Green Splits Research Articles

Robust Signal Timing for Arterials under Day-to-Day Demand Variations

This paper formulates a scenario-based stochastic programming model to optimize the timing of pretimed signals along arterials under day-to-day demand variations or future uncertain traffic growth. Demand scenarios and their corresponding probabilities of occurrence are introduced to represent the demand uncertainty. On the basis of a cell-transmission representation of traffic dynamics, cycle length, green splits, phase sequences, and offsets are determined to minimize the expected delay incurred by high-consequence demand scenarios. A simulation-based genetic algorithm is proposed to solve the model, and a numerical example is presented to verify and validate the model.

Generating More Equitable Traffic Signal Timing Plans

Signal timing plans designed under a total delay minimization strategy can induce excessively high delays for low-volume movements and result in an uneven distribution of delay among motorists. A multiobjective optimization approach is considered for the minimization of both overall delay and delay imbalance. The multiobjective method is found to be highly successful. Compared with a pure delay minimization strategy, the multiobjective optimizer is able to produce signal timing plans with similar overall delay that have a considerably more equitable delay distribution. Multi-objective optimization provides the traffic engineer with a choice from an entire range of compromise solutions in the two competing objectives. Large reductions in the delay imbalance can be achieved at the cost of small sacrifices in overall delay. Multiphase signal control, shifting green splits in favor of low-volume movements, and decreasing bandwidth provide more-balanced delays at the cost of increasing overall delay.

Modeling urban traffic: A cellular automata approach

In this article we introduce a new cellular automata approach to construct an urban traffic mobility model. Based on the developed model, characteristics of global traffic patterns in urban areas are studied. Our results show that different control mechanisms used at intersections such as cycle duration, green split, and coordination of traffic lights have a significant effect on intervehicle spacing distribution and traffic dynamics. These findings provide important insights into the network connectivity behavior of urban traffic, which are essential for designing appropriate routing protocols for vehicular ad hoc networks in urban scenarios.

A multimodal traffic responsive strategy using particle swarm optimization

The paper describes a model predictive control strategy for multimodal urban traffic regulation for private vehicle (PV) traffic and public transport (PT). By acting on the traffic lights, the strategy aims to achieve two objectives. First to make public transport vehicles respect their timetable and, second, to improve the global traffic conditions. Based on a complex model, the strategy determines the optimal green splits and the offsets of the traffic lights. The optimization problem is multiobjective and resolved by the particle swarm optimization algorithm. Two criteria are proposed for private vehicle traffic and public transport. One of the originalities of this work is that the two criteria are expressed globally and are related since the PT progression model depends on the PV traffic. Two PSO algorithm versions are used: the original algorithm and a modified version expected to be more efficient. The efficiency of the strategy is evaluated on a large virtual urban network.

Optimization of Adaptive Transit Signal Priority Using Parallel Genetic Algorithm

Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This paper presents an adaptive transit signal priority (TSP) strategy that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of TSP. The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. A VISSIM (VISual SIMulation) simulation testbed was developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer can produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles.

Dynamic traffic signal control using a nonlinear coupled oscillators approach

Traditional signal control systems use prestored timing plans that have been developed offline using historic data. These systems are not responsive to dynamical demand changes of traffic and may deteriorate in performance over time. Dynamic traffic signal control systems can adapt to actual traffic conditions, coping with complex flow patterns and unpredictable variations. They seek continuous optimal system performance. The main goal of this paper is to design a methodology for control of arterial traffic flows. To fulfill this goal, the nonlinear coupled oscillators model is adapted to the traffic signal system of a two-way arterial road. The control methodology is based on measurements of the microscopic occupancy parameters for incoming flows at intersections that have a four-way geometrical structure with four-green splits. The desired signal parameters such as cycle times, green splits, and offsets are adjusted dynamically according to local traffic data. Thus, the desired signal patterns are self-organized through the mutual interactions among the signals. The numerical and case study simulation results demonstrate the effectiveness of the control methodology under the dynamical demand changes of traffic. Key words: traffic control, control systems, nonlinear coupled oscillators, signal control.

Modeling of Delay Induced by Downstream Traffic Disturbances at Signalized Intersections

Macroscopic models that can be used to estimate the delay at signalized intersections caused by downstream traffic disturbances, such as queues in closely spaced settings, are presented. The models use basic traffic flow properties and control parameters at neighboring intersections. The models are applied to a hypothetical two-signal system. The results show that the delay caused by downstream disturbances can be significant and therefore must be included in level-of-service and capacity analyses. The results also show that control parameters, such as offsets and green splits at upstream and downstream approaches, play key roles in reducing delay. Validation by the use of microscopic traffic simulation shows close agreement between the delay estimates from the proposed models and that from the microscopic simulation model.

Modeling of Delay Induced by Downstream Traffic Disturbances at Signalized Intersections

Macroscopic models that can be used to estimate the delay at signalized intersections caused by downstream traffic disturbances, such as queues in closely spaced settings, are presented. The models use basic traffic flow properties and control parameters at neighboring intersections. The models are applied to a hypothetical two-signal system. The results show that the delay caused by downstream disturbances can be significant and therefore must be included in level-of-service and capacity analyses. The results also show that control parameters, such as offsets and green splits at upstream and downstream approaches, play key roles in reducing delay. Validation by the use of microscopic traffic simulation shows close agreement between the delay estimates from the proposed models and that from the microscopic simulation model.

New Optimal Cycle Length Formulation for Pretimed Signals at Isolated Intersections

Under near-saturated or saturated conditions, the optimal cycle length formulation proposed by Webster becomes infeasible because (1) it generates an unreasonably large cycle length as the intersection critical flow ratio approaches one, and (2) it becomes inapplicable if the intersection critical flow ratio is equal to or greater than one. An attempt is made here to rectify this deficiency by providing a simplistic but reasonably accurate formulation for optimal cycle length under saturated conditions. Using the optimal timing variables obtained based on the delay minimization criterion, the functional relationship between optimal cycle lengths and traffic flow parameters, including intersection critical flow ratio, total lost time, and duration of analysis period, is established through a nonlinear regression analysis. The resulting formulation generates fairly accurate estimates of optimal cycle length with 5.7% average deviation from the analytical solutions. The corresponding average delay, however, only deteriorates about 0.9%. The timing plans consisting of the proposed optimal cycle estimates and the equalized degree-of-saturation green splits produce near-optimal delay performance with 3.3% degradation from the optimal solutions.

Analysis of Traffic Flow Characteristics on Signalized Arterials

The characteristics of traffic flows on signalized arterials are examined within a cellular automaton microsimulation model. The model is used to analyze arterial throughput and travel times for given densities, coordination schemes, and signal spacings. A fundamental three-dimensional relationship is established between flow, density, and offsets for signalized arterials. In particular, it is shown that arterial throughput is dependent on offsets and that the constituent single-intersection limiting capacity, as determined by the saturation flow and the green splits, can be realized only under optimal coordination conditions for a limited range of densities on the arterial. This finding is a manifestation of the important role that signal coordination and, in fact, intelligent transportation systems in general play in the operation of urban street networks.

Extensions and New Applications of the Traffic-Responsive Urban Control Strategy: Coordinated Signal Control for Urban Networks

The objectives, approach, advantages, and some application results of recent extensions of the traffic-responsive urban control (TUC) strategy are presented. Based on well-known methods of the automatic control theory, TUC allows for traffic-responsive coordinated signal control of large-scale urban networks that is particularly efficient under saturated traffic conditions. The first version of the TUC strategy controlled only the green splits. After initial development and the first field implementations and evaluations, TUC was expanded to perform real-time cycle and offset control, and to allow for public transport priority. Simulation investigations of the extended TUC application in parts of the urban networks of Tel Aviv and Jerusalem, Israel, by use of the AIMSUN microscopic simulator demonstrate the high efficiency of the new signal control strategy.

Marginal Delay: New Measure for Quality of Service at Signalized Intersections

Most existing analytical models determine signal settings at intersections by minimizing total delay. The main problem with these methods is that when green split is based on minimum total intersection delay, low-volume approaches are penalized. Although this may be appropriate, the extent of this penalty has never been theoretically resolved. A new concept and its methodology for determining traffic signal settings were proposed to provide a theoretical basis for this issue. This new concept, marginal delay, has its inception in marginal analysis and is defined as the increase in total delay resulting from a one-vehicle increase in the approach volume. Given the nature of the existing delay equations, marginal delay also represents the measure of the maximum individual vehicle delay for a given cycle. Three marginal delay equations were derived and analyzed over a range of 265 cases. Marginal delay analysis was applied to signal-setting calculations and compared with existing delay models. The work concluded that marginal delay is a significant variable in the calculation of signal settings, especially when large differences exist between the volumes of the different approaches. Furthermore, marginal delay used in conjunction with total delay can improve current signal-timing methods by quantifying the penalty applied to light-volume approaches and by providing a measure of variance between real-time flow and design flow.

Optimisation of Fixed-Time Signal Timings for Area Traffic Control Using Genetic Algorithm

In this paper, a genetic algorithm is developed to optimise the fixed-time signal timings for area traffic control. The traffic model from TRANSYT is employed to evaluate the performance of a signal-controlled network. The encoding method, reproduction, crossover, mutation and fitness scale in the genetic algorithm are discussed and the detailed implementation of them in the optimisation process is also given. The advantages of the proposed genetic algorithm over the conventional hill-climbing method in TRANSYT are that the probabilistic nature of the genetic algorithm enables a near global optimum to be determined, since the search process covers more extensively the feasible region of the problem; and in contrast to the signal optimiser in TRANSYT the proposed methodology enables the common cycle time, offsets, green splits and stage ordering to be optimised together in a unified manner.

Requirements for automating signal timing plan design

The optimization of signal timing plans for isolated intersections is a complicated procedure. Most current techniques such as the Canadian Capacity Guide for Signalized Intersections and the Highway Capacity Manual rely on relatively simple analytical models to estimate the optimum cycle time and green time splits, and leave the determination of the optimum phasing scheme to the experience of the user. The main problem with current procedures is that, because of the large amount of human effort required, only a very limited subset of all possible solutions can be examined. In addition, none of the current procedures are entirely satisfactory in their ability to deal with complicated congested conditions. The interaction of shared lanes, permitted left turn movements, cycle times, and green time splits requires an iterative approach to the design of signal timing plans, if current methods are to be used. Owing to the large number of calculations that need be done, current procedures are, by and large, computerized. Using any of the procedures currently available, each time a further iteration is needed, a new set of saturation flow rates or volume allocations must be manually coded into the input files of the computerized procedure. Thus, the search for the optimum solution to a signal timing plan problem can require a large amount of engineering time. This article describes the development of a notation and vocabulary that permits the automation of the logical decisions that must be made in order to optimize signal timing plan design. As well, the information that is necessary to define the intersection geometry and volume demands, in order that an automated process can optimize a signal timing plan is presented. The rules that can be used to determine the phase of discharge of each lane and pedestrian demand volume, the lanes that are opposed by a conflicting movement, and the movements that oppose traffic attempting to discharge from a turning lane are also described. Finally, a brief description of the framework of Signal Expert, a computer model that automates all of the above, is provided.

Individual controlled junctions: Optimal design

The phase-based approach is a recent evolution in the field of undersaturated isolated junction control optimization. Using the incompatibilities among the streams, it proceedes calculating the control variable values without the external individuation of a stage matrix. One of these methods, based on a binary linear mathematical model, performs the simultaneous optimization of cycle time, green splits and green scheduling. The model, however, requires a preliminary decision about the composition of the streams and their assignment to the lanes. The flow ratios of the streams, indeed, have to be supposed constant during the cycle. In this paper an idea to remove this last hypothesis is described. It is based on a simple model regarding the behaviour of the users belonging to streams coming from the same access. A numerical example using a test junction is shown; the obtained results are compared to the ones deriving from a standard phase-based method.

An expert assistant for selecting green splits, cycle times, and phasing schemes based on the Canadian Capacity Guide procedures

The determination of the optimum phase scheme, cycle time, and green split for an isolated traffic signal is usually a very tedious and time-consuming activity. Several computer packages, such as the Micro-Sintral program, have been developed to assist in such situations by automating many of the calculations for a given set of inputs. Unfortunately, the inputs are often equally difficult to determine, and as they may depend upon the ultimate outcome of the optimization process, several time-consuming iterations, during which new input values must be calculated, are required. This paper presents a program called Signal Expert which automates the above iterations and therefore greatly reduces the traffic engineer's efforts in generating a new signal timing plan based on the rather sophisticated procedures that are outlined in the Canadian Capacity Guide. The benefits of applying this new program are illustrated and discussed using the example intersections that are analyzed in the Canadian Capacity Guide and in the Micro-Sintral User's Manual. Key words: isolated intersections, capacity, delay.

The optimum green split of a cycle time

The optimum split of a cycle time for a controlled traffic intersection within an urban network is determined for four objective functions. These are total delay, total number of stops, fuel consumption, and carbon monoxide minimization. It is shown that for each objective function, an optimum value of green split that minimizes the function exists. An expression for the optimum green is derived in each case. It is further shown that these optima do not coincide. A method of determining optimum green split based on a parameter defined as a flow factor is also introduced. This method is a function of the serviceability of the intersection with respect to minimizing total delay incurred by all vehicles at the intersection during one cycle.

Optimization of Traffic Signal Settings by Mixed-Integer Linear Programming

Setting traffic signals in a signal-controlled street network involves the determination of cycle time, splits of green time, and offsets. Part I of this paper considers the network coordination problem, i.e., given a common cycle lime and green splits at each intersection, determine offsets for all signals. Part II considers the more general synchronization problem, i.e., determine simultaneously all the control variables for the network including offsets, splits, and cycle time. In Part I, a link performance function is developed to express the loss incurred by platoons traveling through a signal-controlled intersection us a function of link offset. Integer variables enter the formulation because of the periodicity of the traffic lights: The algebraic sum of the offsets around any closed loop of the network must equal an integral number of cycle limes. The optimization problem is formulated as a mixed-integer linear program and a test network is solved by branch-and-bound techniques using IBM's MPSX package.