This paper was adapted from my master's thesis for presentation at the 2004 Transportation Research Board conference.

1. Selecting Corridors for Bus Rapid Transit Using a Multicriteria Method
Eric Holeman
Chicago Transit Authority
120 N. Racine Avenue
Chicago IL 60607
Tel. (312) 733-7000
Fax (312) 432-7127
Email: ehol@xmission.com

2. Eric Holeman 2
ABSTRACT
Many bus rapid transit (BRT) projects result from the availability of a single vacant corridor, such as an abandoned
rail right of way. Deciding where to implement BRT service in an existing transit network, in the absence of an
obvious corridor, is a more difficult question. Various factors, such as the potential rider density, possible travel
speed, and distance from other rapid transit corridors all weigh into the mix. Often the objectives tend to be mutually
exclusive: a corridor that can provide fast travel times may offer few potential riders, while the corridor that
provides the most riders may be along a traffic-clogged arterial. Where no one corridor is perfect, the best choice is
necessarily a compromise between varied and often conflicting objectives.
Because of the conflicting objectives, a multicriteria method was chosen to address the question of identifying
potential BRT corridors. Four alternatives were compared across a number of different criteria. The concordance
analysis method was chosen because of its usefulness in evaluating alternatives where the differences are both
measurable and scalable. By placing different weights on the various objectives, the concordance analysis method
show method does not result in the selection of one superior alternative, but instead shows how alternatives
compare, given a particular set of priorities. Conversely, by showing how weighted alternatives rank, the method
reveals the priorities involved in the choice of a given alternative. The results point strongly to an alternative that
was eventually chosen by the transit agency for a limited-stop BRT-type service.

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INTRODUCTION
The Federal Transit Administration (FTA) has encouraged bus rapid transit (BRT) as a way to develop new rapid
transit projects at a low up-front cost. A number have of these projects have been undertaken by U.S. transit
agencies. Many of those have typically taken advantage of the availability of a single corridor, such as Pittsburgh’s
use of an old rail right of way, or Seattle’s use of high-occupancy vehicle (HOV) lanes along an Interstate highway
corridor.
Such corridors offer an obvious advantage in their ready availability. However, for an established urban transit
system that wishes to overlay BRT services on an existing network, the question of how to select the corridor to
upgrade becomes important. The goals of a BRT corridor typically involve providing a fast ride for a large number
of passengers, yet often the most densely populated transit corridors are those that provide the slowest bus
movement. Conversely, corridors that offer quick vehicle movement are often found in areas of automobile-oriented
development that aren’t likely to provide the number of riders needed to sustain a BRT service.
This paper shows how a transit agency can identify and select bus rapid transit corridors using a multicriteria
analysis method. The study compares a number of candidate corridors in an area of interest using various criteria
appropriate to the agency’s objectives in implementing a BRT service. Any corridor that is clearly superior to all
others may be identified as such. When no corridor is superior in all criteria, the corridors may be compared using
different criteria weightings reflecting different prioritizations of the importance of the various objectives.
DESCRIPTION OF CORRIDORS
Four corridors were considered for evaluation in the part of Chicago's South Side, between the Dan Ryan
expressway and Lake Michigan. The area of interest of the corridors extends for five miles, between 63rd Street to
the north and 103rd street to the south. Corridors evaluated were limited to those north-south corridors with existing
bus service. The corridors are described below and listed with a summary of their attributes in Table I. A map of the
corridors is provided in Figure 1.
Each of the four corridors presents varying degrees of acceptability for BRT service. Martin Luther King Jr. Drive,
though a broad boulevard for much of its length, narrows to two lanes through much of the area of interest. Cottage
Grove Avenue, a somewhat more commercially oriented corridor than King Drive, provides two traffic lanes in each
direction for most of its length. Stony Island Avenue, a broad auto-oriented thoroughfare, provides barrier-separated
multiple lanes for both north and southbound traffic. Like Cottage Grove, it is commercially oriented; though being
much wider, it has fewer residential buildings and minimal landscaping. Jeffery Boulevard is the narrowest of the
corridors, containing a single lane in each direction for all of its length. Although a narrow corridor like Jeffery is
not typically a candidate for BRT service, its high level of existing bus patronage merits its consideration in this
study.
METHOD
The concordance analysis method, as described by Giuliano (1) allows for the comparison of alternatives with
different, conflicting objectives. In applying the method, criteria are identified, and appropriate measures are
determined for each of the criteria. Data are then collected for each measure of each alternative candidate. The
alternatives can then be ranked according to one or more weightings of the measures. Consistently unattractive
alternatives can be readily identified and discarded, while the more attractive alternatives may then be compared
more directly.
Unlike a traditional cost-benefit approach, the concordance analysis method does not allow for the maximization of
a single outcome. Because of this, it is necessarily somewhat imprecise: several alternatives may emerge as viable,
and the preferred alternative may end up being superior in no one single measure. Yet because the method enables
the comparison of multiple favorable and unfavorable outcomes, the researcher may identify one or more
alternatives that offer an acceptable combination of outcomes. The method is appropriate for the problem of transit
corridor selection because each alternative presents an assortment of costs and benefits that aren’t easily scaled to
dollar values.

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A number of studies have examined the usefulness of concordance analysis in addressing transportation issues.
Giuliano provided a demonstration of the method that compared transportation improvement alternatives.
Hastak and Abu-Mallouh (2) provided an example of using concordance analysis to prioritize transit station
improvement projects. Both studies strongly suggest the usefulness of concordance analysis as a tool to evaluate
transit corridors in situations where no single criterion is paramount—provided sufficient criteria to be optimized
can be measured and scaled.
Applying the Concordance Analysis Method to the problem BRT Corridor Selection
Once the criteria for comparing BRT corridors are identified, they can be evaluated using available measures. It is
assumed that the objectives of a transit operator, in implementing a BRT project include increasing patronage in the
corridor, improving service quality, minimizing operating costs, and avoiding competition with existing routes.
Increased Patronage
For the desired outcome of increased patronage, it is assumed that a high-ridership corridor has some residual
demand that may be served by providing BRT service. The capacity for patronage increase is therefore assumed to
be greatest in corridors that already have high ridership, and the current ridership in the corridor is assumed to be a
useful measurement of that potential.
It is further assumed that customers prefer faster buses and are more likely to patronize a faster service.
Because a service that operates in relatively uncongested conditions is more likely to benefit from BRT conversion
than a service that is operating in crowded streets, the current operating speed of the bus will be used as a measure of
the corridor’s ability to attract increased ridership.
Improved Service Quality/Reduced Operating Cost
The outcome of improved service quality is somewhat harder to define, and not all aspects of it are necessarily
related to the corridors in which the service runs. However, it will be assumed that for purposes of selecting a
corridor that faster is better. For the transit agency, operating costs are directly related to operating speed—faster
buses mean lower costs. The measures of potential service improvement are also applicable to the objective of
minimizing operating cost, and will hereafter be treated as the same criterion. The current operating speed of the
existing bus service in a corridor, already identified as a measure for the potential of increased patronage, will also
serve as a measure of potential for improved service quality and reduced operating cost.
The possibility of improving service further by adding lane restrictions is also considered, with the
assumption that such a service improvement is more possible if there are more lanes available. Therefore, the
number of traffic lanes in the corridor will provide another measures relating to service quality improvement.
Avoiding Competition with Existing Service
The chosen corridor is expected to avoid redundancy with existing rapid transit services. It is assumed that the
likelihood of service cannibalization is related to the distance to a competing service. For the corridors under
consideration, the nearest competing CTA rapid transit service is the parallel Red Line service. Distance from the
Red Line is therefore an appropriate measure of the likelihood of service cannibalization. However, there is also
competing Metra commuter rail service near the corridors, and it is possible that Metra customers may be less likely
to consider a CTA service, as they already enjoy a rapid transit-style service with stops approximately half a mile
apart. The distance to the nearest parallel Metra service, then, may also be considered an appropriate measure of the
possibility of service competition.
DATA AND DATA COLLECTION
Once measures for the criteria were defined, data could be collected. A field survey of the corridors determined the
number of lanes in each direction along the length of each corridor. CTA provided schedules and ridership reports,
and the agency’s map was used to determine the distance to competing services.

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Schedule Data
Schedule data were used to calculate the average current travel speed, providing a measure of the capacity of ability
of buses to quickly move through the corridors. For each bus route along each of the corridors, recent published
CTA schedules were consulted to determine average speed along the corridor during AM rush hours for inbound
service and during PM rush hours for outbound services. While buses do not always travel according to their
schedules, it was assumed that the published schedules provide an approximation of the travel time, if not an exact
measure.
Ridership Data
Current ridership counts provide a measure of the corridor’s support of the current bus service, a measure that is
used as a proxy for potential BRT ridership. CTA’s ridership data provides the number of passenger boardings per
weekday per route. This provides a crude measure of the route patronage; however, it should be noted that the
ridership figures are not available for time of day. Further, only boarding counts for the entire length of each route
could be obtained, though it would have been preferable to isolate boardings that occurred within the area of
interest. The ridership counts for all the services in each corridor were combined, including both local and express
services.
Corridor Data
The width of each corridor was determined by a field survey. Each of the four corridors was traveled along its entire
length, from 63rd Street to 103rd Street. For each half mile (i.e., four numbered streets) the number of lanes in each
direction was noted at the midpoint. Each corridor runs for five miles through the area of interest, so a total of ten
measurements were made. From these ten measurements, the average width of each corridor was computed. Only
one corridor, Jeffery Boulevard, was of uniform width along the entire five miles. Parking lanes and turning lanes
were not included in the lane measurements.
Competitive Service (“Cannibalization”) Data
Data measuring the distance between the proposed alternatives and competing CTA and Metra commuter rail
service were taken from the CTA’s route map. For CTA service, the only competing service is the Red Line rail
service between 63rd and 95th Streets. The nearest Metra service to all corridors is the Metra Electric main branch
service. The distance between the candidate corridor and the potentially competing rail corridor was measured along
the connecting east-west street at the location of the rail station, and averaged out over the length of the competing
corridors.
DATA ANALYSIS
Five measures are available for the analysis, representing the various criteria. The raw data for each of the measures
for the four candidate corridors is shown in Tables I and II. A summary of the associations of measures with criteria
is shown in Table III.
To compare the alternatives across different measures, the measures must be are normalized to values between 0 and
1, as shown in Table IV. A graphic illustration of how the normalized measures of the corridors compare is shown in
Figure 2. Examining the relative values of the measures among the alternatives, no one alternative emerges as truly
superior or inferior to all others, however, the King Drive alternative emerges as inferior in all measures but one: the
separation from the Metra corridor.
Selecting Weightings for Corridor Comparison
To compare the various alternatives, a relative percentage weight is assigned to each measure, with the criteria
weights summing to 100%. For the initial analysis, three weightings are applied. Each of these initial weightings
assumes that one of the outcomes is of primary importance, and that the other two are of equal secondary
importance. For computational simplicity, the total weighting of the measurements of the primary criterion is set at

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60%, and the secondary criteria weightings are set to 20% each. The initial weightings of each measurement under
these scenarios are shown in Table V.
Some assumptions must be made within these basic weightings. As the measurement of current service
speed is considered a measure of both potential ridership increase and improved travel time, it is “double” weighted
in all scenarios, assigned a weight that allows for its significance to both of these criteria. In addition, the criterion of
avoiding conflict with existing corridors has two measures, one relating to competing CTA service and another
relating to competing Metra service. The importance of avoiding conflicting CTA service is arbitrarily assumed to
be three times more important than avoiding conflicting Metra service. A greater assumption is made in the
derivation of the weightings. Ideally, the process of deriving weightings would involve interested stakeholders the
agency and from the community. For the sake of expedience in this study, arbitrary weightings are used.
In the scenario emphasizing ridership improvement, the current ridership is weighted at 30%, for one half
of the needed 60% weighting. Service speed is weighted at 30% toward improving ridership, completing the needed
60% emphasis on that criterion, but it is also weighted another 10%, to account for its importance as half of the
measurement of the criterion of improving travel time. The number of lanes is weighted 10%, as the other half of
this criterion measurement. The 20% weight for avoiding service redundancy is split at 15% for the CTA
measurement and 5% for the Metra measurement, per the 3:1 ratio already assumed. Figure 3 provides a graphic
summary of the weight assignments of this scenario.
Assignment of Weights to Scaled Measures and Ranking of Alternatives
For each scenario, the various weights are then assigned to the scaled measures. The resulting scores are then
summed, and the alternatives can then be ranked according to how they score under that particular weighting
scenario.
Ridership Emphasis Scenario
Using the weights for the increased ridership emphasis scenario yields the results shown in Table VI. The ridership-
emphasis scenario, which places a heavy emphasis on the measures of current ridership and current speed,
unsurprisingly favors the Jeffery and Cottage Grove corridors, each of which score high in both measurements.
Interestingly, although the current ridership measurement for the Stony Island corridor is much lower than that of
King Drive, the heavy weighting on travel time makes the two corridors almost equally preferred under this
scenario.
Travel Time Improvement Emphasis Scenario
Under the travel time improvement scenario, the weights fall heavily on the measures of corridor speed and number
of lanes. Existing ridership receives only a 10% weight in this scenario. Unsurprisingly, the Stony Island corridor,
with its high number of lanes and correspondingly high travel times emerges as the preferred alternative. However,
the Cottage Grove corridor actually posts a higher score under corridor speed, and outweighs Stony Island by a
factor of two in the discounted measure of existing ridership. A summary of the results of the travel time emphasis
scenario is shown in Table VII.
Corridor Conflict Avoidance Scenario
The final initial scenario explores the results of a weighting scheme that emphasizes avoidance of competition with
existing service. The greatest emphasis, a 45% weight, is placed on avoiding CTA service duplication. Lesser
emphasis (15%) is placed on avoiding Metra service duplication.
The results of the competition avoidance scenario are found in Table VIII, and as might be predicted, the
total scores are proportionate to the distance from the CTA Red Line corridor. The lowest scores are found in the
King Drive corridor, which runs a scant half-mile from the Red Line, and along Cottage Grove, a full mile from the
Red Line but bordering a Metra line for much of its length. Interestingly, the Jeffery corridor, which features a high
level of service and the second-highest ridership of all the corridors, scores best in this scenario. This finding is
consistent with CTA policy of avoiding duplicating service where possible.

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Summary of All Weighting Results
The different weighting scenarios place a high emphasis on a few measures, with very predictable results. In each
scenario, one measure is typically weighted at 40%, with two measures accounting for up to 70% of the total weight,
resulting in a very coarse identification of the category leaders for each criterion. A summary of initial results can be
found in Table IX.
The low ranking for King Drive in all scenarios is consistent with the initial observation that this corridor
may constitute an inferior solution. In the raw measure values, it was outranked by Cottage Grove in all measures
except for distance from Metra, a value that has not been weighted heavily in any scenario.
Among the higher scoring corridors, few emerge as choices without compromise. The Jeffery corridor
leads in two scenarios, confirming its status as the current leader in ridership and competition avoidance, but doesn’t
show up particularly well in travel time improvement potential. Moreover, its width of only one lane through the
length of the corridor would make it an unattractive candidate for BRT service. The Stony Island corridor scored the
highest in the travel time improvement scenario, yet its low current ridership would tend to suggest that the same
factors that make its buses move quickly—fast travel times and high number of lanes--also make it an unattractive
destination for bus riders.
An interesting result is noted in the second-place scoring. Cottage Grove, the second ranking finisher in the
travel time and ridership improvement scenarios, emerges as unattractive only under the service conflict avoidance
scenario. However, its current ridership score—highest of all corridors—shows that the corridor is already attractive
to bus riders.
CONCLUSIONS
Applying the concordance analysis methodology is a straightforward process, yet it necessitates a number of
assumptions. Most of these assumptions result from the difficulty in obtaining needed information. The limited
scope of the study further necessitates assumptions. However, as these assumptions may be addressed by obtaining
more complete data and including it in the study, they do not detract from the usefulness of the method.
The four generalized criteria are likely sufficient for evaluating corridors from the agency’s perspective, which is
consistent with the scope of this study. It is assumed that other factors, such as residents’ concern regarding impacts
resulting from the implementation of BRT service, would necessarily be addressed in a different study.
While the results of this study should be considered in light of the data used, these concerns involve only the data
used, and not the method used to analyze the data. The concordance analysis method has previously shown to be
useful in selecting among transportation alternatives. Given a wider variety of more specific data inputs, the method
can be readily adapted to the question of BRT corridor selection.
ACKNOWLEDGEMENTS
Financial assistance for the study was provided through the “Making CTA More Competitive as it Moves into the
21st Century” program, subcontracted through the Great Cities Urban Data Visualization Program and the Urban
Transportation Center of the University of Illinois at Chicago, and through URS Corporation and the Chicago
Transit Authority.
REFERENCES
1. Giuliano, Genevieve. “A Multicriteria Method for Transportation Investment Planning.” Transportation
Research, vol. 19A, no. 1, February 1985, pp 29-41.
2. Hastak, Makarand and Maher M. Abu-Mallouh. “MSRP: Model for Station Rehabilitation Planning.” Journal
of Infrastructure Systems, vol. 127, no. 2, June 2001, pp. 58-66.

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Table I: Selected Attributes of Corridors
Distance to Distance to
nearest nearest
Mean CTA rail Metra
Daily Number of service service
Corridor Boardings Lanes (miles) (miles)
Cottage Grove Avenue 28,848 1.10 0.52 .82
Jeffery Boulevard 27,961 1.70 1.02 .32
Martin Luther King Drive 22,066 3.20 2.02 .82
Stony Island Avenue 12,147 1.00 2.52 1.32

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Table II: Average Current Bus Travel Speeds in Candidate Corridors
AM Peak Travel Speed PM Peak Travel Mean Peak Travel
(mph) Speed (mph) Speed
Corridor Northbound Southbound (mph)
Martin Luther King Drive 10.9 10.0 10.5
Cottage Grove Avenue 10.4 12.0 11.2
Stony Island Avenue 10.0 7.5 8.8
Jeffery Boulevard 10.0 8.6 9.3

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Table III: Summary of Criteria and Respective Measures
Criteria
Increased Shorter travel Maximize distance from
ridership time existing service
Current ridership X
Measure
Current service speed X X
Number of lanes X
Distance from Red Line X
Distance from Metra Lines X

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Table IV: Summary of Normalized Measures
Mean
Distance to Mean
Speed Mean Number CTA rail Distance to
Through of Lanes service Metra service
Corridor Ridership Corridor (each direction) (miles) (miles)
Martin Luther King Drive 0.76 0.93 0.34 0.21 0.62
Cottage Grove Avenue 1.00 1.00 0.53 0.41 0.24
Stony Island Avenue 0.42 0.83 1.00 0.80 0.62
Jeffery Boulevard 0.97 0.78 0.31 1.00 1.00

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Table V: Summary of Measurement Weights Under Initial Weighting Scenarios
Measurement
Current
Current service Number Distance from Distance from
ridership speed of lanes Red Line Metra Lines
Increasing
Weighting Scenario
ridership 30% 40% 10% 15% 5%
Emphasis
Travel Time
10% 40% 30% 15% 5%
improvement
Avoiding
competition with 10% 20% 10% 45% 15%
existing service

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Table VI: Analysis Results, Ridership Emphasis Scenario
Corridor Distance
Ridership Speed Number of Distance to to Metra
Corridor (30%) (40%) Lanes (10%) CTA (15%) (5%) Sums
Martin Luther
0.23 0.37 0.03 0.03 0.03 0.699
King Drive
Cottage Grove
0.30 0.40 0.05 0.06 0.01 0.826
Avenue
Stony Island
0.13 0.33 0.10 0.12 0.03 0.709
Avenue
Jeffery Boulevard 0.29 0.31 0.03 0.15 0.05 0.834

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Table VII: Analysis Results, Travel Time Emphasis Scenario
Ridership Corridor Speed Number of Distance to CTA Distance to
Corridor (10%) (40%) Lanes (30%) (15%) Metra (5%) Sums
Martin Luther
0.08 0.37 0.10 0.03 0.03 0.615
King Drive
Cottage Grove
0.10 0.40 0.16 0.06 0.01 0.732
Avenue
Stony Island
0.04 0.33 0.30 0.12 0.03 0.825
Avenue
Jeffery Boulevard 0.10 0.31 0.09 0.15 0.05 0.703

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Table VIII: Analysis Results, Service Conflict Avoidance Scenario
Ridership Corridor Speed Number of Distance to Distance to
Corridor (10%) (20%) Lanes (10%) CTA (45%) Metra (15%) Sums
Martin Luther
0.08 0.19 0.03 0.09 0.09 0.484
King Drive
Cottage Grove
0.10 0.20 0.05 0.18 0.04 0.572
Avenue
Stony Island
0.04 0.17 0.10 0.36 0.09 0.762
Avenue
Jeffery Boulevard 0.10 0.16 0.03 0.45 0.15 0.884

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Table IX: Summary of Overall Rankings under Initial Weighting Scenarios
Highest Score Second Highest Score Lowest Score
Increasing
Jeffery Cottage Grove King Drive
Ridership
Travel Time
Stony Island Cottage Grove King Drive
Improvement
Avoiding
Competition with Jeffery Stony Island King Drive
Existing Service

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Figure 1: Map of Corridors and Rail Service

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Figure 2: Graphic Summary of Normalized Data
100%
Martin Luther
King Drive
Cottage Grove
Percent of Maximum Value
Avenue
50% Stony Island
Avenue
Jeffery
Boulevard
0%
Ridership Speed Mean Distance Distance
Number to CTA to Metra
of Lanes Rail

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Figure 3: Weights for Ridership Improvement Emphasis Scenario
Current Speed Current Speed
Number of
Lanes Improving Ridership
Improving Travel Time
Distance from
CTA
Avoiding Competing
Distance from Service
Current
Metra
Ridership