Measuring System Performance: The Key to Establishing Operations

**as a Core Agency Mission**

**by**

**Michael D. Meyer, Ph.D., P.E.**

**Georgia Institute of Technology**

# Introduction

The performance of the transportation system affects our lives on a
daily basis. This effect is perhaps most noticeable to the estimated 132
million Americans who daily commute to and from work. Whether by car,
bus, rail, or some other form of transportation, every commuter's day
begins with some experience of how well his or her community's
transportation system worked. Those making trips for other than work
purposes during the day also experience the challenges that often face
those "in a hurry to get somewhere." And importantly, even for those who
do not travel on a particular day, all of the food and goods found in a
typical household at one time moved on the transportation system. Having
a transportation system that reaches throughout a community has thus
become an important precursor to economic and community success in the
21^st^ century. However, having a transportation system that not only
reaches throughout a community, but also one that performs well 24 hours
a day, seven days a week (e.g., with reasonable travel times and safe
traveling) has become an even more important ingredient to this success.

System management and operations (M&O) focuses on transportation system
performance. What can be done in the short term to improve the flow of
people and goods through the transportation system? What can be done
over the longer term to put in place management and operations
strategies that will provide the best possible performance of the
transportation system? These strategies might include not only expansion
of existing facilities, but perhaps better surveillance, monitoring, and
reaction to traffic accidents; better coordination of traffic signals;
improved cooperation among the many different agencies responsible for
system operations; and enhanced information to the users of
transportation so they can make better decisions on trip-making. The
challenge to the transportation professional community, however, is that
these types of actions are often not seriously considered as part of a
metropolitan area's or state's transportation vision or strategy for the
future. With an historical focus on expending investment dollars on the
construction of transportation "projects," many local decision makers do
not consider M&O strategies as having an important part of a regional
strategy for enhancing transportation system performance. This emphasis
on project construction is found historically in legislation, policy,
and program development at the national and state government levels
(which, given the importance of federal and state funding programs for
influencing local transportation priorities, could also explain why this
emphasis is found at the local level).

One of the ways of increasing the importance of M&O strategies aimed at
enhancing transportation performance is to collect data on system
performance. By monitoring key performance measures that reflect what is
of greatest concern to the users of the transportation system, state and
local officials can link this understanding with the types of strategies
and actions that best improve this performance. In addition, by
providing meaningful system performance information at the national
level, system management and operations could become an important
element of a federal program for improving the nation's transportation
system.

The purpose of this paper is to identify the role that performance
measures could play in making system management and operations a more
important part of national, state and local strategies for improving the
transportation system. Inherent in the use of performance measures is
the importance of a customer perspective in planning and decision
making. This in turn necessarily entails knowing what the customer wants
from the transportation system. This paper discusses the results of
research and consumer surveys of the American public that illustrate
what the consumers of transportation services consider to be important
service characteristics.

The primary source of background information for this paper is the
proceedings of the *Conference on Performance Measures to Improve
Transportation Systems and Agency Operations* organized by the
Transportation Research Board in Irvine, California on October
29-November 1, 2000 \[TRB, 2000\]. However, given the author's
familiarity with the subject, other sources are also used in support of
the paper's observations and conclusions.

# Question: Why Measure? Answer: Because It Is Important

Performance measures are indicators of system performance that are
related to the important issues or concerns of those making investment
decisions. The transportation literature discusses a wide range of
applications for performance measures. In some cases, such measures are
used as a means of providing accountability to elected officials on what
has happened with the funds they have provided. In other cases,
performance measures are (mis)used as evaluation criteria for the
selection of projects or strategies in a planning study. And in still
others, performance measures are used as internal organizational metrics
to monitor progress toward "success", e.g., number of projects reaching
the construction phase. Based on numerous case studies of
performance-based planning in the U.S., Pickrell and Neumann \[2000\]
summarized the major reasons for adopting performance measures as:

> **Accountability**: Performance measurement provides a means of
> determining whether resources are being allocated to the priority
> needs that have been identified, through reporting on performance and
> results to external or higher-level entities.
>
> **Efficiency**: Performance measurement focuses actions and resources
> on organizational outputs and the process of delivery; in essence, in
> this context, performance measurement becomes an internal management
> process.
>
> **Effectiveness**: Related primarily to planning and goals
> achievement, performance measurement in this case provides a linkage
> between ultimate outcomes of policy decisions and the more immediate
> actions of transportation agencies.
>
> **Communications**: Performance measurement provides better
> information to customers and stakeholders on the progress being made
> toward desired goals and objectives.
>
> **Clarity**: By focusing on the desired ultimate outcomes of
> decisions, performance measures can lend clarity to the purpose of an
> agency's actions and expenditures.

**Improvement over time**: Performance measurement allows periodic
refinement of programs and service delivery given more intermediate
results of system monitoring.

Kasoff \[2000\] noted that the characteristics that typically govern how
performance measures are introduced range from:

-   [Strategic policy initiatives]{.underline} (e.g., smart growth, and
    the measurement of changing accessibility to critically important
    areas or groups) to [efficiency initiatives]{.underline} (e.g.,
    operational measures such as maximizing the number of transit
    revenue passengers per seat-mile of transit service)

-   [External]{.underline} (e.g. responding to outside mandates from
    governors, legislatures, commissions) to [internal]{.underline}
    (e.g. responding to management initiatives from within)

-   [Comprehensive]{.underline} (broad base and systematic processes
    cutting across entire agency) to [selective]{.underline} (focused
    processes targeted to certain key areas)

-   [Top down]{.underline} (e.g., driving down into the organization by
    front office leadership) to [bottom up]{.underline} (e.g.,
    percolated up into the organization from front line staff or first
    line managers)

-   [Voluntary]{.underline} (e.g., participation invited for those who
    are willing and motivated) to [mandatory]{.underline} (e.g.,
    participation required to achieve cross-cutting consistency and
    completeness)."

***In almost all cases, the main reason for using performance measures
was that it reflected some aspect of system performance that was
important to decision makers***. Can this rationale be the basis for
enhancing the importance of M&O strategies in funding programs and in
transportation programs? There is evidence to suggest that the answer to
this question is "yes." For example, although no study has shown a
direct linkage between the collection of pavement and bridge condition
data by state transportation agencies and the corresponding eligibility
of, and increases in federal funding for, such actions, it seems highly
likely that the greater knowledge of the deteriorating condition of the
nation's highways led to federal funding initiatives in these areas. In
the case of bridge condition data, it took a fatal bridge collapse for
Congress to require that periodic bridge condition data be collected by
the states.

In at least two major metropolitan areas, data on system performance has
been used by the metropolitan planning organizations (MPOs) to increase
the visibility and funding of M&O strategies. At a recent Association of
Metropolitan Planning Organizations (AMPO) conference, Michael Morris,
director of transportation planning for the North Central Council of
Governments in Dallas-Ft. Worth stated that there were two key
ingredients to their success in implementing M&O strategies.\[Morris,
2001\] The first was collecting data on system performance that are used
in an annual performance report to MPO board officials. With this data,
the MPO staff was able to show that over the past several years a 10
percent increase in population in the metropolitan area resulted in a 57
percent increase in the number of road segments operating at level of
service F, the highest level of congestion. The data illustrated not
only a congested transportation system, but also one that was very
unreliable. The second ingredient to success was being honest to local
officials about the significant constraints facing the region in dealing
with this problem. Air quality mandates, safety concerns, system
unreliability, and a lack of funds all suggest to local officials that
M&O strategies have an important place in the regional transportation
vision.

Similarly, Steve Heminger, Executive Director of the Metropolitan
Transportation Commission in the Bay Area , stated that the MPO has been
collecting system performance data for many years, including input from
the public. He stated that "there is a clear sense of urgency" in the
Bay Area on dealing with congestion, and that this is mostly manifested
in public comments as poor signal coordination, inadequate transit
connections, and poor use of transit and ridesharing options. Because of
the decision maker and public emphasis on system performance,
approximately 60 percent of the MPO staff budget is allocated to M&O
activities, and for the first time in MTC's history, a Deputy Director
for Operations now reports to the Executive Director.

The examples above, the cases discussed at the TRB conference on
performance measures, and the continuing development of performance
measurement in the profession suggest that the reasons for creating and
using a system performance measurement scheme varies widely throughout
the U.S. However, it is interesting to observe that ***those measures of
most importance to the traveling public tend to be the ones at the core
of system performance measurement. And these measures focus on system
management and operations.***

***The Implications of a Customer Orientation on Performance Measurement
and Operations: What to Measure?***

One of the key characteristics of transportation policy, management and
planning over the past decade has been an increasing focus on "serving
the customer." This customer-orientation has spawned numerous studies,
reports, and books on how this can best be done in an industry like
transportation. The implications of such a customer focus on system
performance measurement are significant. As noted by several
participants at the TRB conference on performance measures:

> "Where appropriate, the selected performance measures should reflect
> the customer or system user point of view. This requires an agency to
> think about who their customers are (often there are multiple customer
> groups or "market segments"), what the customer actually sees of the
> department's activities and results, and to define measures that
> describe that view." \[Pickrell and Neumann, p.20\]
>
> "...goals, objectives, and measures have to resonate with society. We
> had that benefit because we had all aspects of society working with us
> on our plan..." \[Poorman, p.35\]
>
> "We have done a lot of customer research in establishing performance
> measures...customer research can help prioritize and shift resources
> to products and services that the customer currently believes should
> have higher value...but it has limits in that it cannot replace
> vision."\[Ekern, p.37\]
>
> "Most end-user customers cannot be expected to exhibit great interest
> in the process of implementing performance measures. On the other
> hand, if it is clear that what is being measured is of direct concern
> to them as users, and that it will provide the basis for some action
> that will improve services upon which they depend, then they can be
> expected to show some interest." \[Kasoff, p. 55\]
>
> "From a transit perspective, the customer input is an important part,
> even to the extent of seeing customers as stakeholders in the
> performance measure process in terms of what and how to measure, and
> even perhaps with what to do with the results." \[Stuart, p. 73\]
>
> "Customer measures are an important component in an organization's
> family of measures...."\[Dalton, et al, p. 87\]
>
> "Customers will give direction, but are less interested in details of
> measurement. When you involve people from the freight community,
> shippers and carriers, it's going to probably be difficult to find
> anyone who is going to work at a real detailed level, but if you
> combine your staff effort and help them provide some of the direction
> and concepts, you can make progress."\[Larson, p. 193\]

The customer orientation of performance measurement leads to the
questions of who are the customers and what are their expectations? In
addition, if we accept as a point of departure the definition of
successful system management established by the Transportation
Operations Dialogue, that is, providing system performance that meets or
exceeds customer expectations, then the same questions are even more
relevant. I will not spend much time discussing who are the customers.
The TRB conference proceedings present lengthy discussion on this issue.
The bottom line seems to be....it all depends! Customers have been
defined as legislators, stakeholders, other agencies, the governor's
office, elected officials, and the users of the transportation system.
For purposes of defining a systems management perspective that is based
on operations strategies for improvement, customers are defined very
simply as the users of the transportation system. What then do system
users want from the transportation system?

For many years, studies have shown that individual travelers
consistently value the same things in terms of trip-making. The results
of many of these studies have been used to determine the most
appropriate causal variables to place in demand models. More recent
efforts have collected similar data to identify customer satisfaction
with transportation system performance that can be used in
prioritization schemes, for public relations, and in monitoring
performance measures. A recent paper presented at the annual meeting of
the Transportation Research Board found the following trip
characteristics to be most important to system users.\[Hall, Wakefield,
and Al-Kaisy, 2001\]:

1.  Travel time: The quality of the trip on the freeway was most
    importantly related to the traveler perception of how long it takes
    to get to his/her destination; travel time was considered to be
    "lost" time to the travelers.

2.  Traffic density or maneuverability: The distance between cars in
    front and back was of greater concern to drivers than being able to
    change lanes.

3.  Safety: The risk to personal safety was considered the most
    important issue in this category.

4.  Value of travel information: Uncertainty on what is causing
    slowdowns and knowing available options were pointed to as the
    reasons for the value attached to this factor.

Another study used a survey of 2,500 residents in a highway corridor in
Southern California to determine the values of travel time and of travel
time reliability in congested conditions. Table 1 shows the results of
this survey. The standard deviation of travel time was used to measure
reliability. For the average length of trip and for median household
income, the value of \$12.60 per hour of standard deviation was
estimated for travel time variability, as compared to a value of travel
time of \$5.30 per hour for normal travel time. This indicates that
travelers place a much greater value on travel time reliability \[Small
et al., 1999\]. A similar result was found in a study of value of time
associated with travel time variability due to freeway incidents \[Cohen
and Southworth, 1999\]. At a more abstract level, a recent
FHWA-sponsored survey of the U.S. public showed that poor traffic flow
was the characteristic of travel on major highways that received the
largest percentage of dissatisfied customers (see Figure 1).

######## Table1: Value of travel time and reliability of travel time

+-----------------------------------+-----------------------------------+
| **Household income (000s)**       | **Value of travel time            |
|                                   | (\$/hour)**                       |
+-----------------------------------+-----------------------------------+
| 15                                | \$2.64                            |
|                                   |                                   |
| 35                                | 3.99                              |
|                                   |                                   |
| 75                                | 5.34                              |
|                                   |                                   |
| 95                                | 6.70                              |
|                                   |                                   |
| \>95                              | 8.05                              |
+-----------------------------------+-----------------------------------+
| **Trip type and income**          | **Value of reliability (\$ per    |
|                                   | minute of standard deviation)**   |
+-----------------------------------+-----------------------------------+
| Work trip, higher income          | \$0.26                            |
|                                   |                                   |
| Work trip, lower income           | 0.22                              |
|                                   |                                   |
| Non-work trip, higher income      | 0.21                              |
|                                   |                                   |
| Non-work trip, lower income       | 0.17                              |
+-----------------------------------+-----------------------------------+

Source: \[Small et al., 1999\]

![](media/image1.png){width="6.914583333333334in"
height="3.370138888888889in"}

Freight shippers and carriers are another important customer of the
transportation system. Perhaps the best example of what this sector
views as desirable characteristics of transportation system performance
comes from Minnesota. The state DOT established a freight advisory
committee with an objective of developing freight-oriented performance
measures \[Larson, 2000\]. The task force focused on the basic concepts
that were important to the freight sector for the Twin Cities'
transportation system, and state DOT staff defined corresponding
performance measures. Table 2 shows the types of performance measures
proposed by the DOT. Of interest in this set of measures is the
comparative nature of system performance in the Twin Cities to other
metropolitan areas (economic competitiveness) and the travel time
specified by specific origin-destination pairs.

#  It seems clear from the examples above and the many years of research that has focused on better understanding travel behavior that certain "system operations" characteristics of tripmaking are considered to be most important to system users. These characteristics can serve as the basis for both monitoring transportation system performance (i.e., defined as performance measures) in a manner that is directly relevant to the customer, while at the same time being linked closely to evaluation/prioritization criteria that influence the selection of future system investment strategies. Some of these performance measures, which are already in use in many jurisdictions in the U.S., can be applied at different levels of system definition such that they could provide input into decisions at the national, state, and local levels. It seems likely that any national effort to collect such data systematically would in fact utilize the data collected by state or local jurisdictions. An important characteristic of this set of performance measures is that some of the measures are focused on the mobility of people and goods (as perceived by individuals) while others focus on system operations.

### Table 2: Freight-Oriented Performance Measures From Minnesota

+---------------------+------------------------------------------------+
| **Performance       | **Performance Measures**                       |
| Concept**           |                                                |
+---------------------+------------------------------------------------+
| Predictable,        | -   Metro freeway travel time by route and     |
| competitive Twin    |     time of day                                |
| Cities' travel time |                                                |
|                     | -   Ave. speed on metro freeways by route and  |
|                     |     time of day                                |
|                     |                                                |
|                     | -   Congestion ranking of metro freeways, by   |
|                     |     route                                      |
|                     |                                                |
|                     | -   Congestion level compared to other major   |
|                     |     metro areas                                |
+---------------------+------------------------------------------------+
| Economic            | -   Benefit/cost ratio of major state          |
| benefit/cost        |     transportation projects                    |
+---------------------+------------------------------------------------+
| Transportation      | -   State's transportation investment and      |
| investment          |     spending as % of gross state product       |
+---------------------+------------------------------------------------+
| Intercity travel    | -   Peak hour ave. travel speeds on major      |
| time                |     routes between 27 state regional centers   |
|                     |                                                |
|                     | -   Shipper point-to-point travel time         |
+---------------------+------------------------------------------------+
| Freight travel time | -   Travel time to major regional, national    |
| to global markets   |     and global markets---by rail, air, water,  |
|                     |     and truck                                  |
+---------------------+------------------------------------------------+
| Competitiveness of  | -   Shipment cost per mile---by ton or value,  |
| shipping rates      |     by mode for major commodities              |
+---------------------+------------------------------------------------+
| Crash rate and cost | -   Dollar of crashes and crash cost           |
| comparison          |     comparison by mode                         |
|                     |                                                |
|                     | -   Crash rate per mile traveled by freight    |
|                     |     mode                                       |
+---------------------+------------------------------------------------+
| Bottlenecks and     | -   Number of design impediments to freight    |
| impediments         |     traffic, by mode, by type                  |
+---------------------+------------------------------------------------+
| Timely access to    | -   Number of design impediments slowing       |
| intermodal          |     access to truck, rail, air, and waterways  |
| terminals           |     terminals                                  |
+---------------------+------------------------------------------------+

Source: Larson \[2000\]

In order of (my own) preference, the following performance measures seem
to be most important for system users.

1.  System reliability---change in average travel time for specific
    origin-destination pairs, or some measure of variation in average
    travel time per standard time period such as percent of time that a
    person's travel time is no more than 10 percent higher than average

2.  "Reasonable" travel time (or speed)---for specific
    origin-destination pairs, possibly by route and by time of day; or
    other measures such as average minutes per mile, and average minutes
    of delay

3.  Safety---number of crash incidents, or possibly economic costs of
    crashes

4.  Average delay at top "x" bottleneck points in transportation system
    or average daily hours of travel

5.  Traveler costs (perhaps at the national level measured as the share
    of average household budget used for transportation purposes)

6.  Physical condition of the transportation system

7.  Customer satisfaction measures

With modern intelligent transportation systems (ITS) technology, some of
this information could be conveyed to system users in real time. Figure
2, for example, shows travel time contours in Atlanta as data is
collected from the surveillance cameras on the metropolitan area's
freeway system. Thus, system operations information can be very useful
not only for travelers who are trying to find the best path through the
network, but when archived, this data can pinpoint areas where
improvements are necessary.

Figure 3 shows how performance measures can be incorporated into an
institutional decision making structure that encompasses different types
of decision making \[Meyer, 2000\]. Some performance measures can be
defined for use in a specific context, e.g., maintenance, operations,
construction, planning, etc. Such measures are used to monitor and make
improvements to the program delivery of that particular function.
However, Figure 3 also suggests that there are other performance
measures that transcend different decision making levels. For example,
system reliability and average travel time, which are important issues
at the operations level, also become critical performance considerations
in other levels of decision making. In the example shown, they are
considered throughout the decision making structure, from operations
decisions to

![](media/image2.jpeg){width="5.8in" height="4.35in"}

strategic investment decisions. If the performance measures are
institutionalized throughout the decision making structure, then the
types of M&O strategies considered to improve system performance could
very well surface to the top of the transportation program.

Customer satisfaction measures merit some additional thought. Such
information is most often gathered through surveys. This information is
very useful in gauging the public perceptions on how an agency is doing
its job. However, it seems more problematic in basing investment
decisions on the results of such surveys. It is useful, however, to know
that, as in the FHWA national survey, the public views traffic flow as
the most important element of the dissatisfaction with the quality of
their trip. Such information could very well be used in developing a
constituency for targeted investment programs on system management
improvements.

***Some Examples....***

The TRB conference on performance measures presented several examples
that illustrate the important role for system operations in an overall
system management strategy.

**[Minnesota DOT's Business Planning Performance Targets]{.underline}**:
The Minnesota DOT has been one of the nation's leaders in developing
performance measures targeted at the "business" of the agency. In the
mid-1990s, Minnesota DOT developed the concept of a "family of measures"
that reflected the range of impacts and outcomes that were

![](media/image1.wmf)

influenced by transportation system performance. These outcomes and
example measures included:\[Minnesota DOT, 1998\]

-   *Time-directness*: A predictable travel time for length of trip is
    maintained so that customer expectations are met.

> \--Number of freeway miles congested
>
> \--Average travel time and distance
>
> \--Percentage of Minnesotans satisfied with trip time

-   *Safety*: Incidents and crash rates are minimized to MnDOT's current
    and potential ability to influence infrastructure,
    partnerships/education, full range of solutions and driver behavior.

> \--Motor vehicle crash rates and fatal crashes by roadway design
>
> \--Percentage of Minnesotans feeling safe while driving in work zones
>
> \--Percentage of Minnesotans satisfied with the safety of roadways

-   *Condition of infrastructure*: An infrastructure that meets customer
    expectations is maintained.

> \--Pavement quality index
>
> \--Bridge structural rating
>
> \--Bridge functional rating

-   *Access/basic levels of service*: Services are provided to meet
    personal travel and shipping needs.

> \--Percentage of Minnesotans with satisfactory transit options\\
>
> \--Posted bridges and bridge load carrying capacity
>
> \--Miles of trunk highway spring weight restrictions
>
> \--Percentage of Minnesotans satisfied with travel information

-   *Environment:* MnDOT is a proactive, responsible, environmental
    steward.

> \--Percentage of residential areas in incorporated areas exposed to
> noise that exceeds
>
> standards
>
> \--Number of wetland acres impacted and replaced by MnDOT

-   *Socioeconomics*: Transportation investments will yield the highest
    possible economic return to the region, tempered by an evaluation of
    community values and social impacts.

\--Total vehicle miles traveled and freight ton miles

\--Maintenance and construction expenditures per vehicle mile traveled

\--Percentage of highway funds going to construction

Additional measures have been proposed to be included in this family of
measures, including the state's transportation investment and spending
as a percentage of the state's gross state product and shipment cost per
mile by ton or value, by mode, and for major commodities. Senior
management has adopted target values for many of these system
performance measures that relate to departmental strategic objectives.
For example, a strategic objective that relates to the economic health
of the state is "to ensure that corridors of statewide significance link
the state's regional trade centers" (measured by the miles of major
highways between cities attaining a threshold average speed).

#####  **[Florida DOT's Mobility Measures]{.underline}**: Florida DOT has focused on "mobility" as the key system performance measure for "supporting investment decisions and policy analysis."\[Florida DOT, 2000\] Mobility, defined as the ease to which people and goods move throughout the community, state and world, is measured as the quantity of travel served, the quality of travel, accessibility, and utilization of transportation systems. Some example measures for each include:

Quantity: Person and vehicle miles traveled

Person trips

Transit ridership

Quality: Average speed weighted by person miles traveled

Average delay per vehicle

Average door-to-door travel time

Reliability (variance of average travel time or speed)

Maneuverability (vehicles per hour per lane in peak hour)

Auto/transit travel time ratio

Accessibility: Connectivity to intermodal facilities (percentage within
5 miles)

Dwelling unit proximity

Employment proximity

Industrial warehouse facility proximity

Percentage miles bicycle accommodation in right of way

Percentage miles sidewalk coverage

Transit coverage (percentage of person minutes served)

Transit frequency (buses per hour)

Span of service (hours per day)

Utilization: Percent of system heavily congested (LOS E or F)

Vehicles per lane mile

Percentage travel heavily congested

Duration of congestion (lane-mile-hours at LOS E or F)

Transit load factor (Percentage seats occupied)

Of some interest in this set of measures is the effort to measure
reliability of travel. Reliability was defined as percent of travel on a
corridor that takes no longer than the expected travel time, plus some
measure of acceptable additional time. Loop sensors used as part of the
state's ITS program were used to collect the data necessary for this
performance measure.

**[California's Statewide Transportation System Performance
Measures:]{.underline}** Perhaps one of the best examples of a statewide
system performance measurement effort is found in California where
"there is no more potent issue driving better system management than the
need for performance."\[Wolf\] As noted by Wolf, the purpose of
performance measurement in California was defined as:

-   To develop indicators/measures to assess the performance of
    California's multimodal transportation system to support informed
    transportation decisions by public officials, operators, service
    providers, and system users (talk about integration)

-   To establish a coordinated and cooperative process for consistent
    performance measurement throughout California (real integration)

Not only was transportation system performance measurement linked to
informed decision making, but it was designed to provide a better
understanding of the role that the transportation system plays in
society; to focus on outcomes at the systems level (rather than on
projects and processes); to act as a building block toward improved
partnerships with key constituencies; and to better associate
transportation system impacts with non-transportation issues. Figure 4
shows the linkage between desired system performance outcomes that were
identified through a public process, that are estimated by performance
indicators, calculated using outputs from transportation agencies.

The Caltrans Traffic Operation Program developed a strategic plan based
on the concepts of performance-based transportation planning. System
management was the foundation for an integrated approach toward
programmatic decision making within the organization. An
operations-oriented system management strategy has been developed that
provides a framework for coordinating institutional linkages and
partnerships that are necessary for successful systems management.
Figure 5 illustrates this approach. As can be seen in the figure,
monitoring and evaluation serves as the basis for making decisions on
improvements to the transportation system.

Few examples exist in the U.S. where performance measurement has been
used as the foundation of system management decisions and as the
cornerstone of efforts to build institutional relationships and enhance
constituency support. California was certainly one of the first to
incorporate this as a specific goal in its system performance effort.

# 

#  [Albany, New York:]{.underline} The Albany metropolitan area has been one of the leading users of performance measures in transportation planning in the U.S. Beginning in 1992, when the transportation improvement program (TIP) update process was being revised in light of ISTEA, new approaches were adopted for incorporating system performance into planning and decision making. The approach to performance measurement was based on four characteristics of the measures themselves that were incorporated into the New Visions planning process (as reported in \[Cambridge Systematics, 2000\]).

-   Some impacts can be legitimately presented in monetary terms

-   Other impacts can be quantified, but should not be monetarized

-   Other impacts cannot be easily quantified, but should be discussed
    in narrative

fashion ( called distributional effects by MPO planners)

-   All three types of measures are important and should be available
    for the decision making process

![](media/image1.wmf)

![](media/image1.wmf)

# 

A set of core performance measures defined through the *New Visions*
process were grouped into three headings:

##### *Transportation service quality*

##### Access: \--% of person trips within a defined non-auto to auto difference

> \--% of person trips with a travel time advantage for non-drive-alone
>
> modes

\--number or % of major freight movements with modal alternatives

Accessibility: \--travel time between representative locations

\--peak vs non-peak by quickest mode

Congestion: \--hours of excess delay, recurring and non-recurring by
mode

Flexibility: \--reserve capacity on system

\--% of person trips that could be accommodated by modes other than auto

\--number of corridors with reasonable alternatives during closure

# Resource requirements

Safety: \--estimated societal cost of transport and accidents

Energy: \--equivalent BTU/day for transportation capital, maintenance,
operation

> and use

Econ. cost: \--annualized capital, maintenance, operating and user costs

\--value of commercial time in travel

##### *External effects*

##### Air quality: \--daily emission levels

\--air quality attainment status

Land use: \--amount of open space

\--dislocation of existing residences and businesses

\--land use-transportation compatibility index

\--community character index

Environm'tl: \--impacts on sensitive areas

\--noise exposure index

Economic: \--narrative discussion of economic activity supporting or
constraining

> features of transportation system

As indicated in the basic approach outlined by Poorman \[1997\], some of
the measures are quantitative, some are represented by indices, while
still others are simply provided in narrative form.

These case studies, arguably of some of the best practice examples in
the U.S., illustrate the important role that transportation system
operations plays in performance monitoring. Travel time, delay, levels
of congestion, reliability of travel time, accident rates, travel costs,
and customer satisfaction all reflect the degree to which the
transportation system is operating at acceptable levels of performance,
and presumably, at least in the examples above, are important
considerations in the decision making process.

#### Conclusions

This paper has examined the role of performance measures in linking
system management and operations to decision making. By collecting data
on system operations and reporting them to decision makers, the
importance of system performance as compared to other concerns could be
increased significantly. This certainly seems to have been the case in
Dallas-Ft. Worth and the Bay Area where increased funding for M&O
strategies was justified because of the performance "problems"
identified with this data. The several state examples presented above
also have systems operations data as the foundation of performance
monitoring.

This linkage between data collection and resource allocation has
important implications to national policy making. Given a longer term
strategy for increasing the attractiveness of M&O strategies as part of
a transportation investment program, the initial step could very well be
to require periodic collection of system performance data.

Not only could this data be used to identify deficiencies in system
performance, but it could have the dual role of being provided in
real-time to travelers for their use in trip decision making. Based on
research into travel behavior and customer satisfaction, several
categories of performance measures seem most appropriate for a
customer-oriented decision making structure\--system reliability, travel
time (or speed), safety, average delay at top "x" bottleneck points in
transportation system, physical condition of the infrastructure,
traveler costs and customer satisfaction measures. Simply defining such
measures will not assure that the institutional willingness exists to
emphasize system management and operations as solution strategies.
However, they can provide important ammunition for those supporting
these concepts, and given the public interest in improving traffic flow
conditions as seen from surveys, they could act as catalysts for
developing a supportive public constituency.

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