4. Literature Review

A rationale place to begin this analysis is a review recent literature related to the fours quadrants of the signal timing process. In this effort, we have attempted to be comprehensive in our review of the literature published during the last few years related to the signal timing process. We have made a serious effort to identify work that we feel can make an impact on improving one or more of the four elements. This section begins with an overview of the process, we then discuss the literature within the context of each of the four major elements.

4.1 Signal Timing Process

As noted in the Introduction to this report, it is convenient to categorize the signal timing process into four elements as shown on Figure 6. The circular format of this depiction emphasizes the fact that signal timing must be considered as a continuous process. We show that the Documentation element in the center of the process forms the common element among the four circular tasks. This is somewhat arbitrary; the display could have been shown with three elements surrounding a central element which would be comprised of Data Management and Documentation. We chose to separate Data Management from Documentation to be able to more clearly emphasize data management needs distinct from the Documentation needs.

Figure 6. Signal Timing Process.

As we evaluated the literature with respect to the overall process, we found that there was no nationally accepted document that described that entire signal timing process. Several states produce a signal timing manual that defines the suggested approach for that state. The Minnesota DOT, Traffic Signal Timing and Coordination Manual[2], is one such document. This is a large document with more than 270 pages. The Manual is very comprehensive and intended to be the reference document used in a three day course on traffic signal timing and includes a chapter at the end with several examples. Beginning with signal timing theory, it continues with a significant discussion of data collection, a topic frequently glossed over. The primary thrust of the Manual, is the application of Synchro as the primary signal timing optimization tool. The Manual describes the coordinated operation parameters of the Econolite controller that is a standard unit used by the Agency. This Manual is the only example found that covers the entire signal timing process including data collection, optimization, parameter installation, and performance evaluation.

4.2 Signal Timing Optimization

Over the years, this is the area that has received the most attention of the academic community. The theoretical work on which most of modern day signal timing is based is the research conducted in the Untied Kingdom in the late 1950s by Webster[3]. This work was based on pre-timed control and has been incorporated in most traffic optimization and simulation models. The research was primarily focused on the investigation of delay at pre-timed intersections.

Other researchers expanded this research to include the operation of actuated controllers. In 1969, Newell and Osuma[4] showed the relationship between average delay and various controller settings at pre-timed and actuated intersections. They demonstrated that delay for an actuated signal was less that that for a pre-timed signal. This work was more of an investigation into intersection delay than signal timing. In 1976, Staunton[5] summarized the fork of various signal control researchers. This paper provided comparisons of delay produced by both pre-timed and actuated controllers under different demand conditions. Staunton demonstrated that full-actuated control with 2.5 second extensions would always provide better performance than pre-timed control.

These programs provided the foundation for the development of the signal timing optimization programs that are in current use in the Unites States. Much of the development work on Transyt-7F and Passer II was completed in the 1980's. While there have been substantial improvements in recent years, the improvements have tended to be in the area of user interface improvements and migrating the programs from a mainframe computer environment to a desktop computer environment.

The most recent developments have focused on Adaptive Control, a topic beyond the scope of this analysis. There are, however, several, new programs that are designed to provide a solution for a specific signal timing problem. Passer III is one such program. It is designed to optimize the signal timing for diamond interchanges. Passer IV is another such program. It is designed to provide a maximum bandwidth signal timing solution. We do not expect to encounter a "new" optimization program which will prove to be superior to the existing programs; it is felt that more significant advances in the signal timing process will be made in areas other than signal optimization.

In our review of the literature, we noted one significant void. There is no model that is designed to provide the optimized signal settings for an isolated, actuated intersection. It is possible to use a program like Synchro or Passer II to time an individual intersection. But this is, at best, a work-around solution. In the past SOAP-84 filled this role, but this program has several drawbacks, not the least of which is SOAP-84 models a fixed phase sequence type of operation and does not support the phase flexibility inherent in modern actuated controllers.

4.3 Field Deployment

One area where significant improvements are expected is in the translation of the optimization model outputs to the parameters required by the various traffic signal systems.

Traditionally, signal settings were set in the field by traffic signal technicians. In many jurisdictions, this is still the way signal settings are installed. Before the NEMA TS-1 and Model 170 controllers were introduced in the 1970s, this was not an onerous task. Most intersections used two or three phase controllers which had only five or six parameters per phase. At the most, the technician had to calibrate 18 parameters. With the common use of eight phase controllers, all of which supported 20 or more timing parameters per phase, the concept of having these parameters installed by hand becomes somewhat more daunting. In reality, the modern controller uses thousands of parameters, far more than one could expect to be installed manually without error.

Fortunately in this same time-frame when complex controllers were evolving, the market produced the "Closed Loop System" (CLS)." The CLS has many variants. All of the controller suppliers in the United States provide a proprietary CLS that used their products. As a result, each CLS is different and provides unique functions. All, however, have similar attributes and encompasses designs that use the same basic control strategies. As with most human endeavors, the devil is in the details. There are as many different approaches as there are CLS suppliers and systems. Most may be summarized as belonging to one of two philosophies: provide the User with the maximum flexibility by providing easy access of all control parameters, or shield the User from the complexities of coordinated operation by generating the secondary parameters by embedded algorithms.

While Traffic Engineers think in terms of Cycle, Split and Offset, the controller actually uses a few additional parameters. The only consistent reference point in the cycle of an actuated controller is the end of Main Phase(s) Green. These are usually phases two and six. This reference point is called the "Yield Point" in the actuated controller cycle. This is the point in timing plan when the controller is scheduled to leave Main Street green and service all other phases in the cycle.

The most simple actuated controller strategy is to allow the controller to service calls at the "Yield Point" and to depend on the Maximum green timers to terminate each phase until the controller cycles back to Main Street green. While this strategy has the advantage of being simple, it is not very flexible since the split is determined by the Maximum setting.

One way to provide more flexibility is to have a separate Force-off timer for each phase. The Force-off function is like a Maximum timer and it causes the phase to terminate when the Force-off setting is reached. With these definitions, one can see that a signal timing plan could be defined by an Offset, and a Force-off for each phase. The Force-off time for the coordinated phase(s) is 0, which is also the "Yield Point".

There are two issues to be noted with respect to the "Yield Point" operation described above: if there is no demand on an opposing phase at the "Yield Point", the controller will remain in the coordinated phase(s) for another cycle. Because this mode of operation can result in significant delays to minor phase traffic, the concept of a "Permissive Period" was introduced. In essence, the "Permissive Period" stretches the "Yield Point" over a larger portion of the cycle. The effect of a "Permissive Period" is to allow calls on minor phases that arrive after the "Yield Point" to be serviced as long as there is sufficient time in the cycle to enter the coordinated phase(s) at the planned time. In addition to Force-off, controllers can be designed to use Holds, an input that causes the controller to remain in a phase to which a Hold has been applied

How the different suppliers treat the coordination parameters of Cycle, Offset, Force-off, Hold, and "Permissive Period" is defined in the documentation of each system. The suppliers generally do a good job of defining the parameters used by their system. They explain what each parameter does and what the valid range is. They do not, however, explain when a particular mode of control should be used. For example, the discussion above described three different modes of control: Yield Point using Maximum timers, Yield Point using Force-off timers, and Permissive Period using Force-off timers. All suppliers describe how each of these modes can be used with their equipment. None, however, describe when a particular mode should be used. We found several references in the literature that address the overall translation problem.

In 1996 Skabardonis[6] investigated the development of improved procedures for applying the MAXBAND, Passer, and Transyt-7F timing programs to arterials and grid networks with actuated controllers.

Of the many phase related settings on the controller, there is relatively little information available to help the user select the right settings. In 1995, Orcutt[7] defined two basic types of intervals that control vehicle flow and are timed by a traffic signal controller: safety-related intervals, and discretionary intervals. This study described the appropriate use of these intervals as well as the use of gap-reduction settings.

Change[8] conducted research to develop a set of reliable control strategies to allow users to improve the overall design and operation of actuated controllers in conventional coordinated systems.

Bonneson and Lee[9] evaluated alternative control sequences and settings for the actuated, three-phase diamond interchange. The settings evaluated include the minimum green interval, maximum green interval, and passage time. The objective of this project was to develop guidelines for establishing controller settings that would generally yield low-delay (if not lowest) operation for the range of volumes encountered during a typical weekday.

After reviewing the literature related to signal timing parameters published during recent years, we can make several general observations:

1. There has been little published by the academic community in this topic in recent years. Researchers, in general, have focused on other related topics, like adaptive control and simulation.
2. Most of the information available in this general area is provided by vendor user manuals. These manuals describe how the parameter functions. They do not tell the user how to use the parameter. For example, the Extension Time, Time-To-Reduce, and Minimum Gap are the three parameters that provide the gap reduction feature. While all manuals tell the user how to input the three parameters and what parameter range is supported by the system, no vendor manual tells the user when to use gap reduction feature, nor do the manuals guide the user to the optimum values for these parameters.
3. There is a need for a definitive manual to guide the traffic signal engineer for setting the various actuated controller parameters. While there are guidelines to help the engineer with many of the settings, the clearance, change, and maximum intervals are rather well documents. However, many other parameters are less well documented. For example, we know of no procedures that are supported by research to identify the minimum gap or time-to-reduce parameters. This observation is closely related to the previous observation that there is no optimization program explicitly designed for isolated, actuated controllers.
4. The acceptance of UTDC by the private sector has made a significant impact in making the field deployment of timing data much more efficient. The development by the private sector has been driven by competition. As soon as one major vendor claimed an interface with Synchro using UTDF, all vendors began working on a version of this type of interface. It is interesting to note that the market has forced virtually all controller vendors to interface with Synchro.

The following vendors support the UTDF interface with Synchro: Eagle (Actra), BI Tran Systems, Inc. (QuicNet/4), Econolite (icons), and Naztec (Streetwise). There may be other vendors in addition to the ones noted above.

All of these systems support multiple traffic signal plans that can be called by time of day and by traffic flow measures. All of these systems support the capability of measuring the traffic flow rates from sensors installed in or over the roadway. By combining these two features with the interface to Synchro, one can claim a true "closed loop" system. It works like this. Data are collected for a particular period by the system. These data are then electronically transferred to Synchro using the UTDF format. Synchro is executed and optimum timing parameters are generated. These parameters are converted to system input parameters and are electronically transferred from Synchro back to the traffic control system. This flow of information from the street, to the optimization model, back to the system is called 1 ½ Generation Traffic Control. This capability is available with most system currently deployed.

Although this capability exists, it is not often used. One reason is that few systems have enough instrumentation to actually derive new timing plan data. Another reason is that although the capability is inherent in the system design, few vendors are promoting this capability.

While there is considerable promise to improve the signal timing process in this general area of parameter conversion, the most significant advances have been made by the private sector responding to competitive pressures. This area is very difficult to address because it is basically a linkage between two packages that are in the private sector, Synchro and QuicNet/4, for example. There are other examples that we could cite that are comprised of a linkage between a public sector program (Transyt-7F or Passer II) and a private sector system, Actra for example. Perhaps the best contribution to be made in this area is to support training programs that encourage better use of the capabilities of systems.

4.4 Performance Evaluation

As we illustrated in the "Looks OK" decision box in the flow chart we used in Figure 2, this element more often than not is very arbitrary. What looks OK to one engineer may very well not look OK to another. The only alternative way to evaluate signal timing performance is simulation.

While most simulation models provide the same measures of effectiveness, their values frequently differ from model to model given identical inputs. This is not an unexpected result since the models use different assumptions and different algorithms to derive the estimates. During the last few years, researchers have compared the models to each other and to ground truth to try to determine which provides the most accurate estimates.

Mystkowski and Khan[10] compared the queue length estimates based on several models and field results. The models considered were CORSIM, version 4.01; Passer II-90, version 2.0; Synchro, version 3.0; SIGNAL94, version 1.22; Transyt-7F. This paper documented the methods used to estimate queue lengths and provides clarification on the definitions used for the different models.

Seeking new measures of effectiveness to be able to accurately evaluate intersection performance is another goal of many researchers. Husch's Intersection Capacity Utilization[11] is one such measure. The Intersection Capacity Utilization provides a straight forward method to calculate an intersection's level of service. The method simply takes a sum of the critical movement's volume to saturation flow rates.

In general, the trend in recent years is to use simulation to evaluate intersection performance. For example, Transyt-7F can be used to generate optimum signal settings. Transyt-7F can also be used to evaluate existing signal settings. The model can be executed with the signal settings frozen and it will produce measures of effectiveness based on the existing settings. The model can be executed again and allowed to seek an optimum. The measures of effectiveness from the optimized settings can be compared to the measures of effectiveness from the original settings to get a quantified estimate of the probable improvement. This, however, requires a lot of work, generally more than the typical engineer is willing to do to retime a traffic signal.

Another approach is to link the simulation software with the optimization software into an integrated system. Trafficware Corporation offers this capability by allowing the user to optimize the settings with Synchro and then to evaluate the performance with Simtraffic. Through the use of the UTDF capability, the user can also easily export the data to Passer II, CORSIM, Transyt-7F or Highway Capacity Software.

Trafficware is not the only private sector firm to offer this capability. Strong Concepts markets the TEAPAC program suite. TEAPAC is a family of programs that optimize a wide range of traffic engineering procedures within the transportation engineering and planning disciplines. As a part of this suite, Strong Concepts has developed a series of pre and post processor data management programs that allow the user to use one, standard user interface for Passer II, Transyt-7F, and Netsim.

The trends in the area of Performance Evaluation are closely linked to the Data Management issues discussed in the next section. One of the most difficult issues to deal with is the question of how to support solutions that have been developed by the private sector. Trafficware and Strong Concepts as well as others have developed evaluation and data management solutions that address many of the issues related to the signal timing process. Neither vendor, however, has developed a solution to the traffic data input problem although both have made good strides in managing the data once it is collected. Issues specific to the Data Management are discussed in the following section.

4.5 Data Management

Of the four elements of the signal timing process, this is the least explored; but we feel that this element has highest potential to improve the signal timing process. Data management concerns frequently begin and end with Data Collection – specifically, Intersection Turning Movement Counts (TMCs). These data are the common denominator among all models and the one necessary input required of all efforts to time signals. While turning movement data are indeed the crux of the issue, one must take a much broader view to fully appreciate the Data Management issues. Can turning movement data be estimated from measured intersection input and output flows? How can TMCs there were observed on different days be combined into a balanced network? Can TMCs be generated using "short count" techniques? What is the best way to manage data across the network and across time?

Data collection is only the beginning of the data management problem. Traffic data management has both a spatial and a temporal component. The spatial component determines where the data can be used. For example, data collected between two intersections can be useful in estimating turning movement data at the two intersections. In this example, the spatial aspect impacts three different locations: the initial location and the location of the two intersections.

The temporal dimension is important from two aspects: quantity and descriptive characteristic. The quantity is simply a byproduct from the fact that traffic demand changes significantly over the course of a day. The traffic signal timing process, whether manual or automated, requires demand estimates that are representative of periods within the day, the AM Peak Hour for example. Because these periods of relatively constant demand are different at different locations, it is necessary to collect data over significant periods of the day. In addition, to be useful, the data must be aggregated in short periods, such as 15-minute periods. The spatial and temporal requirements combined imply that the number of data elements necessary to support the signal timing process amounts to a very large database.

Frequently, data collection consists of 12-hour counts summarized into 15-minute segments. Since a normal intersection has four approaches and supports three movements per approach, the turning movement data typically consists of 576 (12x4x4x3) data elements per intersection per day. Obviously, with many intersections and data extending over more than one day, dealing with this amount of information can be a significant burden.

As the desktop computer becomes evermore pervasive in the traffic engineering offices, many engineers have developed applications that vastly improve the data management task when compared to manual means. While conducting the literature search for this topic, we found many instances of creative engineers applying spreadsheets and other software packages to solve data management problems. Some of the more interesting studies are described below.

Dowling Associates, Inc., a traffic engineering and transportation planning consulting firm based in Oakland, California developed a program, TurnsW that forecasts turning volumes from existing turning movement volumes and forecast future approach and departure volumes. This program is a mechanization of the techniques described in NCHRP 255, "Highway Traffic Data for Urbanized Area Project Planning and Design", Chapter 8. This program derives forecast turning movements using an iterative approach which alternately balances the inflows and outflows until the results converge (up to a user-specified maximum number of row and column iterations).

If observed turning volumes are not available, then the estimated turning percentages of the future year assigned inflows can be used. The user may 'Lock-In' pre-determined volumes for one or more of the forecast turning movements. The program will then compute the remaining turning volumes based upon these restrictions.

While neither this program, nor the procedure in described NCHRP 255, was developed with signal timing in mind, the process of estimating turning movement flows given estimates of intersection input and output flows is very useful for signal timing exercises. For near real-time traffic flow estimates, the inflows and outflows can be provided by system detectors. For off-line optimization, traffic flow demand networks can be developed from link directional counts. We feel that this is an area where significant progress can be made in the overall signal timing process.

A paper[12] by Gerken, "A practical Approach to Management Traffic Data for Large Scale Studies was prepared described the work conducted in preparing an Environmental Impact Statements (EIS). This effort required peak hour intersection Level of Service (LOS) calculations for over 60 intersections for a base year and future-year scenarios (nearly 1,100 intersection data records). Tight time constraints and the need for efficient stewardship of this large data set lent itself to employing a data management tool. The traffic engineering software package, Synchro, was used for this task.

In this study, existing turning movement counts (TMC), geometric conditions, and signal timing were entered into peak period Synchro files. The Synchro base year TMC were exported in comma delimited (CSV) file format and converted to approach turn percentages using a spreadsheet program. The regional transportation planning model output provided daily link volumes for each scenario. Intersection approach volumes were then determined using historical K and D factors. Incorporating the approach volumes into the TMC spreadsheet provided horizon year TMC. The TMC were then imported back into the Synchro file and optimized to provide future year intersection LOS. This procedure provided considerable timesaving in both data error checking and traffic analysis. Once the data set was entered into Synchro all further data management and analysis was electronically handled, therefore reducing data entry time and the potential for data handling errors.

This effort illustrates use of UTDF by practitioners to manage large data sets. UTDF enables data exchange among many proprietary software programs such as spreadsheets, text editors, or database programs as well as signal optimization programs. UTDF also provides a means to electronically manipulate standard traffic data, in the case of this study, traffic volumes. UTDF uses text files to store and share data. Both comma delimited (CSV) and column aligned text files are supported. The column aligned files can easily be manipulated with a text editor.

Another project[13] conducted by Martin developed and evaluated a new model, Turning Movement Estimation in Real Time (TMERT), that infers unknown traffic flows from measured volumes in sparsely detectorized networks. This model also has the same potential as the Gerken report noted above.

Nihan and Davis[14] examined the use of prediction error and maximum likelihood techniques to estimate intersection turning and through movement probabilities from entering and exiting counts.

Another report[15] documents a method for developing detailed traffic forecasts and turning movements for use by Texas in roadway project planning and design. The methodology uses a combination of current TxDOT corridor analysis procedures, TRANPLAN travel forecasting applications, and traffic refinement and turning movement estimation procedures from NCHRP Report No. 255.

Davis and Lan described another method of estimating turning movements using a statistical approach was reported[16] in 1995. When it is possible to count the vehicles both entering and exiting at each of an intersection's approaches, methods based on ordinary least squares can produce usable estimates of the turning movement proportions, but when the number or placement of the detectors does not support complete counting, these methods fail. The feasibility of estimating turning movement proportions from less-that-complete sets of traffic counts is assessed, and the statistical properties of less-than-complete count estimates are compared.

One primary conclusion that one can draw from this review of the literature related to data management, it that the critical issue is Turning Movement counts. No matter how one conducts the effort, manual turning movement counts are expensive. Most Traffic Engineers consider four plans to be the minimum required for proper signal operation: AM Peak Plan, Day Plan, PM Peak Plan, and the Night Plan. The minimum need, therefore, is to have a turning movement count for each of these four periods; and further, the need is to be able to collect or derive these data at minimum expense.

One way to reduce this expense is to reduce the time required to conduct the counts. Many traffic engineers use "short counts" to develop signal timing plans. Short Counts are normal turning movement counts that are conducted over periods of less that normal. Different agencies follow different procedures in conducting these short counts. There is a need for a defined process that is supported by research to guide the practitioners in conducting short counts.

4.6 Documentation

The final topic in the Signal Timing Process is the glue that holds the entire process together, Documentation. This all-encompassing topic includes all activities related to the process to include the means to recording all changes to the system. It is important to realize the needs of all users of this information. This includes not only the engineering personnel who are responsible for developing the timing data, but it also includes the technicians who are responsible for installing the data in the field, and the technicians who repair the equipment in the electronic shop, and the personnel responsible for operating the computer system when applicable.

Many traffic control systems had the capability to log all database changes. The problem is, the logged data is frequently coded and very difficult to analyze. Improvements in identifying what data should be logged and developing meaningful ways to display the information retained by the system should help the users identify trends in system demand and operation.