Transportation Cost Index:
A Comprehensive Performance
Measure for Transportation and Land
Use Systems
Liming Wang, Portland State University
In Collaboration with
Jenny Liu, Huajie Yang, Shi Wei (PSU)
Bud Reiff (Metro), Brian Gregor (Oregon System Analytics)
Outline
● Why yet another performance
measure (YAPM)?
● Transportation cost index: the idea
● Implementations and application
● Ongoing and future work
Demand for
Comprehensive Measures
● As a supplement/replacement of
traffic-centric measures: LOS, travel
delay
● MAP-21 emphasizes use of
performance measures in
transportation planning & operation
● State legislations: Oregon Job and
Transportation Act (OJTA)
Existing Measures
● Handy and Niemeier, 1997
● Geurs and van Wee, 2004
● NCHRP Report 311, 618, 694, 708 ...
Market Potential Measures
Employment accessible within
30 minutes by public transit
during a.m. peak
• Easy to interpret/understand
• Opportunities, mode, time-ofday and time budget specific
Source: University of Minnesota, Accessibility
Observatory
Utility-based Measures
E(CS) = ln
𝑚′
exp 𝑈𝑚′ 𝑘𝑗
+𝐶
Logsum as an accessibility
measure
• Elegant, composite measures
for all modes; possible to
derive net user benefit
between scenarios
• Hard to interpret by itself;
unable to compare across
regions/times
Generalized Costs
Indicator
per distance generalized
costs for motorized trips
• Easy to
interpret/understand;
able to monitor trends
and compare
scenarios
• ignores land use
system; mode, timeof-day specific
Source: Koopmans, et al, 2013
H+T® Affordability Index
•
•
Tracks out-of-pocket
monetary costs of
transportation and
adds them to housing
costs as a location
efficiency measure;
Does not track the
performance of
transportation system
except for Auto/Transit
uses.
Source: Center for Neighborhood
Technology (CNT)
Wish List for YAPM
● A comprehensive indicator able to present an
overall picture;
● Easy to interpret/understand;
● Applicable to both trend monitoring and
scenario comparison;
● Able to fill gaps in policy areas not adequately
covered by existing performance measures,
e.g. the equity and compatibility aspects (Reiff
and Gregor, 2005)
Consumer Price Index (CPI)
Measures changes in the price level of a
basket of consumer goods and services
purchased by households:
● Build a basket of goods and services from
pre-defined item groups
● Track the prices of goods and services in the
basket
Transportation Cost Index
(TCI)
● Comprehensive measure of transportation
and land use systems;
● Easy to interpret/understand;
● Based on widely available data sources,
possible for use in trend monitoring and
comparing scenario outcomes;
● Able to serve as an indicator for policy
areas including transportation and land
use system compatibility and balance.
Transportation Cost Index
(TCI)
Measures changes in the price level of
a market basket of trips/destinations
meeting households’ daily needs:
● Identify a basket of trips/destinations
based on pre-defined groups (trip
purpose categories);
● Track the costs of accessing
destinations/trips in the basket.
Implementation A: Travel
Survey-based Method
Relies primarily on input from household activity
survey, e.g. Oregon Travel & Activity Survey
(OTAS)
• Construct travel baskets based on activity
diaries or a sample of trips/tours that are
representative of regional travel pattern,
potentially by trip purpose, household size,
income group and geography;
• Track the time and monetary costs of making
these trips/tours;
• Easy for trend monitoring.
Implementation B: TDMbased Method
Relies on inputs from travel demand model
− Data readily available for regions w/ TDM;
− Straightforward for scenario comparison;
− Theoretically can calculate the transportation
cost for every income group and for every
TAZ.
− But we may not want to track it too closely –
patterns from idiosyncrasy or true
differences?
Implementation B: TDM-based
Method
Calculate Travel Costs:
Cost Estimate by Mode
𝐶 = 𝐶0 + 𝑘 ∙ 𝑇𝐷 + 𝑤 ∙ 𝑇𝑇
𝐶0 - Constant
𝑘 ∙ 𝑇𝐷 - Monetary costs (Fuel and tire costs,
Ownership costs, insurance, etc) of travel
𝑤 ∙ 𝑇𝑇 - Time costs of travel
Applications and Demonstration
Generalized Costs by Household Income
Level (Portland, 2011)
Low income
Mid income
High income
Generalized Costs by Household Size
(Portland, 2011)
1
2
3
4+
Generalized Costs by Purpose & Income
Level (Portland, 2011)
Generalized Costs
by Purpose,
Income Level and
Transportation
Districts
(Portland, 2011)
Generalized Costs by Household
Income Level (Portland)
2011
1994
Generalized Costs by Household
Size (Portland)
2011
1994
Generalized Costs by Purpose
and Income Level (Portland)
2011
1994
Generalized Costs Portland vs
Salt Lake City
Df
msa
1
Res 11414
Sum Sq Mean Sq
75870
75870
191411731 16770
F value Pr(>F)
4.524
0.0334 *
Portland – Salt Lake City
Mean difference: 5.37
95% Confidence interval: [0.42, 10.32]
Generalized Costs by Household
Income Level
Portland
Salt Lake City
Generalized Costs by Purpose
and Income Level
Portland
Salt Lake City
Using NHTS Data (2009)
summary(n.tcost.hh.msas.aov)
Df Sum Sq Mean Sq F value Pr(>F)
msa
2 129454 64727 7.566 0.000539 ***
Residuals 1435 12275919
8555
diff lwr upr p adj
Tampa Bay-Portland
-21.63 -43.30 0.04 0.05
Salt Lake City-Portland 12.59 -19.02 44.21 0.62
Salt Lake City-Tampa 34.23 9.63 58.83 0.003
Using NHTS Data (2009)
By household income group:
By household size:
Ongoing and Future Work
● Under development/testing at
http://github.com/cities-lab/tci
● Reconcile TCIs from the two methods;
● Verify patterns of transportation costs with
information from alternative data sources,
such as CES;
● Should external costs be included?
Ongoing and Future Work
● Adopted by the Accessibility Indicator
Development Team (IDT) as one of
indicators for the Oregon Mosaic project
mandated by OJTA
● Test TCI usage in public engagement and
policy making process
Acknowledgements
National Institute for Transportation
and Communities
Oregon DOT
Extra Slides
Income Levels
To be consistent with the classification used in
Metro’s TDM, household income levels are
classified with this scale (1994 dollars):
• < $25K: Low Income
• $25-50K: Mid Income
• > $50K: High Income
Identify Activity Centers (Travel Market
Basket)
Steps (Giulinao, 1991)
1. Calculate employment/size term density;
2. Identify TAZs with densities greater than
density cutoff D and group contiguous TAZs
identified into preliminary centers;
3. Calculate total employment or size terms for
each center identified in step 2 and eliminate
centers with total employment or size terms
below total cutoff E from centers identified in
step 2. The remaining are activity centers.
Determine Cutoffs
• Giulinao (1991) provides no guidance in
selecting density cutoff (D) or total cutoff (E).
They relied on expert knowledge
• Sensitivity Tests to determine cutoffs
Sensitivity Tests: HBW
Sensitivity Tests: HBS
Sensitivity Tests: HBS
Sensitivity Tests: HBO
Travel Costs Calculation:
Cost Estimate by Mode
• Auto
𝐶𝑎𝑢𝑡𝑜 = 𝐶𝑎𝑢𝑡𝑜0 + 𝑘𝑎𝑢𝑡𝑜 ∙ 𝑇𝐷𝑎𝑢𝑡𝑜 + 𝑤𝑎𝑢𝑡𝑜 ∙ 𝑇𝑇𝑎𝑢𝑡𝑜
– 𝐶𝑚0 - Constant
– 𝑘𝑎𝑢𝑡𝑜 ∙ 𝑇𝐷𝑎𝑢𝑡𝑜 - Monetary costs (Fuel and tire
costs, Ownership costs, insurance, etc) of driving
– 𝑤𝑎𝑢𝑡𝑜 ∙ 𝑇𝑇𝑎𝑢𝑡𝑜 - Time costs of driving
Travel Costs Calculation:
Cost Estimate by Mode
• Public Transit:
𝐶𝑝𝑢𝑏𝑙𝑖𝑐 = fare + 𝑤𝑝𝑢𝑏𝑙𝑖𝑐 ∙ 𝑇𝑇𝑝𝑢𝑏𝑙𝑖𝑐
– Fare: Transit fares
– 𝑤𝑚 ∙ 𝑇𝑇𝑝𝑢𝑏𝑙𝑖𝑐 : Time costs of riding transit
• Non-motorized modes (bicycling and walking)
𝐶𝑏𝑖𝑐𝑦𝑐𝑙𝑒 = 𝐶𝑏𝑖𝑐𝑦𝑐𝑙𝑒0 + 𝑤𝑏𝑖𝑐𝑦𝑐𝑙𝑒 ∙ 𝑇𝑇𝑏𝑖𝑐𝑦𝑐𝑙𝑒
𝐶𝑤𝑎𝑙𝑘 = 𝑤𝑤𝑎𝑙𝑘 ∙ 𝑇𝑇𝑤𝑎𝑙𝑘
– Time costs of Bicycling and Walking