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CHAPTER 8
Using Travel Time Data in Planning
and Decision Making
8.1 Introduction sources of detailed information and practical guidance cover-
ing that topic, including most recently NCHRP Project 3-68,
This section provides guidance on how to utilize travel- A Guide to Effective Freeway Performance Measurement, which
time-based performance information in typical planning ap- covers a wide range of material related to reporting conditions
plications faced by departments of transportation, regional on freeway systems using TMC type data.
planning agencies, transit system operators, and other agen-
cies with similar roles and responsibilities. The selection and
presentation of information in this chapter reflects the find- 8.3 Organization
ing that a very large percentage of reported travel time, delay, The next several subsections provide context for applying
and reliability data is used primarily for reporting on current travel time and related performance data to planning
conditions or historical trends. Many of the published or processes and decisions, drawing examples from the case
web-based sources of travel time data are used to inform the study research. These findings illustrate some of the important
public, stakeholders, and decision makers about how well a technical and institutional steps or approaches that should be
system is currently performing and/or what has been the considered to improve the quality and utility of performance
impact of a particular program of investment. Less evident is data in these applications. In the remainder of the chapter, we
the application of similar types of data to drive typical plan- offer six different example planning applications frequently
ning functions, such as current and projected future needs confronted by planning agencies, and offer step-by-step ap-
(or deficiencies) identification, comparison of alternatives, or proaches for applying the technical methods and approaches
hypothetical before/after (or "what if") studies prior to actual provided in the earlier chapters of this guide.
project selection and implementation. This guidebook is
intended to help fill that gap and provide practitioners with
accessible, effective methods for bringing travel-time-based 8.4 Creating a Performance-Based
data into the decision process for potential future actions, as Decision-Making Environment
well as to identify and evaluate needs by looking at both Performance measures have been used to evaluate both
historical and projected trends. system condition and quality, as well as to track the level of
activity required to build, maintain, and operate a system.
Planners talk of output or activity-based measures that
8.2 Scope and Limitations
quantify the level of effort that goes into the system, such as
This material is primarily suited to support planning deci- incident detection and clearance time, as well as outcome or
sions about investment in system expansion, and to a lesser quality of service measures that describe the resulting effect of
extent, on system operations. It focuses on using travel-time- investment choices (e.g., total annual delay per person). There
related measures of system performance to discern looming is an even longer history of using performance data to track
trends, identify needs, and distinguish between alternative the physical condition of the transportation system, for
courses of actions. It is not intended to provide advice on short- example, in pavement and bridge management.
term system management and detailed operational analyses The literature search, agency interviews, and case studies
based upon archived TMC data, nor on traveler information conducted during the course of this project suggest that use of
systems based on real-time data. There are other excellent travel time and delay data for planning purposes is currently
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limited. Most agencies do not actively use such data or education (tracking test scores), welfare (tracking numbers of
projections in their planning processes. Much more common welfare recipients), environment (particles per million), and
is the use of travel time, delay, and to some extent reliability other disciplines in the public's eye. Congestion mitigation (if
statistics, for reporting current operational conditions and his- not outright reduction) and mobility management are still high
torical trends, and possibly identifying congested corridors for on the list of decision makers' objectives, and even the concept
further analysis. What is still relatively new for most agencies is of travel time reliability has worked its way into the regular di-
the use of the quality of service measures based on measured alog of decision makers and even the general traveling public.
and modeled travel times, used in conjunction with other Of course, the private sector has faced this type of ac-
measures and factors, to help decision makers choose the most countability for decades. Publicly traded for-profit companies
effective course of action. Actual ongoing application of such have to maximize shareholder value by producing financial re-
data to specific needs identification, alternatives analysis, or sults that reflect profitability, revenue growth, positive cash
before and after studies (including the hypothetical before/ flows, and other indicators believed to be central to a company's
after or "what if" analysis comparing synthetic forecasts) is mission and objectives. Even though these companies adopt
much more limited. Yet travel time and delay statistics can be and track other metrics for success (e.g., number of registered
useful in helping analysts, decision makers, and the general patents, effective knowledge management, retaining key staff,
public to understand the potential payoff of different capital minimizing work-related accidents), ultimately they are judged
and operating investments in terms that are most immediately by profitability and growth or, more generally speaking, return
relevant to daily trip-making of system users. on investment.
The same can be said for transportation. One could argue
that even though many performance outcomes should be con-
8.4.1 Using Travel Time and Delay Measures
sidered in evaluating each project or investment (e.g., safety,
Transportation project complexity and costs are continu- environmental quality, social equity, geographic equity, etc.),
ing to grow significantly. The costs for design, materials, travel time and reliability of travel time are the most important
energy, construction, and environmental review and mitiga- and immediate indicators of system performance and mobil-
tion, among other elements, are all escalating at rates higher ity for most customers. People want to be able to get from point
than general inflation or transportation funds. Project costs of A to point B in a reasonable time with reasonable predictabil-
$100 million (and in some case much more) are no longer un- ity. These two attributes should be among the key factors for
usual. Simultaneously, agency planners, decision makers, and any transportation planning process and for any decision-
even the lay public are increasingly aware of the important making process, in most cases. The selected performance
benefits that stem from good system investments, in terms of measures should offer decision makers an understanding of the
improved economic vitality, more efficient movement for differences in travel time and reliability that would result from
personal and commercial purposes, and a resulting overall alternative courses of action. These can be aggregated to the
higher quality of life than would be present without the region or system level, or reported individually for specific
investment. In short, most stakeholders are looking for greater project corridors or segments.
return on investment from transportation expenditures. Our experience in working directly with numerous public
Because travel time and delay affect this broader stream of agencies in performance-based planning and management
benefits, there is a compelling case for including analysis of suggests several important considerations. The case studies
these factors in deciding on future investments. Identifying, and agency interviews conducted for this research project
selecting, and implementing the best performing projects, not support these findings and recommendations as well.
simply the least expensive projects, are increasingly important
as the cost of building, operating, and maintaining a modern
8.4.2 Make Performance Part of Everyone's
transportation system grows, and its importance to the over-
Daily Discussions
all well-being of the community grows as well.
At the same time, members of the traveling public do not Much has already been written about the institutional
always understand why the large amount of ongoing trans- aspects of developing a successful performance-based man-
portation expenditures (which are visually evident to any agement approach. A frequently cited tactic is to raise the
system user, due to ever-present construction and mainte- visibility of performance data and performance monitoring to
nance) do not result in more significant improvements to the the point that every division in the organization is engaged in
quality of their travel experience, regardless of mode. some aspect of performance delivery, knows the relevant met-
Finally, decision makers, elected or appointed officials, face rics and desired targets or objectives, and is comfortable dis-
increasing pressure to deliver quantifiable results. This phe- cussing them. This is much easier said than done. To illustrate
nomenon is not unique to transportation. It encompasses this point, ask yourself: how many people in the organization
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know the average travel time (or total daily delay) in their re- types of measures are considered together, planners and
gion (or state) and the reliability of travel time? How many decision makers may reach the wrong conclusion about the
know what the agency's prediction for the next five years is for benefits of the project.
these two measures? What are the reasons for these predic- Another example relates to the use of delay as a planning
tions, and how are they tracking their progress? This means evaluation measure. In its 2004 Regional Transportation Plan,
that every planning product, every presentation to decision the Southern California Association of Governments (SCAG)
makers, every staff recommendation for investment must be projected future delays and compared them to the base year
performance driven or at least include a discussion on delay. At first, the results of this comparison were disappoint-
performance impacts. Clearly, this takes time and effort. But ing. Despite a variety of potential system investments over 25
as discussed before, performance-based planning and decision years costing more than $100 billion, total delay was projected
making have become an imperative, not a choice. Achieving to increase significantly between the base year and the horizon
the best results from an investment requires an up-front year of 2030.
investment in planning analysis. Yet, SCAG recognized that total system delay does not re-
flect the individual customer's experience, or their expecta-
tions. Rather, delay per trip was deemed a more appropriate
8.4.3 Develop an In-Depth Understanding measure, since it is linked to something the traveler actually
of Trends and Measures experiences and can measure on their own (even if only casu-
For performance data to have an impact on agency deci- ally or subconsciously) (i.e., the excess time required to make
sions, there needs to be wide understanding within the organ- a particular trip due to congestion). In some cases, growth in
ization of the agency actions and external trends that are delay is more meaningful to the traveler than growth in travel
driving performance, the measures that are used to gauge per- time, since travel time may be expected to increase due to land
formance, and the relationship between the two. Again, this use policies, personal location decisions, etc. As shown in
seems easier than it really is. For instance, several agencies we Exhibit 8.2, the two examples lead to different conclusions
have reviewed evaluate measures of mobility (e.g., travel time, about the future system performance and the benefits of the
delay, speed) independently from reliability (e.g., on-time ar- improvement program. As these graphs show, delay per capita
rival, percent variation of travel time, buffer index). Yet, these is projected to stay almost constant despite the increase in de-
two measures are interdependent. If the number of accidents mand. To many transportation professionals, this projection,
are reduced (by implementing safety projects) and/or accident if it holds true, would be a major accomplishment. And to
clearance times are reduced (by investing in incident manage- many system users, it also would seem a reasonable outcome,
ment strategies), planners and decision makers expect an im- if taken from a realistic perspective of population growth and
provement in the reliability measure. Yet, in some instances continued economic prosperity in the region.
that may not happen. Since delays due to accidents are re- The point made here is that adopting and generating per-
duced, the average travel time over a month (or year) also will formance measures are not enough. An organization must
be reduced. This, in turn, changes what on-time arrival means, spend significant time to understand the measure, the results,
what the percent variation means, and what the buffer index and the limitations of the measure before basing decisions on
(as a percent of travel time) refers to. Therefore, it is critical to the measure.
look at the trends of both travel time and reliability together.
The hypothetical example in Exhibit 8.1 illustrates this point.
8.4.4 Invest in Data
Clearly, the after scenario reflects an improvement over the
before scenario, even if it does result in an increase in the Perhaps the seemingly most under-valued investment is
variability as measured by the buffer index. Yet, unless the two the collection and storage of good monitoring data. The
On-Time Arrival
Average Buffer (Within 5 Minutes
Travel Time Index of Average)
Before 22 minutes 30% 65%
After 18 minutes 32% 65%
Exhibit 8.1. Example before-after comparison of different travel
time measures.
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6 14
Daily Person Hours of Delay
13.6
Avg. Daily Delay per Capita (in
12
5 5.2
10
(in millions)
4
millions)
8
7.9 8.0
3 3.0 6
2 2.2 4
1 2
0
0 Base Year 2000 Baseline 2030 Plan 2030
Base Year 2000 Baseline 2030 Plan 2030
Exhibit 8.2. Delay and delay per capita projected for 2030 in the SCAG region.
number of planning studies conducted by state and local such strategies must look for alternative tools, such as mi-
agencies that must rely only on existing, readily available crosimulation tools. Moreover, as more data is available,
data from secondary sources suggests as much. Yet, moni- travel demand models can be improved through better cali-
toring data is used not only to measure what is. It is also used bration. Again, we see this commitment to improving tools
to calibrate the models that eventually project what will be. across the private sector. Financial firms, for instance, have
It is, therefore, important for both decision-makers and abandoned many of the traditional stock and option valua-
planning professionals to embrace the need for more tion models over recent years as new data illustrated serious
frequent and regular data collection, and to view data and flaws in them. Car companies have developed new computer
data systems as assets to be developed and valued. A review tools to help them assess wind resistance and the impact on
of the private sector confirms the importance that should be fuel utilization. The list goes on, but the principle remains: if
placed on data if decisions are to be based on performance. the tools are important for decision-making, improving the
Wal-Mart has implemented systems that let them know what tools must be a priority. Research projects, such as these and
item is sold when, as well as the trends for each item on a many others like it, ultimately provide planners with the nec-
daily and weekly basis. FedEx can tell where a shipment is at essary tools to estimate and apply travel time performance
all times and can project when it will be delivered. And, of data in a broad variety of situations.
course, Internet companies can learn from online transac-
tion and search trends to tailor advertisements for each in-
8.4.6 Understand and Embrace
dividual. Without good data, performance measurement
the Difference Between Policy
cannot succeed as a basis for planning and decision making.
and Technical Analysis
Fortunately, developments in data collection equipment
strongly suggest that automated detection systems are We have all witnessed the frustration of technical staff
becoming more affordable and easier to install. Such systems when decision makers do not allocate the suggested invest-
are especially important to evaluate trends in travel time and ment to their area (e.g., pavement rehabilitation, highway
reliability. Moreover, over the longer term, they are likely expansion, operational strategies). This frustration is under-
to prove more cost effective than manual data collection standable and perhaps even needed. After all, each program
efforts. area needs advocacy. However, agency technical staff also
must recognize that their primary job is to adequately inform
decision makers of the performance ramifications of their po-
8.4.5 Understand the Limitations of Tools
tential decisions from a technical perspective (e.g., what are
and Continually Improve Them
the cost ramifications in the future of deferring maintenance
With the ever increasing computer power and the contin- in order to address a critical capacity deficiency). This way,
uous advancement of the science of transportation and traf- staff can focus on technical analysis, risk analysis, and per-
fic engineering, it is important for agencies to understand the formance measurement to provide an accurate picture as
limitations of their current tools and, when possible, invest possible to decision makers. Using available tools and meth-
in improving them. For instance, 4-step travel demand ods to generate with and without estimates of volume, speed,
models have limitations in terms of evaluating operational travel time, and physical condition, analysts can generate
strategies (e.g., incident management, auxiliary lanes, ramp measures that help identify the difference between these two
metering). Therefore, agencies that are about to focus on choices.
