1.0 INTRODUCTION

1.1 Why Are Work Zone Performance Measures Needed?

Public-sector agencies and private-sector companies need to understand how well they are designing and operating work zones in order to improve the efficiency and effectiveness of the work zones. They must determine whether any changes made to improve current and future work zones are having the desired effect. The selection, development, and use of performance measures are critical to this improvement effort.

The effect of highway work zones on traveler safety and mobility has become an increasingly important focus area for the Federal Highway Administration (FHWA) in recent years. Current Federal Regulations (23 CFR 630 Subpart J) encourage states to collect and analyze work zone safety and mobility data. The data is to be used to support the initiation and enhancement of agency-level processes and procedures to avoid or mitigate work zone impacts.

The New York State Department of Transportation score the specific traffic control and safety attributes of the work zones it inspects each year, and uses those scores to identify key topics or issues to emphasize in future department work zone training efforts (1).

Performance measures quantify how a particular work zone or several work zones together are affecting traveler safety and mobility. In addition, performance measures can help agencies and contractors assess if and how their work zone safety and mobility policies, processes, and procedures are working well or should be improved.

The challenges related to measuring performance for many agencies and companies include:

1. Identifying which measures are most important;
2. Determining what data is needed for the measures;
3. Determining where and how to get the data; and
4. Determining how to compute the desired measures from the collected data.

Agencies and companies must also consider the availability, accessibility, and applicability of data when deciding which work zone performance measures to focus on and how the measures will be computed and reported. These challenges and decisions can be somewhat daunting. This guidance document has been prepared to assist agencies and companies in developing useful and effective work zone performance measures.

1.2 What Data Is Needed?

In the context of highway work zones, there are three major data needs:

• Performance data;
• Exposure data; and
• Work zone indicator or stratification data.

An overview of the types of data needed is provided in Table 1-1. In essence, Performance data describe “how much” a work zone or group of work zones affects travelers, the agency, and/or the contractor. Performance data includes travel times that motorists using the work zone experience relative to their normal travel times, traffic crashes or worker accidents, and public opinions gathered about driving conditions through a work zone.

Table 1-1. Overview of Data Types

Type	Description	Examples
Performance data (How much did the work zone affect things?)	Data that may be used by an agency, contractor, or other entity (i.e., the public) to evaluate something about work zone operations or its effects.	Travel time changes Crash increases Driver opinions about travel conditions
Exposure data (Who or what was affected by the work zone?)	Data used – in combination with performance data – to normalize to a rate of some type (i.e., per vehicle, per trip, per hour).	Vehicles-miles passing through the work zone, for the entire day or for some subset of the day (i.e., during the peak periods) Hours of temporary lane closures occurring during the project Total worker-hours occurring over a project or project phase Number of person-trips passing through the work zone, for the entire day or some subset of the day
Indicator or stratification data (When or where did the effects occur?)	Data used to further stratify or focus the performance data to a particular subset of the work zone or work operation, such as: during peak travel hours, during certain specific work tasks, during particular project phases, or for work zones with specific features of interest.	Time periods when temporary lane closures occurred The specific hours selected as the AM or PM peak period Specific dates when a project was in a particular construction phase

Meanwhile, exposure data count the “who” or “what” that are affected by the work zone or group of work zones of interest. Most commonly, exposure is measured in terms of number of vehicles, people, and/or miles of travel through the work zone. The number or total hours of lane closures or full roadway closures required during a project is another example of exposure data. In fact, the number of work zones that experience a particular condition (such as a traffic queue that exceeds a particular length) could also be considered a type of exposure data for assessing levels of compliance with an agency’s work zone mobility goals or policies.

Finally, work zone indicator or stratification data focus attention or otherwise target how performance was affected during specific activities, phases, time periods, or other events of the work zone. For example, an agency may be interested in determining whether its current lane closure restriction policy is keeping delays below a selected threshold. In this case, times and locations of lane closures would be indicator data needed to focus on those delays occurring when and where lane closures were in place. Indicator/stratification data might also be used in determining the appropriate exposure data of interest, such as the dates when a project was in a particular phase. Knowing those specific dates, an agency could then use crash data and vehicle-miles-traveled (VMT) through the work zone data to compute a crash rate per VMT during that particular phase.

Overall, the three data types in Table 1-1 are extremely broad and general, and further categorizations within each type are necessary in order to fully assess and understand the current and potential sources for such data and the opportunities to use the data for work zone performance measurement. Key categories of work zone performance, exposure, and indicator or stratification data addressed in this document are shown in Table 1-2. These categories were verified through Delphi survey techniques, using an expert panel of practitioners assembled for this document development, as being both important and useful to many different audiences with possible interest in work zone performance.

With regards to how much work zones affect conditions, four categories of performance data are viewed as important:

• Mobility – data that characterize how trip duration for an individual or the number of trips being made are affected by a work zone;
• Safety – data that characterize how risks to travelers and highway workers are affected by a work zone;
• Customer satisfaction – data that characterize how travelers, residents, and business owners in or near a work zone perceives its effect on them; and
• Agency and contractor efficiency and productivity – data that can be used to assess contractor/agency efforts to minimize the duration and extent of travel impacts from a work progress perspective.

Within these main categories, subcategories also exist. As an example, within the mobility category, performance data can be further subdivided into the following subcategories:

• Throughput;
• Unit travel times or delay;
• Travel time reliability; and
• Traffic queues.

Table 1-2. Work Zone Performance Data Categories

Type	Categories	Subcategories
Performance Data	Mobility	Throughput Unit travel time Delays Travel time reliability Queues
Performance Data	Safety	Crashes Safety surrogates Worker accidents
Performance Data	Customer satisfaction	Project-specific satisfaction Agency or region-wide satisfaction with work zones
Performance Data	Agency and contractor productivity and efficiency	Construction productivity Roadway durability
Exposure Data	Traveler/vehicle counts and travel distances	N/A
Exposure Data	Durations of specific work tasks or conditions, worker-hours in the field	N/A
Exposure Data	Work zone activities/conditions	N/A
Indicator or Stratification Data	Roadway classification/conditions	N/A
Indicator or Stratification Data	Work zone activity/conditions	N/A
Indicator or Stratification Data	Events (incidents, special events, weather, etc.)	N/A

Likewise, the safety performance category can be further divided into the following:

• Traffic crashes;
• Operational safety surrogates; and
• Worker accidents.

As Table 1-2 illustrates, the exposure data and work zone indicator or stratification data include multiple categories. Exposure data categories include:

• Counts or distances traveled through work zones by travelers or vehicles;
• Project, phase, activity durations (such as hours of work activity), or worker-hours in the field; and
• Number of phases or activities that occur.

Meanwhile, indicator or stratification data categories include:

• General roadway design characteristics (type of road, normal number of travel lanes, shoulder presence and size, speed limit, etc.) before the project began, and design characteristics of interest within the work zone (lane and shoulder widths, long-term lane closures, design characteristics of crossovers and lane shifts, etc.);
• Locations and times of work activities of interest (temporary lane closures, full road closures, etc.) and dates of major phase changes; and
• Time and characteristics of events of interest (weather events, major incidents, special events, etc.).

The event data can be used to eliminate data with external influences (such as crashes occurring after a major incident created significant backups in the work zone), or may be used to further examine impacts that occurred during those events (such as how crashes in the work zone were affected when adverse weather conditions were present).

1.3 Where Can Practitioners Obtain Data?

Methods for Obtaining Data Extract from existing sources Collect using electronic or manual methods Interpolate or estimate from existing or collected data sources

There are several ways practitioners may obtain data for use in work zone performance measurement. One method for accessing data is to extract it from existing sources. For example, when evaluating queue lengths in work zones, practitioners may use data from existing Traffic Operations Center (TOC) spot speed traffic sensors. Another method is to specifically collect the data of interest through a variety of methods. In the case of queue lengths, this may entail manual on-site observations by field personnel, closed-circuit TV operated by TOC staff, or via temporary video cameras. Lastly, data may be interpolated or estimated from existing or collected data sources. For example, a practitioner may decide to estimate traveler delays from manually-recorded queue length data, using basic macroscopic traffic flow relationships (an illustration of how to do this can be found in the chapter on mobility data and performance measures).

The potential sources of performance data are described in detail in later chapters of this document. For exposure and indicator or stratification data (which are used to compute many of the specific performance measures presented later in this document), it typically requires digging into project-specific files and databases, culling the desired data from them (usually by hand), and then collating and correlating these data with the performance data. Table 1-3 presents the various exposure and indicator/stratification data categories listed in Table 1-2, and identifies the common source or sources where that data may be obtained. Vehicle and person-based exposure data can come from the same sources as throughput data (one of the mobility-related performance measure categories) and is discussed in more detail in chapter 3. For the other data categories, project-related files are the main source of information available. Presently, details about the status of each work zone on a day-by-day basis are commonly limited to whatever is captured in the daily diaries kept for each project. A few agencies transfer these diary entries into their overall construction management database, but still as a narrative summary of activities. Project engineers or inspectors are those most commonly assigned to this task, as are maintenance supervisors for crews performing various minor maintenance tasks with agency forces.

Table 1-3. Sources of Exposure and Indicator/Stratification Data

Exposure and Indicator/StratificationData Categories	Potential Data Sources
Traveler/vehicle counts and travel distances	See discussion on work zone throughput in the mobility-related performance measures chapter (starting on page 3-1)
Durations of specific work tasks or conditions	Project daily diary notes Electronic construction management database Agency maintenance activity records Lane closure notification/approval database
Work zone activities/conditions	Project daily diary notes Electronic construction management database Project plans (for maintenance-of-traffic conditions in each phase, temporary geometrics) Agency maintenance activity records Lane closure notification/approval database
Roadway classification/conditions	Roadway inventory file or database
Events (incidents, special events, weather, etc.)	Transportation operations center (TOC) operator incident logs Project daily diary notes Electronic construction management database entries National Climatic Data Center (www.ncdc.noaa.gov)

Traditionally, there can be considerable variation in both the quality and quantity of information pertaining to work activities documented in the project diary or project correspondence files, depending on who does the documentation. As agencies and contractors become more involved in work zone performance measurement, emphasis on documentation of details that are of most interest will likely be required. Long-term lane and shoulder reductions will typically be documented in the maintenance-of-traffic (MOT) sheets of a set of project plans, but the actual dates that the reductions begin and end will not. Similarly, any changes in the MOT plan itself will need to be captured (both when and what) in the diary narrative. For short-term or short-duration lane or shoulder closures, documentation of the time, location, and extent of closures (how many lanes are closed or kept open) will often only be found in project diary information. A few agencies may have procedures in place to receive notification of these temporary lane closures (or perhaps to even approve them). In regions with TOCs, lane closure notifications to the TOC may also be an information source. For these agencies, this database can be a potential source of the desired exposure and indicator/stratification data, although the prevalence of “phantom” lane closures (those that have been requested and approved but which do not end up actually occurring) should be assessed before relying on this database for this purpose.

Document Objectives Provide practitioners with the skills to: Identify current data sources for work zone performance measurements Identify potential data sources for work zone performance measurement that may be available in the near future Select and compute useful work zone performance measures, given the data sources that are available

Agencies will usually have a fairly good database of roadway conditions that exist normally on the facilities under its jurisdiction. These data can be easily accessed to establish baseline conditions regarding geometrics, access, etc. for comparison against conditions implemented through and around the work zone. For specific events that may compound with the effects of the work zone, common data sources include incident logs (for work zones located within the coverage of a transportation management center), unusual events documented in the project diary, and historical weather data from the National Climatic Data Center.

1.4 Guidance Document Objectives

The purpose of this guidance document is to provide practitioners with the skills to identify current data sources (both existing data and data collected specifically for the work zone) for use in work zone performance measurement, as well as potential data sources that could be useful to work zone performance measurement in the near future. This document is also intended to assist practitioners in determining how to select and compute useful work zone performance measures, given the data sources available to them.

For both current and potential data sources, guidance is presented on the viability of each source for work zone performance measurement, as well as on possibly leveraging opportunities to maximize the value of data collection and extraction efforts. This leveraging can occur by identifying multiple ways in which a particular data source can be used for performance measures and for other purposes, such as for operating a work zone intelligent transportation system (ITS) for traveler information that can also provide data for work zone performance measures. Leveraging can also occur when certain data are used for multiple work zone performance measures. For example, an agency may choose to monitor work zone queues because of both work zone mobility and safety performance concerns.

Work Zone Performance Measure Guidance Provided Priorities identified by an expert practitioner panel Basic computations required Appropriate audience(s) for the measures Impact of different data sources on measures that are computed

In addition to information about data sources and opportunities, guidance is provided regarding work zone performance measures that the various data sources can support. The measures have been prioritized by an expert practitioners panel using an on-line Delphi surveying technique (details on how the measures were prioritized is included in Appendix A).  Information is provided regarding the basic computations needed for each measure, its overall level of importance (as rated by the panel), and the audiences for which the measure would be most applicable. A discussion of how specific measures compare when computed using different data sources is also provided. Where appropriate, examples are provided as to how data assessment, collection, application, and interpretation can be accomplished. In this way, document users can obtain an overall perspective.

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