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3.0 Signal System Characteristics

In order to identify the key characteristics of signal systems that should be taken into account in the development of a SSAMS, the state-of-the-practice in signal system asset management was evaluated through a literature review, agency survey, and follow-up in-depth interviews. The detailed findings of the state-of-the-practice review were documented in an earlier report prepared for this project,1 and are summarized below.

3.1 State-of-the-Practice Review

The state-of-the-practice review targeted mid-sized agencies (200 to 1,000 signals), which have a sufficient degree of complexity in their operations to merit a structured approach to asset management, but not such a large scale so as to create unique requirements or allow for major efforts that are not representative of the majority of agencies. In order to identify the “mid-sized” agencies, a copy of the latest (2000) ITS Deployment Tracking Survey2 database was obtained from Oak Ridge National Laboratories. This database covered agencies in the 75 largest U.S. metropolitan areas. Figure 3.1 shows the distribution of agency size included in this database. Of 428 total agencies included in the ITS Tracking Survey database, 41 percent (176) have less than 100 signals; 21 percent (89) have between 100 and 200 signals, 32 percent (137) have between 200 and 1,000 signals, and the remaining six percent (26) have over 1,000 signals.

Figure 3.1  ITS Deployment Tracking Survey
Distribution of Agencies by Number of Signals

Figure 3.1.  This bar chart shows the distribution of agency size included in this database.  Of 428 total agencies included in the sample, 41 percent (176) have less than 100 signals; 21 percent (89) have between 100 and 200 signals, 32 percent (137) have between 200 and 1,000 signals, and the remaining six percent (26) have over 1,000 signals.

Twenty-six mid-sized agencies identified from the ITS Tracking Survey database agreed to participate in this state-of-the-practice review. These agencies were asked to provide information about the following three aspects of signal system operations and management:

  1. Physical – The specific physical components that make up signal systems (e.g., signal heads, loop detectors, video cameras, controller boxes);
  2. System – The capabilities and configuration of hardware, software and communications infrastructure that connects and controls the signal system to provide the traffic management function; and
  3. Personnel – The staff resources available for operating and maintaining the signals and the institutional and management approaches used to provide these staff resources.

The data collection instrument was designed to gain insights into how agencies balance investments in these three areas as they maintain and improve their signal systems.

Results of the agency survey indicate that agencies are tracking and managing the physical, systems and personnel components of their signal systems at varying levels of sophistication, as appropriate to the scale and complexity of their systems. Tools and techniques are in place to optimize system performance for the road user; most agencies track performance of intersections or groups of intersections with respect to safety and delay, and use this information to identify improvement needs. As agencies upgrade signal management technologies, new real-time capabilities for performance monitoring and control will come on-line which will allow further performance gains to be realized.

With respect to the physical aspect of signal systems, most agencies have basic inventory tracking and maintenance management systems, but relatively few maintain data on failure rates and historical repair costs that would be needed to make a case for doing more preventive (versus reactive) maintenance. This type of data would also be needed to develop predictive capabilities in support of performance-based budgeting approaches. Given the agencies’ concerns with respect to budgetary and staff limitations and their desire to reduce repair costs, improved capabilities to both prioritize investments and to demonstrate what could be achieved with additional resources would be valuable.

Agencies are considering tradeoffs between technology and staff resources, and the application of asset management principles will increase the sophistication of this analysis.

Based on the data collected, the following conclusions can be drawn regarding the state-of-the practice in relation to the asset management principles stated in the previous section:

Policy-Driven and Performance-Based – Signal system goals and objectives focus on two major areas. One is performance of the system equipment in terms of reliability and function. The other is the level of service provided to the end-user in terms of throughput and safety. These areas are related in that unreliable equipment impacts the road user. Performance measurement for signal systems appears to be well understood and mature with respect to end user measures, particularly at the site-specific (as opposed to systemwide) level.

Analysis of Options and Tradeoffs – Based on agency ratings of priorities, it appears that practitioners do consider a variety of alternatives for signal system maintenance and improvement – spanning physical upkeep of existing components, upgrades to components, implementing new traffic management capabilities, additional coordination within and across jurisdictions, adding signals, adding staff, and building staff capabilities. However, resource limitations constrain the set of feasible options for improving system performance.

Decisions Based on Quality Information – Some agencies have implemented integrated management systems to link inventory data, maintenance management, and customer request management. Some are making use of signal management systems which support real-time monitoring and control. Simulation models are being used to improve signal optimization and maintenance management systems are providing improved information on equipment status. However, many agencies operate in a reactive mode and both staff and analytical tools for data reduction and analysis are scarce.

Monitoring to Provide Clear Accountability and Feedback – Maintenance management systems, traffic monitoring systems and real-time signal control and performance monitoring systems all offer the potential for a rich set of monitoring information that can be used to improve both day-to-day operations and longer-term strategic investment decisions for signal systems.

3.2 In-Depth Interviews

In-depth interviews were held with the Minnesota DOT Metro Division and the Wisconsin DOT Central Office Traffic Operations Group. These interviews supplemented the state-of-the-practice review, providing more detailed information on signal system management and operations that are necessary for defining the elements of a SSAMS. Key findings were as follows:

MnDOT Metro District

WisDOT

3.3 Overview of Signal System Characteristics

The information collected from the state-of-the-practice review and in-depth interviews has provided insights into the decision-making structure of signal system agencies. This section builds on these reviews, and identifies those characteristics of signal systems that need to be considered in order to determine the types of capabilities to be provided by a SSAMS.

Figure 3.2 provides an overview of the characteristics of a signal system that are relevant to the development of a SSAMS, and shows the logical interrelationships among these characteristics.

Figure 3.2 Signal System Characteristics

Figure 3.2.  This flow chart outlines logical interrelationships among the characteristics of a signal system.  The top box is labeled signal system and has two components:  physical characteristics and operational characteristics.  An arrow labeled affects is directed from the signal system box to another box labeled performance.  Another arrow labeled affects is directed from a box labeled operating environment to the performance box.  This symbolizes that both the signal system and the operating environment affect performance.  An arrow labeled constrain is directed from a box labeled funding sources to another box labeled budgets.  An arrow labeled allocated to is directed from budgets to a box labeled resources.  An arrow labeled used for is directed from resources to a box labeled actions.  Finally, an arrow labeled modify is directed from actions back to the top box labeled signal system.  This symbolizes that funding sources constrain budgets which are allocated to resources that are used to modify the signal system.

Each of these characteristics is discussed below:

The next section of this report presents a model of a “generic” signal system based on a description of the above characteristics. Then, this model is used to define key elements of a SSAMS.

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