone Star Rail — proposes to build a 9.5-mile, high-capacity transit line in Austin from East Riverside & Grove to Austin Community College’s Highland campus. Transit vehicles would follow a dedicated guideway — either rails or an exclusive busway — with trains or buses stopping about every one-half mile. Although buses are being considered as an alternative, it is clear that Project Connect planners already favor rail; as a presentation by Project Connect concludes: “Urban Rail is the appropriate mode to meet system needs.”There are several problems with this proposal. First, the proposed rail line is not truly high-capacity transit; though Project Connect has failed to admit it, buses can actually move more people than light rail. Second, the line is projected to cost $1.38 billion, but planners have failed to demonstrate the need for an expensive, dedicated guideway system of either bus or rail. In fact, the peak-hour demand projected for the line is well below the capacity of either buses or light rail. Finally, project planners have greatly overestimated the benefits of the proposed line. For example, far from relieving congestion, light rail will make it worse as it will have priority at traffic signals, disrupting the flow of traffic for everyone else. For much less than the cost of a single fixed-guideway transit line serving a few travelers, Austin can both improve bus service and relieve traffic congestion for all travelers. Traffic signal coordination, staggered bus stops in high-demand areas, increased bus frequencies, double-decker buses on high-demand routes, and the construction of more HOT lanes will smooth traffic flows and provide better transportation for everyone in the Austin area.

A Dynamic Offset Model based on Stop Line Detector Information

Existing traffic networks have to be controlled and regulated efficiently before trying to build new transportation facilities, with an aim to reduce the growing traffic congestion. One of the effective option is signal coordination which helps in improving the uninterrupted flow of traffic. The offset provided for traffic signal coordination is often static assuming constant link travel time making it unfit for varying traffic flows. Present study is aimed at building a dynamic offset model, based on the flow rate and the link length between the intersections meant for coordination. Estimation of travel time required for the vehicles to travel from one intersection to another forms the basis of the offset calculation. The underlying assumption is that the travel time increases with an increase in the rate of vehicular flow, as well as the distance between the intersections. This can be captured by a vehicle detector typically placed at stop line. The relation between travel time and vehicular flow has been verified by conducting studies in congested corridors in Mumbai, India, during peak and off peak hours. An algorithm similar to a vehicle actuated algorithm, but terminate at some common cycle length is used in the development of the models and evaluated using a robust traffic simulator. A non-linear dynamic offset model is hence built, which caters to the real time fluctuating traffic conditions. However, the estimation of vehicular flow rate from the detectors in the field is sometimes difficult and erroneous. To address this limitation, a second model is proposed based on the assumption that the green time provided by the algorithm can be used as a proxy for the detector output and consequently the level of congestion. Accordingly, a dynamic offset model is developed which gives the value of the offset to be implemented based on the green time used and the link length. The models developed are compared with the independent vehicle actuated control and constant offset control. The average delay and travel time are considered as the performance indicator. It is observed that the dynamic offset is successful in improving the coordination efficiency of corridors, even for heterogeneous traffic conditions.

A Quick Offset Optimization Method for Traffic Signal Coordination

To develop a quick offset optimization mehtod for traffic signal coordination scheme, the calculating methods for common cycle length and green split are brought forward firstly. Based on the vehicle delay model under isolated traffic control mode, the progression factor is introduced to improve the model. Then the relationship between progression factor and offset is derived. Minimizing average vehicle delay is selected as the optimization objective, the function with simple structure between the objective and offset is developed. At last, take two adjacent signalized intersections as example, the optimizaiton method is validated and the results show that the method is effective.

Self-Organized Traffic Signal Coordinated Control Based on Interactive and Distributed Subarea

In traditional traffic signal coordination control, all intersections are shared a common cycle and have fixed offsets in one sub-area. The range of sub-area is normally fixed, plan switching is difficult, and the reaction to the traffic problem is slow. In this paper, a self-organized dynamic control strategy is proposed. it decomposes the network optimization into overlapped and interactive problems between Basic Coordination Units (BCU). It presents an interaction-forecast model among intersections, each intersection not only considers its own benefit, but also takes downstream intersections into account. Multi-scenarios simulation shows it works well in all saturation degrees, reduces total delay around 8% to 12.3%.

Combining Static and Dynamic Models for Traffic Signal Optimization Inherent Load-dependent Travel Times in a Cyclically Time-expanded Network Model

Travel times in traffic models are of great interest for developing realistic solutions for traffic assignment and traffic signal coordination in urban traffic networks. In this paper, we present a cyclically time-expanded network for this purpose, which is a static and linear model from its structure. However, it provides enough dynamics to reproduce load-dependent travel times and it is capable to model traffic signals. Thus, this traffic flow model is at the cutting-edge of static and dynamic models, and furthermore, it allows the simultaneous optimization of traffic assignment and signal coordination with exact mathematical programming techniques. We study the inherent properties of the travel times in this model and demonstrate its capabilities by simulation results obtained with state-of-the-art simulation tools.

Effects of traffic signal coordination on noise and air pollutant emissions

Traffic management solutions are increasingly called for to address problems of transport and mobility. In particular, coordinated traffic lights that create green waves along major arterials are an increasingly used strategy to reduce travel times. Although it is usually assumed that an improved traffic flow will result in lower vehicle emissions, little scientific research has been spent on the effects of synchronized traffic lights on emissions. Moreover, because changes in traffic flow do not necessarily influence travel times, noise and air quality in the same way, there is a clear need for a combined approach. This paper reports on a computational study in which a microscopic traffic simulation model (Paramics) is combined with submodels for the emission of noise (Imagine) and air pollutants (VERSIT+). Through the simulation of a range of scenarios, the model is used to investigate the influence of traffic intensity, signal coordination schemes and signal parameters on the noise, carbon dioxide, nitrogen oxides and particulate matter emissions along an arterial road equiped with a series of traffic lights. It was found that the introduction of a green wave could potentially lower the emissions of the considered air pollutants by 10%–40% in the most favorable conditions, depending on traffic flow and signal timing settings. Sound pressure levels were found to decrease by up to 1 dB(A) near the traffic signals, but to increase by up to 1.5 dB(A) in between intersections. Traffic intensity and green split were found to have the largest influence on emissions, while the cycle time did not have a significant influence on emissions.

Effect of signal coordination on traffic emission

This study investigates the effect of traffic signal coordination on emissions and compares it with their effects on operational performance measures of delay and stops. Various platoon ratios are obtained by simulating cycle lengths and offsets. Our results indicate that the impact of the cycle length on delay is more significant than those on stops and emissions for under-saturation traffic conditions. Given a fixed cycle length, increasing the platoon ratio can reduce delay, stops, and emissions, with reduction in emissions being correlated with stops than delay. The effect on emissions from the platoon arrival with respect to the onset of green or red indication is identified. With the same cycle length and platoon ratio, the early arrival situation, when the leading vehicles of a platoon encounters the red signal, can generate more emissions than are associated with late platoon arrival, when the last few vehicles in a platoon are stopped at the intersection by the onset of the red signal.

Regional Traffic Control System Study Based on Pattern Identification

The thesis introduces traffic patterns definition and identification. Combined with actual project it has established the regional traffic signal coordination and control system based on particle swarm K-means clustering algorithm pattern identification. It puts forward system structure and working principles with discussions focused on several key problems existing in traffic pattern identification process.

Assessment of the impact of speed limit reduction and traffic signal coordination on vehicle emissions using an integrated approach

This paper examines the effects of two traffic management measures, speed limit reduction and coordinated traffic lights, in an area of Antwerp, Belgium. An integrated model is deployed that combines the microscopic traffic simulation model Paramics with the CO 2 and NO X emission model VERSIT+. On the one hand, reductions in CO 2 and NO X emissions of about 25% were found if speed limits are lowered from 50 to 30 km/h in the residential part of the case study area. On the other hand, reductions in the order of 10% can be expected from the implementation of a green wave signal coordination scheme along an urban arterial road.

Comparing Ant Colony Optimization and Genetic Algorithm Approaches for Solving Traffic Signal Coordination under Oversaturation Conditions

Abstract: This article proposes to solve the oversaturated network traffic signal coordination problem using the Ant Colony Optimization (ACO) algorithm. The traffic networks used are discrete time models which use green times at all the intersections throughout the considered period of oversaturation as the decision variables. The ACO algorithm finds intelligent timing plans which take care of dissipation of queues and removal of blockages as opposed to the sole cost minimization usually performed for undersaturation conditions. Two scenarios are considered and results are rigorously compared with solutions obtained using the genetic algorithm (GA), traditionally employed to solve oversaturated conditions. ACO is shown to be consistently more effective for a larger number of trials and to provide more reliable solutions. Further, as a master‐slave parallelism is possible for the nature of ACO algorithm, its implementation is suggested to reduce the overall execution time allowing the opportunity to solve real‐time signal control systems.

Variable-Bandwidth Progression Optimization in Traffic Operation

Attempts are often made to find an optimal coordinated control plan for a group of traffic signals in urban areas, such that platoons of vehicles can proceed through a continuous series of green lights without stopping, thereby reducing considerable unnecessary delay. One main objective of coordinated control is to provide the maximum bandwidth progression by adjusting the offset and phase sequence pattern for each signalized intersection. Most models and methods currently being used are based on mixed-integer linear programming (MILP), which is a mathematical optimization model originally formulated by Little et al. in 1966. A basic limitation of the MILP is that it adds a large number of complex constraints for traffic control networks. In this paper, a new simple method is introduced for finding the optimization plan of arterial and network control by maximization of variable bandwidth. This method has not any “loop” constraints and a completely new approach compares to the MILP method applied in this field. In addition, the results of two examples this paper provided validity and feasibility of this new approach in real applications of traffic signal coordination control.

Evaluation of Effectiveness of Coordinated Signal Control in Reducing Vehicle Emissions during Peak Hours versus Nonpeak Hours

Traffic signal coordination is not only an effective traffic flow operational strategy to smooth the traffic in urban areas but is also considered a potentially effective means to reduce vehicle emissions. Nevertheless, when traffic flow speed decreases, the effectiveness of using traffic signal coordination to reduce emissions may be substantially weakened. This paper evaluates the effectiveness of signal coordination in reducing vehicle emissions during peak versus nonpeak hours, two speed scenarios. The operating mode binning approach is used as a statistical technique to calculate emission rates, and the difference in emissions is adopted as the measure of effectiveness in the study. Data used in the study include Global Positioning System data and emission data collected from real-world tests. It was found from the study that coordinated signal control could reduce vehicle emissions in the following order (most to least reduction): oxides of nitrogen, carbon dioxide, hydrocarbons, and carbon monoxide. However, its effectiveness would be impaired during peak hours when the speed was decreased. Meanwhile, the test shows that the effectiveness will be affected by driver behavior. Either low average speed or intentionally slow driving will weaken the effectiveness of coordinated control in reducing vehicle emissions. The research in this paper is a pilot study and the same methodology will be used to conduct a more thorough study.

Modelling motorcycle emissions and driving cycle in Edinburgh

This paper explains the modelling of emission in real world onboard measurement under local driving condition for engine size 1000cc and 600cc for motorcycles in Edinburgh. Impact of instantaneous speed, acceleration on emission have been investigated on the air quality management area (AQMA) in Edinburgh. Emission directly observed from the analyser have been converted from ppm and % unit into gm/sec by using the fuel consumption estimates and carbon mass balance equation Finally average emission factors for CO, HC, and NOX along the corridor have been estimated on time based (gm per second) and distance based (gm/km). Since emissions are primarily affected by speed, therefore a correlation between emission factors and speed have been developed. Onboard emission measurements have advantages to collect the emission data into different driving cycle i.e. vehicle operating modes (idling cruise, acceleration, and deceleration). This has been further investigated by developing the relationship between time spent in these modes and emission. These types of models are suitable, in sustainable development of transportation system, traffic demand management, signal coordination, and environment friendly application for Intelligent Transportation System (ITS).