DART
Light Rail Expansion
Impact Analysis
Prepared by
NuStats for
North Central Texas Council of Governments
and Dallas Area Rapid Transit
January 2006
DART
Light Rail Expansion
Impact Analysis
Prepared by
NuStats for
North Central Texas Council of Governments
and Dallas Area Rapid Transit
January 2006
What is NCTCOG?
The North Central Texas Council of Governments is a voluntary association of cities, counties,
school districts, and special districts which was established in January 1966 to assist local
governments in planning for common needs, cooperating for mutual benefit, and coordinating
for sound regional development.
It serves a 16-county metropolitan region centered around the two urban centers of Dallas and
Fort Worth. Currently the Council has 233 members, including 16 counties, 165 cities,
23 independent school districts, and 29 special districts. The area of the region is approximately
12,800 square miles, which is larger than nine states, and the population of the region is over
6.15 million, which is larger than 30 states.
NCTCOG's structure is relatively simple; each member government appoints a voting
representative from the governing body. These voting representatives make up the General
Assembly which annually elects a 15-member Executive Board. The Executive Board is
supported by policy development, technical advisory, and study committees, as well as a
professional staff of 235.
NCTCOG's offices are located in Arlington in the Centerpoint Two Building at 616 Six Flags Drive
(approximately one-half mile south of the main entrance to Six Flags Over Texas).
North Central Texas Council of Governments
P. O. Box 5888
Arlington, Texas 76005-5888
(817) 640-3300
NCTCOG's Department of Transportation
Since 1974 NCTCOG has served as the Metropolitan Planning Organization (MPO) for
transportation for the Dallas-Fort Worth area. NCTCOG's Department of Transportation is
responsible for the regional planning process for all modes of transportation. The department
provides technical support and staff assistance to the Regional Transportation Council and its
technical committees, which compose the MPO policy-making structure. In addition, the
department provides technical assistance to the local governments of North Central Texas in
planning, coordinating, and implementing transportation decisions.
Prepared in cooperation with the Texas Department of Transportation and the U. S. Department
of Transportation, Federal Highway Administration, and Federal Transit Administration.
"The contents of this report reflect the views of the authors who are responsible for the opinions, findings,
and conclusions presented herein. The contents do not necessarily reflect the views or policies of the
Federal Highway Administration, the Federal Transit Administration, or the Texas Department of
Transportation."
DART LIGHT RAIL EXPANSION IMPACT ANALYSIS
TABLE OF CONTENTS
I. INTRODUCTION..................................................................................................................... I-1
Project Overview ........................................................................................................................ I-1
Survey Methods ......................................................................................................................... I-2
II. SURVEY RESULTS .............................................................................................................. II-1
Demographic Profiles ................................................................................................................ II-1
Surveyed Trips ........................................................................................................................ II-10
General Service Usage ........................................................................................................... II-37
III. LRT IMPACT ON TRANSPORTATION NETWORK ........................................................... III-1
IV. APPENDIX A: STUDY METHODS ..................................................................................... IV-1
Sample Plan ............................................................................................................................. IV-1
Data Collection Schedule ......................................................................................................... IV-1
Staffing ..................................................................................................................................... IV-2
Surveyor Training ..................................................................................................................... IV-3
Focus Group and Pilot Testing................................................................................................. IV-4
Survey Instrument .................................................................................................................... IV-5
Data Collection Methodology ................................................................................................... IV-6
Data Entry and Data Cleaning.................................................................................................. IV-6
Geocoding ................................................................................................................................ IV-9
Response Rate....................................................................................................................... IV-11
V. APPENDIX B: BOARDING AND ALIGHTING LOCATIONS BY LINE.................................. V-1
VI. APPENDIX C: SURVEY INSTRUMENT............................................................................. VI-1
Exhibit
Page
II-1
Home Locations of ALL Respondents by Line on Which They were Surveyed....... II-2
II-2
Home Locations of Dallas and Collin County Respondents by Line on Which
They were Surveyed................................................................................................ II-3
II-3
Demographic Characteristics by Line ...................................................................... II-5
II-4
Demographic Characteristics by Peak / Off Peak.................................................... II-7
II-5
Demographic Characteristics of Zero-Vehicle Households ..................................... II-9
II-6
Trip Origins ............................................................................................................ II-11
II-7
Trip Destinations.................................................................................................... II-12
II-8
Trip Origins and Destinations – Red Line .............................................................. II-14
II-9
Trip Origins and Destinations – Blue Line ............................................................. II-16
II-10
Red Line Boarding Stations by Time of Day.......................................................... II-18
II-11
Red Line Alighting Stations by Time of Day .......................................................... II-20
II-12
Blue Line Boarding Stations by Time of Day ......................................................... II-21
II-13
Blue Line Alighting Stations by Time of Day.......................................................... II-22
II-14
Red Line Boarding and Alighting Stations In-Bound During AM Peak .................. II-24
II-15
Red Line Boarding and Alighting Stations Out-Bound During PM Peak................ II-25
II-16
Blue Line Boarding and Alighting Stations In-Bound During AM Peak.................. II-26
II-17
Blue Line Boarding and Alighting Stations Out-Bound During PM Peak ............... II-28
II-18
Access Mode ......................................................................................................... II-29
II-19
Type of Trip ........................................................................................................... II-30
II-20
Characteristics of Temporary Rail Users ............................................................... II-31
II-21
How Often Make this Trip ...................................................................................... II-33
II-22
Length of Time Making this Trip ............................................................................ II-34
II-23
Why Started Using Light Rail for this Trip.............................................................. II-35
II-24
Why Continue Using Light Rail for this Trip ........................................................... II-36
II-25
Experiences and Influences by Line ...................................................................... II-38
II-26
Length of Time Using Rail ..................................................................................... II-39
II-27
Prior Mode ............................................................................................................. II-40
II-28
Use DART to Access American Airlines Center .................................................... II-40
II-29
Characteristics of American Airlines Center Users................................................ II-41
III-1
Freeway ADT in the North Central Corridor 2004................................................... III-5
III-2
Arterial ADT in the North Central Corridor 2004 ..................................................... III-6
III-3
Estimated ADT in the North Central Corridor No-Build Scenario ........................... III-6
III-4
Estimated ADT in the North Central Corridor No-Build Scenario ........................... III-7
IV-1
Geocoding Match Rate ......................................................................................... IV-11
A-1
Red Line Respondents’ Boarding and Alighting Locations...................................... V-1
A-2
Blue Line Respondents’ Boarding and Alighting Locations ..................................... V-2
ABSTRACT
TITLE:
DART LRT Expansion Impact Analysis
Study
CONTACTS:
Ruth Boward
Senior Transportation Planner
E-mail: [email protected]
SUBJECT:
Results of an intercept onboard study of
DART’s passengers who use the most
recent light rail extension portion of the Red
and Blue Lines.
DATE:
January 2006
SOURCE OF COPIES:
Regional Information Center
North Central Texas Council of
Governments
P. O. Box 5888
Arlington, Texas 76005-5888
(817) 640-3300
ABSTRACT:
A report summarizing the findings of an
intercept onboard survey of light rail
passengers who use the most recent
extended sections of the Red and Blue
Lines. The survey was conducted to assess
reasons for using light rail,
origins/destinations, and demographic
characteristics. An assessment of the
impact of light rail on the transportation
network was also conducted as part of the
study.
I. INTRODUCTION
PROJECT OVERVIEW
In 2002, Dallas Area Rapid Transit (DART) expanded service on its Red and Blue light rail line
extensions. For the Red Line, the new stations extended from the Parker Road station to the
Walnut Hill station and for the Blue Line, the new stations included those from the Downtown
Garland station to the White Rock station. The expanded service has been successful, as
evidenced by its steady attraction of new riders.
While DART has conducted basic assessments of these new light rail passengers over the past
four years, there still existed a need to develop detailed user profiles of those who use the new
light rail stations that were built as part of the 2002 service expansion. In particular, DART was
interested in understanding previous travel patterns, home location, and travel mode shifts
(particularly from auto drivers to light rail) as well as the impact of this new service on travel
times and air quality. In addition, the North Central Texas Council of Governments (NCTCOG)
was interested in understanding how the expanded light rail service has provided area residents
with an alternative transportation option, who is currently using the system, and what impact the
expansion has had on travel time savings. This information, coupled with the analysis of
relevant pre-light rail expansion data, will provide additional insight in modeling updates.
To meet these objectives, NCTCOG contracted with NuStats Partners, L.P., (Austin, Texas) to
conduct an on-board survey of riders of the new extension. NuStats was assisted by URS
Corp., who lead the analysis of the impacts of the extension on the transportation network, and
Dunbar Transportation Consultants, who lead the assembly and analysis of the ridership and
transportation system data.
I-1
SURVEY METHODS
The on-board survey was conducted by NuStats over a 13-day period, beginning May 6 through
May 12 and continuing May 17 through May 22, from 7 am to 7 pm each day in order to provide
coverage for all service time periods (AM peak, mid-day, PM peak, and evening). A brief
synopsis of the study methods is included in this section. A more detailed description is
provided in Appendix A.
The data collection plan entailed the collection of 1,800 surveys, 900 each from the Red and
Blue Lines. Within each line, the goal was to have the 900 surveys distributed approximately as
660 weekday and 240 weekend surveys. Since the ultimate goal of the data collection effort was
to obtain details about the travel pattern of riders using the extended portion of each line, the
survey was distributed only to those passengers age 16 or older who boarded at the new
stations (between Parker Road and Walnut Hill stations on the Red Line and between
Downtown Garland and White Rock stations on the Blue Line).
The survey instrument itself consisted of 24 questions organized into four general categories:
1. Demographics
2. Trip origin/destination (boarding station, alighting station, origin, destination, trip
purpose)
3. Travel history (length of time using light rail service, mode of access, frequency of use,
etc.),
4. Factors influencing the use of rail service.
A total of 1,865 surveys were collected, 931 from Red Line passengers and 925 from Blue Line
passengers. These surveys were edited for completeness, scanned into an electronic format,
then geocoded (for the origin, destination, and boarding/alighting stations). Section II of this
report provides a summary of the survey results. Section III provides an assessment of the LRT
impact on the transportation network, as well as a summary of key conclusions.
I-2
II. SURVEY RESULTS
The Red and Blue Line Extension on-board survey effort resulted in the collection of data from
1,856 respondents: 931 (50%) from the Blue Line and 925 (50%) from the Red Line. This
section of the report provides a summary of the survey results, focusing first on a demographic
profile, followed by characteristics of the surveyed trip, and concluding with a more general
profile of travel. The responses in this report display all survey results (unweighted) with the
results categorized by line as well as overall.
According to Henry,1 survey data are weighted when the sample is drawn with unequal
probabilities, thus requiring an adjustment to minimize sampling bias. Unequal probabilities can
result from disproportionate sampling techniques or duplication of sampling frames. In this
study, the universe was described as all passengers boarding the rail service at and beyond
stations that opened during the 2002 service expansion. The data set contains equal numbers
of Red and Blue service riders, and data collection called for distribution of surveys to every
third passenger boarding. Data weighting was not a part of the scope of services, thus there is
the potential for sampling bias in the data in that certain population sub-groups may not be
proportionately represented in the results. To the extent that this bias may influence drawing
conclusions from the survey data for key indicators, statistical tests for significant differences
are included to guide the reader.
DEMOGRAPHIC PROFILES
The survey was administered to riders boarding at designated stations associated with the rail
line extensions. Their home locations across Collin, Dallas and Tarrant Counties are shown on
the map on the following page (Exhibit II-1). Exhibit II-2 focuses more closely on riders living in
Collin and Dallas Counties only.
1
Henry, Gary T., in Practical Sampling (Vol. 21 of the Applied Social Research Methods Series by Sage
Publications), 1990.
II-1
II-2
HOME LOCATIONS OF ALL RESPONDENTS BY LINE ON WHICH THEY WERE SURVEYED
EXHIBIT II-1
II-3
HOME LOCATIONS OF DALLAS AND COLLIN COUNTY RESPONDENTS BY LINE ON WHICH THEY WERE SURVEYED
EXHIBIT II-2
The survey was designed to document several important demographic characteristics about the
rail users. This included gender, age, household size, vehicle availability, employment status,
and household income. The results, shown in Exhibit II-3, are for respondents overall as well as
for each line.
Red Line riders were predominantly male (61%), under the age of 55 (86%), residing in
households of 1 of 2 persons (51%). The majority has access to at least one household vehicle,
with only 18% reporting no vehicles available. Two-thirds (67%) reported being employed fulltime and sixty eight percent reported household incomes under $75,000.
Blue Line riders were also predominantly male (61%), under the age of 55 (88%), residing in
slightly larger households as compared to Red Line riders but with fewer vehicles on average
(23% reporting no household vehicle). A smaller proportion of those on the Blue Line indicate
being employed full time (58%). Seventy nine percent reported household incomes under
$75,000.
Statistically, the Red Line riders differed from the Blue Line riders with regards to:
•
Age: there was a statistically lower proportion of riders younger than 24 on the Red Line
as compared to the Blue Line proportions at the 90% confidence interval. (There was no
difference among proportions of any other age group).
•
Income: there was a statistical difference in the proportion of Red Line riders as
compared to Blue Line riders at the 90% confidence interval with respect to the income
categories of $25,000 to < $45,000 (fewer Red Line riders than Blue Line riders) and the
income categories of $75,000 to <$100,000 and $100,000 to <$125,000 (a higher
proportion of Red Line riders reporting higher incomes compared to Blue Line riders.)
II-4
EXHIBIT II-3
DEMOGRAPHIC CHARACTERISTICS BY LINE
CHARACTERISTIC
RED LINE
(N=931)
BLUE LINE
(N=925)
TOTAL
(N=1,856)
Gender
Male
60.8%
60.6%
60.7%
Female
39.2%
39.4%
39.3%
Age
Under 24
18.7%
26.3%
22.5%
25-34
21.6%
20.0%
20.8%
35-44
25.0%
23.2%
24.1%
45-54
20.8%
18.3%
19.6%
55-64
8.5%
8.3%
8.4%
65+
4.5%
3.0%
3.8%
Refused
Household Size
1
0.9%
0.9%
0.9%
20.4%
16.3%
18.4%
2
30.8%
27.0%
28.9%
3
18.8%
23.6%
21.2%
4
17.8%
17.5%
17.7%
5+
Household Vehicles
0
10.5%
14.1%
12.3%
18.0%
23.2%
20.6%
1
27.5%
28.9%
28.2%
2
35.8%
30.6%
33.2%
3+
16.4%
15.1%
15.8%
Refused
Employment Status
Employed Full Time
2.3%
2.2%
2.2%
67.3%
58.2%
62.8%
Employed Part Time
11.0%
12.8%
11.9%
Student Full Time
12.8%
15.6%
14.2%
Student Part Time
3.9%
3.7%
3.8%
Retired
5.5%
6.3%
5.9%
Homemaker
1.5%
1.0%
1.2%
Unemployed
6.6%
11.8%
9.2%
II-5
Demographic Characteristics by Line (Continued)
Household Income
< $25k
28.4%
30.5%
29.4%
$25k - < $45k
20.9%
27.0%
24.0%
$45k- < $75k
19.1%
21.1%
20.1%
$75k - < $100k
12.7%
7.5%
10.1%
$100k - <$125,000
7.5%
3.6%
5.5%
$125k - <$150,000
3.3%
1.3%
2.3%
$150,000 +
2.5%
2.4%
2.4%
Income refusals
Ride Time
Peak
5.6%
6.7%
6.1%
35.1%
33.9%
35.0%
Off-Peak
57.8%
55.6%
57.0%
Unknown
7.1%
10.5%
8.0%
Exhibit II-4 summarizes the same characteristics based on whether the rider rode during the
peak or off-peak period. The differences between peak and off-peak riders was of particular
concern to the study sponsors, given that more than half of the survey respondents were offpeak riders although this particular group only accounts for 20% of DART ridership. As shown in
this exhibit, there are three groups of riders: peak riders (35%), off-peak riders (57%), and
“other” riders (whose time of rail usage was not documented – 8%). The only statistical
difference to note between the peak and off-peak riders was in the employment status – peak
riders were employed full or part time to a much higher degree as compared to off-peak riders.
II-6
EXHIBIT II-4
DEMOGRAPHIC CHARACTERISTICS BY PEAK/OFF PEAK
CHARACTERISTIC
Peak Rider
(N=640)
Off-Peak Rider
(N=1052)
Other Rider
(N=163)
TOTAL
(N=1,856)
Gender
Male
55.9%
65.1%
51.0%
60.7%
Female
44.1%
34.9%
49.0%
39.3%
Age
Under 24
20.0%
25.1%
15.3%
22.5%
25-34
21.3%
20.5%
20.9%
20.8%
35-44
25.0%
22.8%
29.4%
24.1%
45-54
21.6%
18.6%
17.2%
19.6%
55-64
8.3%
7.9%
12.3%
8.4%
65+
3.1%
4.2%
3.7%
3.8%
Refused
Household Size
1
0.8%
0.9%
1.2%
0.9%
16.1%
19.6%
19.6%
18.4%
2
30.5%
28.6%
24.5%
28.9%
3
22.8%
20.0%
22.7%
21.2%
4
15.8%
18.9%
17.2%
17.7%
5+
Household Vehicles
0
13.8%
11.2%
13.5%
12.3%
18.8%
22.1%
17.8%
20.6%
1
27.2%
29.5%
23.9%
28.2%
2
35.5%
31.8%
33.1%
33.2%
3+
17.2%
14.3%
20.2%
15.8%
Refused
Employment Status
Employed Full Time
1.4%
2.3%
4.9%
2.2%
76.3%
44.6%
32.5%
62.8%
Employed Part Time
8.6%
14.0%
11.0%
11.9%
Student Full Time
13.0%
16.1%
6.7%
14.2%
Student Part Time
2.7%
4.5%
3.7%
3.8%
Retired
2.5%
7.7%
7.4%
5.9%
Homemaker
0.8%
1.3%
2.5%
1.2%
Unemployed
5.3%
11.4%
9.8%
9.2%
II-7
Demographic Characteristics by Peak/Off Peak (Continued)
Household Income
< $25k
24.8%
32.3%
28.2%
29.4%
$25k - < $45k
24.1%
23.4%
27.6%
24.0%
$45k- < $75k
19.7%
20.8%
17.2%
20.1%
$75k - < $100k
12.3%
8.7%
9.8%
10.1%
$100k - <$125,000
7.8%
4.1%
6.1%
5.5%
$125k - <$150,000
3.0%
1.9%
2.5%
2.3%
$150,000 +
3.0%
1.8%
4.3%
2.4%
Income refusals
Line
5.3%
6.9%
4.3%
6.1%
Red
50.9%
51.1%
40.5%
50.1%
Blue
49.1%
48.9%
59.5%
49.9%
Exhibit II-5 summarizes the demographic characteristics of respondents who reported not
owning any household vehicles. This is again summarized by line. In general, respondents with
no household vehicles are more likely to be from small households with a greater proportion of
unemployed residents and lower incomes as compared to all respondents.
II-8
EXHIBIT II-5
DEMOGRAPHIC CHARACTERISTICS OF ZERO-VEHICLE HOUSEHOLDS
CHARACTERISTIC
RED LINE
(N=168)
BLUE LINE
(N=215)
TOTAL
(N=383)
Gender
Male
64.2%
61.7%
62.8%
Female
35.8%
38.3%
37.2%
Under 24
17.9%
20.9%
19.6%
25-34
22.6%
26.0%
24.5%
35-44
22.6%
23.3%
23.0%
45-54
26.2%
18.6%
21.9%
55-64
6.5%
7.4%
7.0%
65+
4.2%
2.3%
3.1%
Refused
Household Size
1
0.0%
1.4%
0.8%
49.4%
39.1%
43.6%
2
25.0%
28.8%
27.2%
3
14.3%
14.9%
14.6%
4
6.0%
9.3%
7.8%
5+
3.6%
7.0%
5.5%
Employment Status
Employed Full Time
56.5%
48.8%
52.2%
Employed Part Time
14.9%
17.2%
16.2%
Student Full Time
11.9%
9.8%
10.7%
Student Part Time
5.4%
3.3%
4.2%
Retired
4.2%
5.1%
4.7%
Homemaker
0.6%
1.4%
1.0%
Unemployed
Household Income
< $25k
17.9%
22.8%
20.6%
66.1%
68.4%
67.4%
$25k - < $45k
22.0%
24.7%
23.5%
$45k- < $75k
4.2%
2.8%
3.4%
$75k - < $100k
2.4%
0.5%
1.3%
$100k - <$125,000
0.0%
0.0%
0.0%
$125k - <$150,000
0.0%
0.0%
0.0%
$150,000 +
2.5%
2.4%
2.4%
Income refusals
5.4%
3.7%
4.4%
Age
II-9
SURVEYED TRIPS
Given the purpose of the survey, most of the survey questions focused on the origins and
destinations of travel on the day of the survey. As a result, respondents provided details about
the origins and destinations of travel, boarding and alighting stations, reason for travel on the
survey day, access mode, and whether their use of DART for this particular surveyed trip was
temporary or permanent. This section of the report summarizes those details.
The first question was pertaining to the trip origin. As shown in Exhibit II-6, the majority of Red
Line users began their trip at home (58%) or work (25%). Blue Line users reported a greater
variation in origins of travel, with only 53% reporting a home start, and 18% a work start.
II-10
II-11
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Ho
me
Sc
ho
ol
W
or
k
Blue Line
Re
sid
en
ce
Me
dic
al
Red Line
Total
St
To
St
Ot
or
ate
he
ur
e/R
ist
r
o
rO
Lo
es
tau
ca
ffic
tio
ra
eB
n
nt
ldg
TRIP ORIGINS
EXHIBIT II-6
Re
fus
ed
II-12
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Ho
me
Sc
ho
ol
W
or
k
e
Blue Line
Re
sid
en
c
Me
dic
al
or
e/R
Red Line
St
es
ta
ur
an
t
TRIP DESTINATIONS
EXHIBIT II-7
Total
To
ur
is
tL
oc
ati
on
St
ate
or
Of
fic
eB
ldg
Ot
he
r
Re
fu
of Red Line respondents reported trips to school and to tourist destinations (the zoo, the museum or aquarium).
se
d
In terms of trip destinations, most respondents were on their way to home or to work, as illustrated in Exhibit II-7. A greater proportion
The table shown in Exhibit II-8 summarizes reported trip origins and destinations for
respondents surveyed on the Red Line. The numbers shown in each cell represent the total
number of trips surveyed that were associated with travel between the reported origin and
destination. For example, of all surveyed trips, 4% began at home and ended at school. The
Total column shows the total proportion of all trips that began at a particular origin. As indicated,
58% of all Red Line trips began at home. The total row shows the proportion of all trips that
ended at a particular destination. Here, 34% ended at home. The most common origins and
destinations of travel were between home and work (52%), followed by 7% between home and
school, and 7% between home and popular tourist destinations (zoo, museums, and aquarium).
In reviewing the origins and destinations of travel reported by Red Line respondents and
summarized in Exhibit II-8, the following summarizes the travel based on standard modeling
classifications of home-based work, non-home based work, home-based other, and non-home
based other:
•
52% of the trips were home-based work trips (defined as the origin being home and the
destination being work or vice versa).
•
5% of the trips were non-home based work trips (defined as one trip end being work and
the other being something other than home).
•
40% were home-based other trips (defined as one trip end being home and the other
being something other than work)
•
6% were non-home based other trips (neither trip end was home or work).
II-13
II-14
4.7%
0.1%
0.3%
32.0%
0.8%
1.6%
34.2%
Refused
Total
0.1%
4.2%
1.2%
0.1%
0.1%
2.7%
0.9%
0.5%
6.6%
0.2%
0.1%
0.1%
0.4%
0.1%
0.1%
0.1%
0.1%
1.1%
Other
Office Bldg
Zoo /
Museum /
Aquarium
State Gov’t
Bldg
0.2%
0.3%
0.2%
0.1%
0.1%
0.5%
Restaurant
Church
1.1%
3.8%
0.2%
0.1%
8.7%
0.8%
0.1%
0.2%
0.1%
0.1%
100.0%
3.1%
1.2%
0.3%
0.9%
1.2%
0.3%
0.6%
2.7%
25.4%
4.2%
57.9%
1.0%
0.1%
0.3%
7.1%
Store/Mall
0.3%
0.2%
3.1%
1.1%
0.1%
Refused
1.1%
0.3%
Other
Hospital/
Dr. Office
0.1%
0.2%
5.8%
Zoo /
State Office
Office Bldg
Museum /
Bldg
Aquarium
0.1%
0.1%
0.3%
Church
1.7%
0.1%
0.1%
0.6%
Restaurant
Residence
1.2%
0.3%
2.2%
Store/
Mall
0.3%
1.2%
Hospital /
Dr. Office
22.8%
0.2%
3.4%
Residence
Work
0.5%
29.5%
Work
0.1%
4.2%
School
3.0%
Home
TOTAL
School
Home
Origin
DESTINATION
TRIP ORIGINS AND DESTINATIONS – RED LINE
EXHIBIT II-8
Exhibit II-9 shows similar travel trends, this time for passengers surveyed on the Blue Line. As
illustrated, 53% of all Blue Line trips began at home while 37% ended at home, for a total of
91% of all trips. Of these, 22% ended at work, 3% ended at tourist destinations, and 3% ended
at school.
In reviewing the origins and destinations of travel reported by Blue Line respondents and
summarized in Exhibit II-9, the following summarizes the travel based on standard modeling
classifications of home-based work, non-home based work, home-based other, and non-home
based other:
•
38% of the trips were home-based work trips (defined as the origin being home and the
destination being work or vice versa).
•
4% of the trips were non-home based work trips (defined as one trip end being work and
the other being something other than home).
•
52% were home-based other trips (defined as one trip end being home and the other
being something other than work).
•
6% were non-home based other trips (neither trip end was home or work).
II-15
II-16
0.1%
0.1%
1.1%
1.0%
Store/Mall
Restaurant
4.1%
24.9%
5.3%
1.5%
2.7%
0.2%
0.1%
3.1%
0.3%
4.1%
0.1%
16.2%
1.6%
100.0%
8.9%
37.4%
0.2%
Total
1.3%
0.4%
1.1%
1.6%
1.7%
2.2%
2.5%
17.9%
6.2%
53.1%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
13.7%
6.3%
0.4%
0.1%
0.1%
0.2%
0.1%
3.0%
Refused
0.1%
0.1%
0.2%
Refused
2.2%
0.1%
0.2%
2.8%
Other
0.2%
0.3%
0.1%
Church
1.2%
0.1%
0.1%
0.1%
Restaurant
Other
0.1%
0.2%
0.1%
0.1%
2.2%
Store/
Mall
1.0%
0.1%
1.0%
0.1%
0.1%
0.1%
1.2%
Hospital /
Dr. Office
TOTAL
1.0%
0.1%
0.3%
0.1%
0.2%
0.2%
0.2%
4.1%
Residence
Zoo /
State Office
Office Bldg
Museum /
Bldg
Aquarium
Office Bldg
Zoo /
Museum /
Aquarium
State Gov’t
Bldg
0.1%
0.1%
1.8%
Hospital/
Dr. Office
0.8%
0.2%
1.6%
Residence
Church
1.2%
16.1%
0.4%
22.3%
Work
Work
0.1%
3.4%
School
5.3%
Home
School
Home
Origin
DESTINATION
TRIP ORIGIN AND DESTINATIONS – BLUE LINE
EXHIBIT II-9
Respondents were also asked for the stations at which they boarded and planned to exit the
trains. Exhibits II-10 through II-13 show the boarding and alighting stations as reported by
respondents on the Red and Blue Lines, stratified by time of day.
The first exhibit (II-10) shows the boarding stations by time of day for the Red Line. The stations
are in “in-bound” order. During the morning peak, more than half of the respondents (56%)
boarded the train at Parker Road. This was the largest boarding location across all time periods.
About 6% of respondents each boarded at Bush Turnpike, Arapaho Center, and Walnut Hill.
During the mid-day period, Parker Road was again the dominant boarding location (35%),
followed by Walnut Hill (9%), Arapaho Center (8%), and Downtown Plano (7%). For the PM
Peak, Parker Road still exhibited the largest percentage of boardings (26%), followed by Walnut
Hill (13%), Bush Turnpike (8%), and Arapaho Center (6%). Evening boardings were most
commonly seen at West End (22%), Parker Road (17%), Downtown Plano (9%), and
LBJ/Central (9%).
II-17
EXHIBIT II-10
RED LINE BOARDING STATIONS BY TIME OF DAY
TIME OF DAY
At what station did
you board this
train?
Parker Road
AM Peak
(< 9 am)
(N=99)
55.6%
TOTAL
Mid-day (9 am
PM Peak
– 2:59 pm)
(3 pm – 6 pm)
(N=515)
(N=227)
35.0%
25.6%
Downtown Plano
2.0%
6.8%
5.7%
Bush Turnpike
6.1%
4.1%
Galatyn Park
3.0%
Arapaho Center
Evening
Not recorded
(after 6 pm)
(N=66)
(N=23)
17.4%
21.2%
6.1%
6.0%
7.5%
6.1%
5.2%
1.4%
1.8%
1.5%
1.6%
6.1%
7.9%
5.7%
6.1%
6.9%
Spring Valley
2.0%
4.1%
3.1%
1.5%
3.3%
LBJ/Central
2.0%
1.4%
1.8%
4.5%
1.9%
Forest Lane
2.0%
2.7%
1.3%
4.5%
2.4%
Walnut Hill
6.1%
9.1%
12.8%
4.3%
12.1%
9.8%
Park Lane
2.0%
2.9%
2.2%
4.3%
3.0%
2.9%
1.0%
1.3%
4.3%
3.0%
1.2%
4.3%
4.5%
3.3%
Lovers Lane
8.7%
33.2%
8.7%
Mockingbird
3.0%
2.9%
4.0%
Cityplace
4.0%
2.3%
4.0%
1.5%
2.8%
1.4%
2.2%
1.5%
1.4%
1.2%
2.6%
13.0%
4.5%
2.0%
Akard
2.3%
4.0%
8.7%
6.1%
2.9%
West End
4.5%
3.5%
21.7%
3.0%
4.1%
1.7%
2.2%
1.6%
Convention
Center
0.2%
0.4%
0.2%
Cedars
0.2%
1.8%
0.5%
8 & Corinth
0.6%
0.9%
1.0%
0.4%
Pearl
St. Paul
Union
1.0%
1.0%
th
Dallas Zoo
1.0%
3.0%
0.8%
Tyler/Vernon
Hampton
0.8%
0.0%
1.0%
Westmoreland
0.4%
0.4%
0.4%
1.6%
0.9%
1.1%
Not provided
2.0%
3.7%
4.0%
4.3%
6.1%
3.8%
Total
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
II-18
In terms of alighting stations, most Red Line travelers in the AM peak alighted at St. Paul (13%),
Parker Road (11%), the West End (8%), or Arapaho Center (7%). For the mid-day Red Line
users, the most frequent alighting stations were Parker Road (17%), the West End (15%),
Arapahoe Center (7%), or Mockingbird (6%). PM peak alightings were concentrated at Parker
Road (27%), the West End, Downtown Plano, and Bush Turnpike (8% each). See Exhibit II-11.
II-19
EXHIBIT II-11
RED LINE ALIGHTING STATIONS BY TIME OF DAY
At what station
did you alight
from this train?
Parker Road
AM Peak
(< 9 am)
(N=99)
11.1%
Time of Day
Mid-day (9 am
PM Peak
– 2:59 pm)
(3 pm – 6 pm)
(N=515)
(N=227)
17.1%
26.7%
Total
Evening
Not recorded
(after 6 pm)
(N=66)
(N=23)
39.1%
25.8%
20.0%
Downtown
Plano
1.0%
7.2%
7.6%
13.0%
6.1%
6.7%
Bush
Turnpike
3.0%
2.7%
7.6%
17.4%
12.1%
5.0%
0.6%
0.4%
1.5%
0.5%
Galatyn Park
Arapaho
Center
7.1%
6.6%
2.7%
4.3%
6.1%
5.6%
Spring Valley
3.0%
3.5%
5.8%
4.3%
1.5%
3.9%
LBJ/Central
4.0%
2.1%
2.7%
Forest lane
6.1%
5.4%
4.9%
4.5%
5.2%
Walnut Hill
4.0%
2.5%
3.1%
1.5%
2.7%
Park Lane
3.0%
3.1%
3.1%
2.8%
Lovers Lane
5.1%
2.1%
2.2%
2.3%
Mockingbird
6.1%
5.8%
4.9%
Cityplace
5.1%
2.7%
2.2%
Pearl
5.1%
4.7%
2.2%
St. Paul
13.1%
3.5%
Akard
4.0%
West End
Union
9.1%
6.0%
2.6%
3.9%
2.2%
3.0%
4.1%
4.3%
2.2%
4.5%
3.7%
8.1%
14.8%
8.0%
13.6%
12.0%
2.0%
3.3%
3.1%
4.3%
2.8%
0.2%
0.1%
Cedars
2.0%
0.4%
2.7%
8 & Corinth
1.0%
0.2%
0.9%
Dallas Zoo
2.0%
3.5%
Tyler/ Vernon
1.0%
0.2%
Hampton
1.0%
0.2%
0.9%
Westmoreland
0.8%
2.7%
Not provided
0.2%
Total
13.0%
1.5%
Convention
Center
th
2.3%
2.0%
1.1%
1.5%
0.5%
3.0%
2.4%
0.2%
0.4%
1.5%
1.2%
0.1%
2.1%
1.3%
II-20
4.3%
3.0%
2.0%
The downtown Garland station was the primary boarding location for Blue Line respondents,
across all time periods (38%). Other frequently reported stations included White Rock (10%),
LBJ/Skillman (9%), and the West End (8%). The full distribution of Blue Line boardings by time
of day is show in Exhibit II-12.
EXHIBIT II-12
BLUE LINE BOARDING STATIONS BY TIME OF DAY
At what station did
you board this
train?
Downtown Garland
AM Peak
(< 9 am)
(N=121)
43.8%
Time of Day
Mid-day
PM Peak (3 pm Evening
Not
(9 am – 2:59
– 6 pm)
(after 6 pm) reported
pm) (N=503)
(N=193)
(N=11)
(N=97)
39.0%
32.1%
36.4%
39.2%
Forest/Jupiter
8.3%
6.8%
6.2%
LBJ/Skillman
9.9%
9.3%
11.9%
White Rock
9.1%
9.3%
12.4%
Mockingbird
4.1%
2.0%
Cityplace
1.7%
Pearl
38.2%
11.3%
7.5%
2.1%
9.1%
7.2%
9.8%
5.2%
3.1%
3.0%
2.0%
2.1%
1.0%
1.8%
3.3%
3.6%
2.1%
3.1%
3.1%
St. Paul
2.5%
1.2%
4.7%
2.1%
2.2%
Akard
2.5%
2.8%
4.7%
4.1%
3.4%
West End
5.0%
10.5%
5.2%
8.2%
8.3%
Union
2.5%
1.4%
1.0%
2.1%
1.5%
Convention Center
0.2%
Cedars
0.8%
th
8 & Corinth
0.8%
Morrell
0.6%
Illinois
0.8%
Kiest
0.8%
VA Medical Center
1.2%
18.2%
Total
18.2%
9.1%
0.1%
1.0%
0.5%
0.4%
0.5%
1.0%
0.5%
1.0%
1.0%
0.4%
1.0%
1.0%
1.1%
4.1%
1.0%
1.0%
3.2%
1.0%
Ledbetter
4.1%
3.8%
2.6%
Not provided
1.7%
3.6%
6.7%
18.2%
6.2%
4.4%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Total
Downtown Garland was also the main alighting station until 6 pm when the evening alightings
were twice as high in White Rock and West End. In terms of alightings by time of day, the
highest proportion of AM peak Blue Line users reported alighting at downtown Garland (26%),
St. Paul (13%), LBJ/Skillman or Akard (10% each).
II-21
For the mid-day period, downtown Garland had 25% of the alightings, followed by 20% in the
West End, 12% at LBJ/Skillman, and 8% at Forest/Jupiter station. Finally, for the PM peak, the
alightings were concentrated at: Downtown Garland (29%), LBJ/Skillman (15%), the West End
(12%), and Forest/Jupiter and White Rock (9% each). See Exhibit II-13.
EXHIBIT II-13
BLUE LINE ALIGHTING STATIONS BY TIME OF DAY
At what station did
you alight from this
train?
Downtown Garland
AM PEAK
(< 9 AM)
(N=121)
25.8%
Time of Day
Mid-day
PM Peak (3
Evening
Not reported
(9 am – 2:59 pm – 6 pm) (after 6 pm)
(N=97)
pm) (N=503)
(N=193)
(N=11)
25.1%
28.6%
9.1%
28.4%
Forest/Jupiter
6.7%
8.0%
8.9%
LBJ/Skillman
10.0%
12.0%
15.1%
White Rock
0.8%
4.6%
8.9%
Mockingbird
2.5%
5.0%
4.7%
Cityplace
5.8%
2.0%
1.6%
Pearl
5.0%
2.2%
2.6%
St. Paul
13.3%
3.4%
Akard
10.0%
West End
Total
26.1%
9.5%
8.1%
9.1%
10.5%
12.2%
18.2%
3.2%
5.0%
3.2%
4.4%
9.1%
4.2%
2.7%
9.1%
4.2%
2.9%
1.0%
7.4%
4.6%
3.8%
3.1%
3.2%
4.4%
6.7%
20.4%
11.5%
18.2%
12.6%
15.9%
Union
1.7%
1.6%
3.1%
9.1%
3.2%
2.2%
Convention Center
2.5%
1.0%
1.1%
1.0%
1.1%
0.4%
Cedars
0.4%
0.5%
0.6%
0.5%
0.7%
Morrell
0.4%
0.5%
0.3%
Illinois
0.8%
2.6%
1.0%
th
8 & Corinth
1.7%
Kiest
0.8%
0.6%
0.5%
2.1%
0.8%
VA Medical Center
0.8%
0.8%
1.0%
2.1%
1.0%
Ledbetter
0.8%
2.0%
1.6%
1.1%
1.6%
Not provided
5.0%
5.4%
3.6%
18.2%
2.1%
4.8%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Total
II-22
Appendix B contains tables that show the full origin/destination patterns of travel, based on
stations boarded and alighted, for each line. Here, the focus is on in-bound AM peak origins and
destinations of travel, as well as those out-bound PM peak trips. The results are presented by
line in Exhibits II-14 through II-17.
First, in-bound AM peak travel patterns for the Red Line are shown in Exhibit II-14. Here, each
proportion in the table reflects how the 72 surveys are distributed across various origin
destination pairs. The total rows reflect the total proportion of trips originating or concluding for a
given origin-destination pair. The main station again is Parker Road. Specifically, 75% of all
peak in-bound AM trips for the Red Line began at Parker Road. Eighteen percent ended at St.
Paul, followed by 10% at the West End, and 8% at Mockingbird.
II-23
II-24
Total
Dallas Zoo
Cityplace
Arapaho
Center
Walnut Hill
Downtown
Plano
Bush
Turnpike
Galatyn Park
At what
station did
you board
this train?
Parker Road
2.8%
1.4%
1.4%
2.8%
1.4%
1.4%
Parker Arapaho
Road Center
1.4%
1.4%
2.8%
1.4%
1.4%
5.6%
5.6%
5.6%
2.8%
2.8%
2.8%
2.8%
6.9%
6.9%
8.3%
1.4%
1.4%
5.6%
6.9%
1.4%
5.6%
St.
Paul
5.6% 18.1%
2.8%
1.4%
5.6% 13.9%
Spring LBJ / Forest Walnut Park Lovers Mocking Cityplace Pearl
Valley Central lane
Hill
Lane Lane
bird
5.6%
5.6%
9.7%
1.4%
8.3%
2.8%
1.4%
1.4%
2.8%
2.8%
1.4%
1.4%
2.8%
1.4%
1.4%
1.4%
1.4%
1.4%
1.4%
1.4%
2.8%
2.8%
6.9%
2.8%
5.6%
2.8%
75.0%
Total
2.8% 100.0%
2.8%
Akard West Union Cedars 8th &
Dallas Hampton Tyler /
Not
End
Corinth Zoo
Vernon reported
At what station will you get off the train?
(N=72)
RED LINE BOARDING AND ALIGHTING STATIONS IN-BOUND DURING AM PEAK
EXHIBIT II-14
II-25
At what station did Parker Road Downtown Bush Turnpike
you board this train?
Plano
Parker Road
0.9%
0.9%
Bush Turnpike
Galatyn Park
0.9%
Arapaho Center
1.7%
0.9%
Spring Valley
1.7%
LBJ/Central
1.7%
Forest lane
1.7%
Walnut Hill
12.8%
0.9%
4.3%
Park Lane
0.9%
Lovers Lane
0.9%
Mockingbird
2.6%
0.9%
Cityplace
4.3%
2.6%
Pearl
0.9%
St. Paul
4.3%
0.9%
Akard
3.4%
1.7%
West End
5.1%
1.7%
Union
0.9%
0.9%
0.9%
Convention Center
Cedars
1.7%
th
8 & Corinth
0.9%
Dallas Zoo
0.9%
Hampton
Westmoreland
0.9%
Not reported
2.6%
0.9%
Total
47.0%
9.4%
12.09%
1.7%
0.9%
0.9%
Arapaho
Center
2.6%
9.4%
0.9%
0.9%
0.9%
1.7%
1.7%
0.9%
5.1%
0.9%
0.9%
0.9%
1.7%
0.9%
3.4%
0.9%
0.9%
0.9%
0.9%
1.7%
0.9%
0.9%
1.7%
0.9%
2.6%
1.7%
0.9%
1.7%
0.9%
Total
9.4%
0.9%
0.9%
2.6%
2.6%
1.7%
2.6%
23.1%
2.6%
0.9%
6.8%
7.7%
2.6%
5.1%
6.0%
6.8%
4.3%
0.9%
2.6%
0.9%
0.9%
0.9%
1.7%
6.0%
1.7% 100.0%
Spring Valley LBJ/Central Forest lane Walnut Mockingbird Cityplace St. Paul Akard West End Cedars
Hill
0.9%
0.9%
0.9%
1.7% 0.9%
0.9% 1.7%
0.9%
At what station will you get off the train?
(N=118)
RED LINE BOARDING AND ALIGHTING STATIONS OUT-BOUND DURING PM PEAK
EXHIBIT II-15
Mockingbird (7%). Most (47%) alighted at Parker Road, Bush Turnpike (12%), Downtown Plano (9%), or Spring Valley (9%).
As seen in Exhibit II-15, outbound PM peak Red Line riders were most likely to board at Walnut Hill (23%), Parker Road (9%), Cityplace (8%) or
11-26
Station
Downtown Forest / LBJ / White Mockingbird Cityplace
Where
Garland Jupiter Skillman Rock
Boarded
Train?
Downtown
1.5% 1.5%
3.0%
6.0%
Garland
Forest /
1.5%
Jupiter
LBJ /
1.5%
1.5%
Skillman
White Rock
1.5%
Mockingbird
1.5%
Union
1.5%
Total
1.5% 1.5%
4.5% 1.5%
4.5%
7.5%
7.5%
7.5%
Pearl
22.4%
3.0%
4.5%
16.4%
1.5%
1.5%
10.4%
Akard
17.9%
St. Paul
th
10.4%
3.0%
7.5%
3.0%
3.0%
4.5%
3.0%
1.5%
3.0%
1.5%
1.5%
West End Union Convention 8 &
Corinth
Center
At what station will you get off the train?
(N=68)
1.5%
1.5%
Kiest
1.5%
1.5%
1.5%
1.5%
7.5%
11.9%
70.1%
Total
7.5%
1.5%
1.5%
7.5% 100.0%
7.5%
VA
Ledbetter
Not
Medical
provided
Center
BLUE LINE BOARDING AND ALIGHTING STATIONS IN-BOUND DURING AM PEAK
EXHIBIT II-16
10% at Akard, and 8% at the West End after boarding at Downtown Garland. See Exhibit II-16.
Most of the in-bound Blue Line riders (70%) during the AM Peak hours boarded at Downtown Garland. Of these, a total of 18% alighted at St. Paul,
Outbound on the Blue Line in the PM peak, riders tend to most often board at White Rock (18%)
or Mockingbird (10%), as seen in Exhibit II-17. They most often alight at Downtown Garland
(53%), LBJ/Skillman (21%) or Forest/Jupiter (17%).
II-27
EXHIBIT II-17
BLUE LINE BOARDING AND ALIGHTING STATIONS OUT-BOUND DURING PM PEAK
(N=97)
Station where Downtown
boarded train? Garland
Downtown
Garland
At what station will you get off the train?
Forest /
LBJ /
White
Cityplace
Jupiter
Skillman
Rock
Total
Pearl
West End
1.0%
Union
1.0%
2.1%
Forest /
Jupiter
2.1%
LBJ/Skillman
6.3%
2.1%
White Rock
4.2%
4.2%
Mockingbird
10.4%
Cityplace
3.1%
Pearl
4.2%
St. Paul
6.3%
1.0%
1.0%
8.3%
Akard
5.2%
2.1%
1.0%
8.3%
West End
3.1%
2.1%
3.1%
8.3%
Union
1.0%
1.0%
2.1%
1.0%
1.0%
1.0%
1.0%
Kiest
1.0%
8.3%
7.3%
1.0%
1.0%
17.7%
10.4%
1.0%
4.2%
4.2%
Morrell
Illinois
3.1%
1.0%
2.1%
1.0%
Ledbetter
1.0%
Tyler /
Vernon
1.0%
2.1%
2.1%
2.1%
5.2%
1.0%
Not
provided
5.2%
3.1%
2.1%
Total
53.1%
16.7%
20.8%
1.0%
3.1%
II-28
1.0%
1.0%
11.5%
3.1%
1.0%
100.0%
11-29
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Dr
ive
alo
ne
Dr
ive
w
/ot
he
rs
(D
Blue Line
Pa
ss
en
ge
r
ro
pp
ed
off
)
Pa
ss
en
ge
r(
pa
r
ke
d)
s
Red Line
Bu
ACCESS MODE
EXHIBIT II-18
W
alk
Bi
ke
Total
riders, 42% transferred from a bus, 24% walked, and 17% drove alone. See Exhibit II-18.
Re
fus
ed
Most Red Line riders accessed the train by walking (27%), transferring from a bus (26%), or driving alone (25%). For the Blue Line
11-30
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
was permanent.
Te
mp
or
ar
y
Blue Line
Red Line
Pe
rm
an
en
t
TYPE OF TRIP
EXHIBIT II-19
Total
No
t
Pr
ov
id
ed
behavior. Two-thirds (66%) of Red Line respondents and 69% of Blue Line respondents indicated that their use of light rail for this trip
As Exhibit II-19 shows, most respondents reported their use of DART for this particular trip was a permanent part of their travel
Those that reported this trip to be temporary tended to be respondents who were traveling for
non-work purposes, during the mid-day period.
EXHIBIT II-20
CHARACTERISTICS OF TEMPORARY RAIL USERS
CHARACTERISTIC
RED LINE
(N=300)
BLUE LINE
(N=272)
TOTAL
(N=572)
Gender
Male
66.0%
67.2%
66.5%
Female
34.0%
32.8%
33.5%
Under 24
26.0%
37.5%
31.5%
25-34
24.3%
16.2%
20.5%
35-44
23.7%
22.8%
23.3%
45-54
16.3%
14.0%
15.2%
55-64
6.0%
5.9%
5.9%
65+
3.0%
2.9%
3.0%
Refused
Household Size
1
0.7%
0.7%
0.7%
19.7%
20.2%
19.9%
2
26.3%
21.7%
24.1%
3
20.3%
26.5%
23.3%
4
19.3%
18.0%
18.7%
5+
12.3%
12.9%
12.6%
0
16.3%
24.3%
20.1%
1
29.7%
30.5%
30.1%
2
32.0%
27.9%
30.1%
3+
19.7%
15.4%
17.7%
Refused
Employment Status
Employed Full Time
2.3%
1.8%
2.1%
60.7%
57.4%
59.1%
Employed Part Time
14.0%
11.8%
12.9%
Student Full Time
15.7%
17.6%
16.6%
Student Part Time
5.0%
2.2%
3.7%
Retired
5.3%
4.4%
4.9%
Homemaker
2.7%
0.4%
1.6%
Unemployed
8.7%
12.5%
10.5%
Age
Household Vehicles
II-31
Characteristics of Temporary Rail Users (Continued)
Household Income
< $25k
32.3%
28.3%
30.4%
$25k - < $45k
21.7%
31.6%
26.4%
$45k- < $75k
19.3%
18.0%
18.7%
$75k - < $100k
11.0%
6.6%
8.9%
$100k - <$125,000
5.7%
2.2%
4.0%
$125k - <$150,000
3.0%
1.1%
2.1%
$150,000 +
2.7%
2.6%
2.6%
Income refusals
Trip Purpose
Work/work related
4.3%
9.6%
6.8%
27.7%
22.1%
25.0%
School
4.7%
3.3%
4.0%
Personal Business
8.3%
6.3%
7.3%
Recreational
28.0%
16.2%
22.4%
Visiting
7.3%
11.0%
9.1%
Return Home
20.0%
29.0%
24.3%
Other
4.0%
12.0%
8.0%
Time of Day of Use
AM Peak
10.7%
10.3%
10.5%
Mid-day
59.3%
59.6%
59.4%
PM Peak
22.0%
19.5%
20.8%
Evening
2.3%
0.7%
1.6%
Not recorded
5.7%
9.9%
7.7%
II-32
II-33
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
57d
ay
s/w
k
24d
ay
s/w
k
on
ce
aw
ee
k
tim
e
Blue Line
Fir
st
Red Line
Total
Se
ve
ra
l ti
me
s/m
th
on
ce
/m
th
HOW OFTEN MAKE THIS TRIP
EXHIBIT II-21
of respondents indicated they made the trip 2 to 4 times per week.
<1
pe
r
mt
h
Re
fus
ed
Almost half of the respondents reported they make this trip 5 to 7 days per week, as illustrated in Exhibit II-21. An additional one-fifth
11-34
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Fir
st
Tim
e
1y
ro
r le
ss
s
Blue Line
25y
ea
r
Red Line
Total
610
ye
ar
s
LENGTH OF TIME MAKING THIS TRIP
EXHIBIT II-22
report having made this trip for the last 2 to 5 years. See Exhibit II-22.
>1
0y
rs
Re
fus
ed
that they were newer riders (first trip or riding one year or less) as compared to Blue Line users. Blue Line users were more likely to
An equal number of riders (43%) reported using the rail one year or less, or 2 to 5 years. Red Line users were more likely to report
Respondents varied in the reasons why they started using light rail for this particular trip. As
shown in Exhibit II-23, the cost of gas was the main reason (42%) for Red Line respondents,
followed by less stress than driving (35%), traffic congestion (31%), and no car available (27%).
For Blue Line respondents, the main reasons included no car available (42%), cost of gas
(32%), station convenient to destination (23%), and less stress than driving (23%).
EXHIBIT II-23
WHY STARTED USING LIGHT RAIL FOR THIS TRIP
REASON
RED LINE
(N=931)
BLUE LINE
(N=925)
TOTAL
(N=1,856)
Able to read/work on train
14.4%
7.4%
10.9%
Change in carpool arrangements
1.1%
0.5%
0.8%
Construction on roads normally traveled
5.6%
1.5%
3.6%
Convenience (parking & riding rail)
22.7%
15.6%
19.1%
Cost of gas
42.2%
32.3%
37.3%
Cost of operating vehicle
18.5%
9.4%
14.0%
Cost of parking
17.3%
14.2%
15.7%
Cost of toll road
4.3%
2.1%
3.2%
Employer subsidizes transit use
9.8%
5.8%
7.8%
Faster travel by light rail over auto
26.3%
20.0%
23.2%
Less stress than driving
34.7%
22.5%
28.6%
Perception that LR is cleaner than bus
2.8%
2.3%
2.5%
Perception that LR is safer than bus
2.7%
2.5%
2.6%
Reliability of arrival time over driving
11.8%
6.9%
9.4%
Station is convenient to home
18.4%
18.9%
18.6%
Station is convenient to destination
24.3%
23.0%
23.7%
Traffic Congestion
31.1%
20.5%
25.9%
No car available
27.4%
42.3%
34.8%
Respondents varied in the reasons why they continue using light rail for this particular trip. For
Red Line respondents, the cost of gas was the main reason (41%), followed by less stress than
driving (33%), traffic congestion (30%), and no car available (26%). Blue Line respondents’
main reasons included no car available (42%), cost of gas (32%), station convenient to
destination (22%), and less stress than driving (22%). See Exhibit II-24.
II-35
EXHIBIT II-24
WHY CONTINUE USING LIGHT RAIL FOR THIS TRIP
REASON
RED LINE
(N=931)
BLUE LINE
(N=925)
TOTAL
(N=1,856)
Always used LR for this trip
5.5%
1.5%
3.5%
Change in carpool arrangements
1.1%
0.4%
0.8%
Construction on roads normally
traveled
6.1%
1.5%
3.8%
Convenience (parking & riding
rail)
19.4%
14.5%
17.0%
Cost of gas
40.9%
31.6%
36.3%
Cost of operating vehicle
18.4%
9.6%
14.0%
Cost of parking
16.8%
13.1%
14.9%
Cost of toll road
4.4%
2.1%
3.2%
Employer subsidizes transit use
8.3%
5.0%
6.6%
Able to read/work on train
10.4%
6.1%
8.2%
Faster travel by light rail over
auto
26.7%
18.3%
22.5%
Less stress than driving
33.0%
21.6%
27.3%
Perception that LR is cleaner
than bus
2.5%
1.9%
2.2%
Perception that LR is safer than
bus
2.8%
2.5%
2.6%
Reliability of arrival time over
driving
11.4%
6.7%
9.1%
Station is convenient to home
17.1%
17.4%
17.2%
Station is convenient to
destination
22.7%
21.7%
22.2%
Traffic Congestion
29.9%
19.4%
24.6%
No car available
26.3%
42.1%
34.2%
II-36
GENERAL SERVICE USAGE
In addition to details about the current trip, the survey also obtained information about what
induced the rider to begin using the rail service, how long ago that was, and why they continue
to use the rail service. The results are presented in this section, focusing primarily on reasons
by route of travel.
First, the survey asked whether the respondent had experienced specific events, which are
typically triggers for changes in travel patterns. For each case where the respondent had
experienced the event, they were asked if that change caused them to start using light rail.
Exhibit II-25 shows the proportions of respondents who had experienced specific triggers.
Of those that had, the proportions citing that trigger as causing a change in travel patterns is
also shown. For Red Line users, 51% reported changing home locations since September 2001.
Of these, about half (53%) said that the move influenced their decision to use light rail. Similarly,
48% of Red Line users changed job locations since 2001. Of those, 61% indicated that the
change in jobs was influential in the decision to start using light rail. No longer employed or no
longer in school were not influential changes in taking light rail.
For Blue Line users, a similar situation presents itself. Specifically, 49% of the Blue Line
respondents indicated that they have moved since 2001, with 50% of those reporting that the
move influenced their decision to use light rail. In addition, 45% said that they had changed job
locations, with 58% indicating that this change in job location was influential in their decision to
use the rail service.
II-37
EXHIBIT II-25
EXPERIENCES AND INFLUENCES BY LINE
Red Line
Experience
Influence
Blue Line
Experience
Influence
Changed home location
51%
53%
49%
50%
Changed job location
48%
61%
45%
58%
Changed route of travel to work
40%
52%
35%
43%
Changed work schedule
37%
50%
38%
51%
Started new job
36%
53%
33%
45%
Permanently lost use of car
26%
45%
25%
45%
Temporarily lost use of car
26%
49%
28%
47%
Started attending school
25%
34%
28%
39%
Gained use of car
22%
23%
23%
15%
No longer employed
20%
16%
24%
17%
Changed school schedule
20%
27%
24%
28%
No longer in school
19%
17%
28%
16%
Lost drivers license
17%
28%
18%
10%
II-38
There was not an overall statistically significant difference in the average number of years that
respondents from the Red and Blue Lines have used the light rail service. Roughly, one-fourth
(24%) of survey respondents across both lines were new to the DART rail system, reporting 0
years of usage. About 2% reported using the system since its start. Exhibit II-26 below provides
more detail.
Statistical tests were conducted to determine if there were differences in length of ridership
based on years of usage and peak/off-peak usage, independent of the line surveyed. In terms
of years of usage, the only statistical difference between riders using the system was in terms of
vehicle ownership: older riders (those riding for more than 5 years) tended to report owning few
vehicles on average as compared to newer riders (those riding for 5 years or less). In terms of
time of day, off-peak riders reported using rail for 2.51 years, as compared to only 2.33 years for
off-peak riders (which was also statistically different).
EXHIBIT II-26
LENGTH OF TIME USING RAIL
# Years used DART light
rail
0
Total
DART line the
respondent boarded
Red
Blue
25.2%
22.2%
Total
23.7%
1
20.5%
19.6%
20.0%
2
19.5%
20.9%
20.2%
3
9.8%
7.4%
8.6%
4
5.5%
7.0%
6.3%
5
4.2%
6.8%
5.5%
6
10.8%
13.5%
12.2%
7
1.6%
1.0%
1.3%
8
1.0%
0.3%
0.6%
9
0.6%
0.6%
0.6%
10
0.1%
0.4%
0.3%
11
1.1%
0.3%
0.7%
100.0%
100.0%
100.0%
II-39
Before using light rail, most riders (53% Red Line, 47% Blue Line) drove themselves to their
destination. They now use light rail to make the same trip.
EXHIBIT II-27
PRIOR MODE
How did you travel to this destination DART line the respondent boarded
before you started using light rail?
Red
Blue
Drove alone
52.5%
46.8%
Total
49.7%
Bus
18.9%
31.8%
25.3%
Rode as passenger & dropped off
6.8%
5.9%
6.4%
Drove w/ another passenger(s)
6.8%
2.7%
4.8%
Walk
4.5%
3.1%
3.8%
Rode as passenger & parked
1.1%
0.8%
0.9%
Bike
0.5%
0.1%
0.3%
Refused
0.2%
Total
100.0%
0.1%
100.0%
100.0%
One final question on the survey focused specifically on the use of DART to travel to special
events at the American Airlines Center. As shown in Exhibit II-28, 30% of Red Line respondents
and 20% of Blue Line respondents indicated that they use DART to access this location.
EXHIBIT II-28
USE DART TO ACCESS AMERICAN AIRLINES CENTER
Do you ever use light rail for
travel to special events at the
American Airlines Center?
DART line the respondent boarded
Red
30.2%
Blue
20.4%
Total
25.3%
No
67.7%
77.5%
72.6%
Don’t Know
1.2%
0.8%
1.0%
Refused
1.0%
1.3%
1.1%
Total
100.0%
100.0%
100.0%
Yes
II-40
Exhibit II-29 provides a summary of characteristics of those riders who use DART to access the
American Airlines Center. The characteristics were very similar regardless of line surveyed on.
Red Line users most likely to use DART to access events at the American Airlines Center
include those employed on a full-time basis (74% compared to 72% in the general survey
population) and surveyed on a work trip, with larger household sizes, more household vehicles,
and higher incomes.
Blue Line users most likely to use DART to access events at the American Airlines Center
include those employed on a full-time basis (69% compared to 72% in the general survey
population) and surveyed on a work trip, with larger household sizes, more household vehicles,
and higher incomes. In addition, Blue Line respondents age 35-44 also were more likely to
indicate traveling to the American Airlines Center using DART (34% compared to 29% overall).
EXHIBIT II-29
CHARACTERISTICS OF AMERICAN AIRLINES CENTER USERS
CHARACTERISTIC
RED LINE
(N=281)
BLUE LINE
(N=189)
TOTAL
(N=470)
Gender
Male
60.4%
66.7%
62.9%
Female
39.6%
33.3%
37.1%
Under 24
17.8%
22.2%
19.6%
25-34
23.1%
18.0%
21.1%
35-44
26.0%
33.9%
29.1%
45-54
19.9%
15.9%
18.3%
55-64
11.0%
8.5%
10.0%
65+
2.1%
1.6%
1.9%
1
15.7%
14.3%
15.1%
2
30.6%
31.7%
31.1%
3
22.8%
18.5%
21.1%
4
18.5%
19.0%
18.7%
5+
11.7%
15.9%
13.4%
Age
Household Size
II-41
Characteristics of American Airlines Center Users (Continued)
Household Vehicles
0
13.5%
18.0%
15.3%
1
25.3%
28.0%
26.4%
2
39.9%
34.4%
37.7%
3+
19.6%
18.5%
19.1%
Refused
Employment Status
Employed Full Time
1.8%
1.1%
1.5%
74.4%
69.3%
72.3%
Employed Part Time
7.1%
12.2%
9.1%
Student Full Time
11.7%
14.3%
12.8%
Student Part Time
5.7%
4.8%
5.3%
Retired
3.9%
5.8%
4.7%
Homemaker
1.4%
0.5%
1.1%
Unemployed
Household Income
< $25k
6.0%
4.2%
5.3%
22.4%
25.4%
23.6%
$25k - < $45k
19.2%
29.6%
23.4%
$45k- < $75k
22.1%
24.3%
23.0%
$75k - < $100k
13.9%
10.6%
12.6%
$100k - <$125,000
10.3%
3.2%
7.4%
$125k - <$150,000
4.6%
1.6%
3.4%
$150,000 +
2.5%
1.1%
1.9%
Income refusals
Trip Purpose
Work/work related
5.0%
4.2%
4.7%
33.8%
25.9%
30.6%
School
5.0%
2.6%
4.0%
Personal Business
7.5%
6.3%
7.0%
Recreational
19.9%
16.4%
18.5%
Visiting
3.2%
9.5%
5.7%
Return Home
29.2%
32.3%
30.4%
Not recorded
Length of Time Making
this Trip
First Time
1.5%
6.9%
3.6%
10.3%
4.2%
7.9%
1 year or less
43.8%
41.8%
43.0%
2-5 years
41.6%
50.8%
45.3%
6-10 years
2.8%
2.1%
2.6%
Not recorded
1.5%
1.0%
1.3%
II-42
III. LRT IMPACT ON TRANSPORTATION NETWORK
With any rail project comes the need to demonstrate the benefits of the rail investment on the
surrounding transportation network. The Dallas area continues to struggle with severe
congestion and air quality issues. The North Central Texas Council of Governments (the
region’s Metropolitan Planning Organization) and transportation providers like Dallas Area
Rapid Transit (DART) devised a multi-pronged approach that includes the introduction of modal
options into as many congested corridors as possible.
In this section of the report, the survey results are summarized and discussed within the context
of the impact of this light rail service on the regional transportation infrastructure. This is
followed by a similar discussion using available non-survey data sources. The section ends with
general conclusions and comments on the findings.
SURVEY SUMMARY
Although this survey was not designed to provide clearly measurable information on the impacts
the LRT extensions have had on the surrounding transportation network, there are inferences
that can be made from the data. The trends and tendencies gleaned from the data can be used
to inform planners and decision maker’s investigations of future LRT extensions. Behaviors and
characteristics of current riders can be used to inform design and consideration of new LRT
corridors in the region.
As evidenced in this survey data, the users of the Red and Blue Line extensions were
predominantly previous vehicular commuters. Red Line users were predominantly male (61%)
and had access to at least one vehicle per household. Blue Line users included 77% with
access to at least one vehicle. When asked how they traveled to their destination prior to using
LRT, the majority of Red Line users arrived by car, with 53% driving alone, and 15% arriving as
III-1
a personal auto passenger. Although the Blue Line had a higher number of former bus patrons
among the respondents, 47% drove alone and 9% arrived as a car passenger. Combined, this
results in the majority of Blue Line patrons being former car users as well.
One logical benefit of converting personal auto commuters to rail commuters is the savings in
terms of air quality (measured in emissions saved) and transportation system delay realized
when a vehicle is removed from the roadway system. While the survey data collected for this
effort is limited in its usefulness for measuring specific savings and/or impacts on the system,
inferences can be made from some of the responses. For example, the majority of Red Line
users indicated their trip purpose as home to work or vice versa. On average, in the Red Line
corridor, a home-based work trip is reported in the 2000 Census as being 25 to 30 minutes in
length. When combined with an average speed assumption of 40 mph, this represents
approximately 20 miles. This translates into a per-passenger round trip savings of 40 vehicle
miles of travel (VMT) per day, or 10,400 per year (assuming 260 work days per year).
Accumulated over all riders along the route who were former single occupant vehicle users, this
value becomes a measurable benefit in terms of VMT removed from the roadway system and
vehicle emissions saved. Similar comparisons can be made for the Blue Line patrons, although
there was greater variation in the reported origins of travel in the Blue Line survey.
Another interesting observation from the survey data relates to the reasons given as to why the
rider began using rail service. For the Red Line, the majority of users reported changing home
and/or job locations since the LRT extension opened for service, prompting them to become rail
riders. This kind of information can be very useful for planners of future rail extensions and
station locations.
It also speaks to another very important observation from the survey – the benefits of transitoriented development. In order to encourage rail transit patronage, the convenience factor of
using rail service to access more residential and employment locations is key. Stations located
III-2
within close proximity (accessible via walking or feeder bus) to residential and employment
locations will result in higher patronage. Survey information, such as that reported here, helps to
emphasize the importance of the development decisions made by local policy makers in
creating a transit friendly/transit oriented community. As evidenced by the survey respondents
who moved within reasonable proximity of the rail service, providing the transit service is not
enough. There must be additional incentives to cause them to become riders.
Blue Line users have a higher proportion of riders with no vehicle available to them (42%). This
is also supported by the fact that the majority of Blue Line riders accessed the train by bus, as
opposed to driving or walking. Riders such as these are important to the system as they sustain
the overall patronage, but do not represent as great an impact or benefit on the transportation
system since they were most likely not driving prior to rail service, but riding the bus. The
benefits reported above from removing single occupant vehicle trips are not as prevalent for the
Blue Line for this reason. However, the modal alternative is still an important part of the system.
The majority of both the Red and Blue Line respondents indicated their switch to rail to be a
permanent one. This is significant as initial ridership often jumps for a new rail service as
patrons are “investigating” the new mode, or ridership increases during periods of high gas
prices or other system anomalies. The indication of permanence by the patrons can be
interpreted as a benefit on the transportation system; regardless of the initial reasons, the new
transit riders appear to have “converted” to transit. This is a useful observation for planners and
analysts who use transit ridership as a commitment for air quality improvements.
ADDITIONAL DATA SOURCES
In order to do more extended comparisons of the impacts of the LRT extensions on the
transportation system, additional data sources were sought outside the survey conducted for
this project. DART conducted a Before and After Study of the North Central (Red Line) LRT
III-3
Extension during 2005, in accordance with the Federal Transit Administration (FTA) Final Rule
on Major Capital Investment Projects. This rule requires all sponsors seeking Full Funding Grant
Agreements for New Starts projects must submit a plan for the preparation of a Before and After
Study. The report generated for this effort (North Central LRT Extension July, 2005 Preliminary
Review Draft Before and After Study), measures a variety of impacts as a result of the LRT
extension. The transportation system impacts contained in the report were reviewed for their
relevance to this project. There were no additional data sources located for the Blue Line
extension, but a summary of the Red Line impacts from the Before and After report are
discussed below.
One important measure of transportation system impacts is the reduction in travel time provided
by the LRT extension to travelers within the corridor. The Red Line extension in the North
Central Corridor was estimated to account for 873,104 hours annually in travel-time savings.
This translates into an estimated $10,215,321 in savings annually. Prior to introduction of LRT,
the route to the Central Business District (CBD) was congested and circuitous (if by bus),
resulting in the time-saving benefits shown here.
Roadway congestion is a critical issue for the corridor paralleling the Red Line, U.S. 75 most
specifically. Indicating another benefit of the LRT extension, traffic reductions were projected to
be approximately 900 vehicles per day at Forest Lane, 1,200 vehicles per day at Arapaho Road
and 700 vehicles per day at Park Boulevard. Although the traffic reduction is beneficial, the
extensive ADT (average daily traffic) in the North Central Corridor results in it representing less
than one percent of the total traffic in the corridor. Nonetheless, the LRT extension does provide
an alternative for those commuters bound for the Dallas CBD.
The parallel arterial street network along the Red Line extension was also expected to
experience reductions in ADT, but again given the extensive arterial street ADT, the reductions
were estimated to be less than one percent of the daily levels.
III-4
Exhibits III-1 to III-4 show the parallel freeway and arterial street ADT for roadways in the vicinity
of the Red Line extension in 2004, after the extension was open for operation. This information
is included to indicate the magnitude of the roadway traffic still remaining in the North Central
Corridor and to emphasize the importance of providing a modal alternative for travelers in this
area. The tables following the 2004 observed ADT contain the model estimates of ADT under
the No-Build scenario. Review of the previous No-Build estimates for parallel freeway and
arterial street ADT indicate significant increases in ADT, even with the introduction of the LRT
extension. As noted at the outset of this chapter, a multi-pronged approach is required to
address the transportation issues in congested corridors such as this.
EXHIBIT III-1
FREEWAY ADT IN THE NORTH CENTRAL CORRIDOR 2004
Intersection
Average Daily Traffic
North Central Expressway (U.S. 75)
Forest Lane
207,000
LBJ Freeway
242,000
Arapaho Road
252,000
Park Blvd.
221,000
LBJ Freeway
Preston Road
278,000
U.S. 75
226,000
Abrams
189,000
S.H. 190 Freeway
Independence Parkway
96,600
Jupiter Road
57,300
Source: NCTCOG, 2005
III-5
EXHIBIT III-2
ARTERIAL ADT IN THE NORTH CENTRAL CORRIDOR 2004
Intersection
Preston Road at Forest Lane
Average Daily Traffic
35,648
Skillman at Northwest Highway
30,493
Greenville Avenue at Royal Lane
30,461
Greenville Avenue at Spring
Valley
17,000
Coit Road at LBJ Freeway
54,373
Plano Road at Arapaho
36,000
Plano Road at Park Boulevard
19,077
Greenville at Campbell
9,500
Belt Line at Jupiter
33,900
Jupiter at Arapaho
35,500
Belt Line at Preston Road
26,405
Coit Road at Parker
49,453
Source: NCTCOG
EXHIBIT III-3
ESTIMATED ADT IN THE NORTH CENTRAL CORRIDOR-NO-BUILD SCENARIO
Intersection
Average Daily Traffic
North Central Expressway (U.S. 75)
Forest Lane
193,000
LBJ Freeway
184,200
Arapaho Road
177,800
Park Blvd.
150,800
LBJ Freeway
Preston Road
239,600
U.S. 75
262,600
Abrams
200,900
S.H. 190 Freeway
Independence Parkway
86,100
Jupiter Road
59,400
Source: NC Corridor LRT Extension
III-6
EXHIBIT III-4
ESTIMATED ADT IN THE NORTH CENTRAL CORRIDOR-NO-BUILD SCENARIO
Intersection
Preston Road at Forest Lane
Average Daily Traffic
22,000
Skillman at Northwest Highway
32,500
Greenville Avenue at Royal Lane
49,800
Greenville Avenue at Spring Valley
35,000
Coit Road at LBJ Freeway
98,000
Plano Road at Arapaho
23,600
Plano Road at Park Boulevard
16,700
Greenville at Campbell
59,000
Belt Line at Jupiter
26,300
Jupiter at Arapaho
28,000
Belt Line at Preston Road
29,800
Coit Road at Parker
31,300
Source: NC Corridor LRT Extension FEIS
CONCLUSIONS
When reviewed in light of the impact of light rail on the regional transportation network, the
survey results suggest three important findings:
1. The availability of rail as a travel mode, combined with a change in home or work
location, has led many respondents to change from auto to rail as their travel mode.
This conversion to rail has resulted in emissions reductions, as well as corresponding
reductions in transportation system delays and VMT.
2. A majority of Red Line users reported changing their home or work location prior to
changing their travel mode to rail. This speaks to the potential benefits of transit-friendly
or transit-oriented development.
It also emphasizes the importance of development
decisions made by local policy makers in creating the rich, mixed-use communities.
Providing the transit service in itself is not enough, but with the additional “convenience”
of retail and service amenities, rail can have a positive impact.
III-7
3. The Blue Line users ride largely due to the lack of vehicle availability. Such riders are
important to the system as they sustain overall patronage, but do not represent as great
an impact or benefit on the transportation system since they were most likely not driving
prior to the rail service, but riding the bus. However, the increased spatial mobility range
that comes with the rail service (as compared to transit service) can open doors to these
riders in terms of increased access to job opportunities, medical services, etc.
In sum, the survey results suggest that the expanded LRT service has had a positive impact
in the region, through induced mode shifts from auto to rail and related reductions in
emissions and VMT, as well as increased mobility for regional residents.
III-8
IV. APPENDIX A: STUDY METHODS
SAMPLE PLAN
In order to determine the appropriate sample size for the study, NCTCOG, DART and NuStats
met to discuss the project needs. During this meeting, it was agreed that the sample plan for the
DART LRT Expansion Impact Analysis Study would require a minimum of 900 completed
questionnaires each on DART’s Red and Blue light rail lines for a total sample size of 1,800
complete and usable pieces of sample. These surveys would represent weekday and weekend
service, thus the goal of 900 completed surveys per line was portioned to approximate the
relative split between weekday and weekend ridership with a goal of 660 completes from
passengers riding during weekdays and 240 completes from passengers using weekend
service.
Because the study was designed to assess the travel patterns of passengers using the
extended portion of both lines that opened in 2002, data collection was conducted only between
the Parker Road station and Walnut Hill station (Red Line) and Downtown Garland station and
White Rock station (Blue Line). Passengers eligible to complete the survey included those age
16 or older that boarded or alighted at any station between the two end points of each line (i.e.,
the new service).
DATA COLLECTION SCHEDULE
Data collection was conducted over a 13-day period, beginning May 6 through May 12, and
continuing May 17 through May 22. For budgeting efficiencies, a four-day break was
purposefully scheduled so the survey team’s work hours did not exceed 40 hours during a
seven-day period.
IV-1
Data was collected on weekdays and weekends from 7:00 a.m. until 7:00 p.m. to cover all
service time periods (AM peak, mid-day, PM peak and evening). Workday schedules for the
interviewers were divided into two eight-hour shifts (7:00 a.m. to 4:00 p.m. with an one hour
break for lunch and 11:00 a.m. to 7:00 p.m. with an one hour break for lunch) and alternated to
ensure data collection activities covered a 12-hour service period. Weekend data collection
occurred between 7:00 a.m. until 1:00 p.m. on Saturdays and between 1:00 p.m. and 7:00 p.m.
on Sundays. This methodology allowed for data to be collected throughout the weekend hours
to cover all time periods.
STAFFING
The surveyor team consisted of six individuals provided by StaffMark, a national temporary
employment agency with a local Dallas office and on-site supervision by NuStats staff. The
surveyor team was selected based on the following skills and personality traits.
Outgoing and friendly personality
Able to walk around the rail car while the train was in motion
Clear, understandable verbal communications skills
Legible handwriting
Former or current transit user
Professional appearance
Mature and able to work with minimal supervision.
IV-2
NuStats senior managers provided on-site supervision. This included accompanying the survey
team during all surveying periods to ensure data was collected according to approved
methodology. NuStats on-site supervisors also reviewed completed questionnaires for accuracy
and to assist surveyors logistically (facilitating new team assignments as the end point on a line
was reached, providing supplies, coordinating daily work and break schedules).
SURVEYOR TRAINING
Surveyor training was comprised of three parts: introduction, mock interviews, and the initial
assignment. The introductory training was conducted in a classroom environment. Surveyors
were required to attend a three-hour training session prior to commencing any data collection
activities. The training session was designed to:
Inform the team about the purpose of the study
Thoroughly familiarize surveyors with the survey instrument
Instruct surveyors about appropriate data collection methodology
Provide surveyors with work schedule information and work rules.
Upon conclusion of the training session, surveyors practiced conducting mock interviews with
each other. Surveyors were paired together and the data collection manager worked with each
team to ensure questions were being asked correctly and data was being captured accurately.
Once training was complete, the NuStats data collection manager monitored each surveyor
during his or her first few live interviews in order to ensure data was being collected according to
approved methodology procedures. Once the data collection manager felt the surveyors were
able to work independently, spot monitoring was performed throughout each work shift.
IV-3
FOCUS GROUP AND PILOT TESTING
Prior to developing the survey instrument, a series of focus group sessions were conducted with
Red and Blue Line passengers who board or alight at one of the stations comprising the
extended portion of the rail lines. The focus group sessions, conducted March 15, 2005,
provided valuable input into the questionnaire design, question ordering and possible question
responses, particularly with regard to identifying factors that influence mode shift and continuing
patronage. The focus group sessions also examined methods for obtaining respondent
participation through discussion of how interviewers should present themselves and introductory
remarks. Upon conclusion of the focus group sessions, results were reviewed and served as a
foundation for development of the draft survey instrument.
Once the draft survey instrument was complete, NuStats conducted a pilot test on April 28,
2005. The purpose of the pilot test was to assess the data collection methods, respondent
comprehension of the questions in the survey, the length of the survey, and item non-response.
Prior to beginning the pilot study, NuStats’ data collection manager provided a briefing of the
data collection process and reviewed the survey instrument with two surveyors from a local area
temporary employment agency. Following the briefing, the surveyors conducted surveys on both
the Red Line and Blue Line (on board the trains between the stations that are part of the
expansion).
Field staff completed 41 surveys from passengers on the Red and Blue light rail lines. Results of
the pilot study revealed that minor refinements to questions and ordering of the questions were
required as detailed in the Pilot Results and Recommendations for Full Study Technical
Memorandum (Attachment 1). As documented therein, the pilot results included a finding that
the data collection methodology was acceptable and no changes in this area were
recommended for the full study. However, some changes were made to the procedures and
IV-4
survey instrument as a result of the pilot study effort. An emphasis was placed on the surveyors
to accurately capture the information of the ONE-WAY trip. Originally, many survey participants
were giving information coinciding with their round trip as opposed to just this single leg trip.
Regarding the survey instrument, all stations were added in list form and designated with a
check mark by the surveyor. This was added due to the fact that station names were not always
being captured clearly and accurately. Also, a few additional code options were added to
questions thus minimizing the number of open-ended responses. For example, “No car
available” was added to question 15, “Why do you continue to use light rail for this trip rather
than your former travel method?”
SURVEY INSTRUMENT
The questionnaire, as shown in attachment 2, consisted of 24 questions organized into four
general categories:
Travel history (length of time using light rail service, mode of access, frequency of use,
etc.)
Trip origin/destination (boarding station, alighting station, origin, destination, trip
purpose)
Influences for using rail service
Rider demographics.
All questions were pre-coded with the exception of origin and destination questions, which
captured the exact address or cross streets, city and zip code data.
NuStats designed the questionnaire to be scanned to facilitate data entry and data file creation.
IV-5
DATA COLLECTION METHODOLOGY
Data collection methodology involved random intercept interviewing of passengers age 16 or
older on-board the recent extension of the Red and Blue light rail lines. Only passengers who
were on board the Red Line, riding between the Parker Road station and Walnut Hill station, or
Blue Line, riding between the Downtown Garland station and White Rock station, were eligible
to participate in the study.
Surveyors were instructed to approach every third passenger and invite the passenger to
participate in the study. This procedure helped to eliminate selection bias that can occur through
self-selection processes. Passengers who declined to participate in the study were politely
thanked for their time and tallied as a refusal for response rate calculation purposes.
On trains consisting of two cars, three surveyors were assigned to each car. On trains with three
cars; two surveyors were assigned to interview passengers riding each car. Surveyors were
instructed to exit the train each time they reached one of the end study point stations and board
the next train traveling in the opposite direction to continue surveying efforts.
DATA ENTRY AND DATA CLEANING
Data entry was conducted using scanning technology in order to minimize human error resulting
from traditional data entry methods. The scanning process involved scanning batches of
approximately 100 questionnaires to produce an image file of the documents. Data results
derived from the image files were individually reviewed and verified by comparing the scanned
image to the data contained in the data file. Text data (primarily origin and destination address
information) was reviewed for the purpose of correcting misspellings and verifying that the
scanner correctly read numeric data. The data file developed from scanned documents was
maintained unaltered for comparison purposes.
IV-6
Prior to the creation of the final database, a Data Items Matrix and Data Dictionary were created
based on the questionnaire and scanning program. The Data Items Matrix and Dictionary
identified variable labels, response labels, variable descriptions, data types, field widths, code
sets, skips, and exact question wording, as it appeared in the questionnaire.
The original database was duplicated and data contained in the database copy were checked
for integrity. Various edit routines were programmed to check the consistency of data and to
identify reporting, scanning or entry errors. Routine edit checks were conducted to examine
questionnaire responses for reasonableness and consistency across items. These included
such items as:
Response Checks
Checking for proper data skips and patterns of answering questions consistent with prior
answers.
Checking for realistic responses (e.g., age and employment category).
Checking for high frequency of item non-response (missing data).
Range Checks
Verifying that all categorical values were within range.
Identifying outliers in continuous variables (variables that represent a continuum of
values and do not have a code set).
IV-7
Open-ends Preparation (non-categorical, text variables)
Reviewing text variables associated with an “Other” type category and recoding text
responses that belonged to one of the categories in the response list/code set.
Correcting text response spelling and typographical errors.
Logic Checks
Verifying the logical consistency of responses. Performing data cleaning consistency
checks that were not possible to include in the Scanning program.
Other Standard Checks
Checking that the total number of records in the data file equaled the total number of
scanned questionnaires.
Correcting or removing duplicates (duplicate unique identifier).
Preparing multiple-response variables (if any) by splitting them into the variables
specified by the Matrix.
Re-verifying data entry for 20% of the total questionnaires collected.
Following completion of the routine edit checks, a series of customized automated and manual
checks were performed. These checks were based on specific questions in the survey
instrument (identified by question number) and included:
Verifying the line, direction, date, and time (administrative details) were complete.
Confirming the length of time making “this trip” on light rail is equal to or less than the
length of time the respondent has used light rail.
Confirming the respondent did not board and alight at the same station.
Confirming the respondent did not report a trip that began at home and ended at home.
IV-8
GEOCODING
The survey instrument contained four location types: boarding station, alighting station, trip
origin, and trip destination. Each of these data had a slightly different strategy for conducting the
geocoding processes.
Trip Origin and Destination
Geocoding of the trip origin and destination consisted of two-stages. An automated batch run
was first attempted in order to successfully geocode all of these locations. The batch run
attempted to match exact addresses or cross-streets obtained from respondents to a street
coverage file for the DFW metroplex provided by NCTCOG. Addresses or cross-streets
matching the coverage file were assigned an X/Y coordinate and a value of “M” for matched,
and placed in the “AV_STS” field. Addresses or cross-streets not matched during the batch run
were flagged with an “AV_STS” value of “U” for unmatched, and passed to the next stage of
geocoding.
During the next stage, addresses were researched using a series of resources, including
switchboard.com, zip2.com, and DeLorme Street Atlas USA (mapping software). Addresses
that were matched to an exact address or cross-streets during this stage were assigned an X/Y
coordinate and an “AV_STS” of “M”. Addresses not geocoded were not assigned an X/Y
coordinate, and were given the “AV_STS” of “U”.
IV-9
Rail Station On / Off
The survey instrument contained 34 pre-geocoded rail station locations. Therefore, only a
minimal effort was needed to geocode cross-streets listed as “other” and the same codes apply
for “AV_STATUS” as above.
Geocoding Quality Control
Once geocoded, records were subjected to series of quality control checks, including:
Visual Quality Control Check. Geocoding was verified for location accuracy. Since this
study was comprised of 3 counties (Collin, Dallas and Tarrant), a visual check was done
by querying approximately 10% of the geocoded records and checking one by one for
visual placement accuracy.
Zip Code Comparison. Using the zip code coverage, a shape-to-shape join on the
address data file and the zip code coverage was performed. This “join” attached the
geocoded zip code number to the data file, allowing a comparison to the zip code given
by the respondent. Those two zip codes were compared and differences were selected
and researched to ensure the highest accuracy of geocoding.
Geocoding Results
Exhibit IV-1 identifies the final geocode match rate for each of the four location types. Match
rates were calculated as a percentage of matched to unmatched address records. Blank
records (where not data was provided by the respondent) and locations outside the study area
are shown for informational purposes only and not used to calculate match rate.
IV-10
EXHIBIT IV-1
GEOCODING MATCH RATE
ADDRESS TYPE MATCHED UNMATCHED
BLANK
OUT OF
AREA
TOTAL
MATCH
RATE
Station On
1,780
76
0
0
1,856
96%
Station Off
1,784
72
0
0
1,856
96%
Origin
1,707
115
2
32
1,856
94%
Destination
1,664
158
0
34
1,856
91%
RESPONSE RATE
The system-wide response rate for the DART Light Rail Expansion Analysis Impact Survey was
70% percent. The response rate was calculated based on the number of interviews conducted
with eligible respondents compared to all respondents with whom an interview was attempted.
The formula for calculating response rate is:
Complete/Partial Questionnaires
Response Rate (%) =
Questionnaires Distributed to Eligible Respondents*
*For the purposes of this study, an eligible respondent was defined as an adult male or female, age
16 or older.
A total of 2,633 intercept interviews were attempted with eligible respondents meeting the
criteria described above, resulting in 1,856 completed surveys. The project goal was 1,800
surveys, so the final data set contains 103% of that goal. The response rate was 70%,
determined by dividing 1,856 completed surveys by all attempted surveys (1,856 completed
surveys plus 777 attempted-but-not-completed surveys).
IV-11
V-1
At what 8th & Akard Arapaho Bush Cedars Cityplace Convention Dallas Downtown Forest Galatyn Hampton LBJ / Lovers Mockingbird
station did Corinth
Center Turnpike
Center
Zoo
Plano
Lane Park
Central Lane
you board
this train?
8th &
0.1%
0.1%
Corinth
Akard
0.3% 0.5%
0.1% 0.1%
Arapaho 0.1% 0.4%
0.3%
0.1%
0.5% 0.4%
0.2%
0.5%
Center
Bush
0.4%
0.1%
0.2%
0.2% 0.2% 0.1%
0.1% 0.4%
0.3%
Turnpike
Cedars
0.1%
0.1%
Cityplace
0.4% 0.6%
0.2%
0.1%
Convention
Center
Dallas Zoo
0.1%
0.1%
Downtown 0.1% 0.2%
0.2%
0.2% 0.1%
0.2%
1.2%
Plano
Forest lane
0.2%
0.1%
0.2%
0.1%
0.2%
Galatyn
0.1%
0.1% 0.1%
0.1%
0.5%
Park
Hampton
0.1%
0.1%
0.2%
LBJ/Central
0.1% 0.1%
0.1%
0.2%
0.1%
Lovers
0.1% 0.1%
0.3%
0.1%
Lane
Mockingbird
0.4% 0.3%
0.8% 0.2%
0.3%
Park Lane
0.2% 0.1%
0.1%
0.1% 0.4% 0.1%
0.1%
0.3%
Parker
0.1% 2.0% 1.1% 0.3% 1.0% 1.4%
0.1% 1.9%
1.4% 1.5%
0.4%
0.6% 1.2%
2.4%
Road
Pearl
0.1%
0.1%
0.1%
Spring
0.4% 0.1% 0.4%
0.1%
0.5%
0.1%
0.1%
Valley
St. Paul
0.5%
Union
0.1% 0.3% 0.2%
0.1%
0.1%
Walnut Hill
1.3% 1.1%
0.2%
0.9% 1.1%
0.2%
0.2%
West End
0.3% 0.2%
0.4% 0.1%
Westmorela
0.3%
0.1%
nd
Refused 0.1%
0.4% 0.1% 0.1%
0.1% 0.3%
0.2%
Total
0.5% 3.7% 5.6% 5.0% 1.1% 2.6%
0.1% 2.4%
6.7% 5.2% 0.5%
0.4%
2.3% 2.3%
6.0%
0.2%
0.1% 0.8%
0.1% 0.1% 0.3%
1.0%
2.8% 20.0 3.9%
%
0.3%
3.9%
0.2%
1.0%
0.2%
0.1%
0.1%
0.2%
0.4%
1.1% 0.1%
0.9%
1.0%
2.3%
1.4%
0.5%
0.1% 3.7%
0.1% 2.7%
0.1% 0.4%
0.1%
0.1%
1.0% 0.1%
0.4%
1.3%
0.4% 0.1%
0.4% 0.2% 0.4%
0.2%
1.0%
0.1%
0.1%
0.1%
0.1%
0.2%
0.2%
1.5% 0.1%
0.5% 0.9%
0.3% 0.1% 0.4%
0.1%
Spring
Valley
0.4%
Park Parker Pearl
Lane Road
At what station will you get off the train?
0.1%
4.1%
3.0%
0.3%
0.4%
0.2%
St. Paul
0.2%
0.1%
0.1%
Tyler/
Vernon
RED LINE RESPONDENTS’ BOARDING AND ALIGHTING LOCATIONS
EXHIBIT A-1
V. APPENDIX B: BOARDING AND ALIGHTING LOCATIONS BY LINE
0.3%
2.8%
0.1%
1.2%
0.1%
0.1%
0.1%
0.1%
0.3%
0.4%
Union
0.1% 0.3%
2.7% 12.0
%
0.1%
0.1% 0.6%
0.2%
1.4% 6.5%
0.1%
0.2%
0.3%
0.2% 1.4%
0.2%
0.2% 1.0%
0.6% 1.0%
0.1%
1.2% 0.1%
0.8%
0.1% 0.1%
0.1%
0.1%
2.0%
1.6%
9.8%
4.1%
1.1%
1.4%
3.3%
3.3%
2.9%
33.2%
0.4%
1.9%
1.2%
2.4%
1.6%
0.8%
6.0%
0.5%
2.8%
0.2%
5.1%
2.9%
6.9%
0.8%
Total
3.7%
2.0% 100.0%
0.1%
0.2%
1.1%
0.4%
0.2%
Walnut West Westmore Other Refused
Hill
End
land
V-2
8th & Corinth
Akard
Cedars
Cityplace
Convention
Center
Downtown
Garland
Forest/Jupiter
Illinois
Kiest
LBJ/Skillman
Ledbetter
Mockingbird
Morrell
Pearl
St. Paul
Tyler/Vernon
Union
VA Medical
Center
West End
White Rock
Refused
Total
0.4%
0.1%
0.1% 0.5%
0.2% 0.1%
0.1%
0.7% 4.4%
0.2%
0.1%
0.3% 3.0%
0.4%
0.1%
0.1%
0.1%
2.7%
0.4%
1.5%
0.5%
0.3%
0.1%
1.0%
0.4%
0.1%
0.2%
0.2%
0.7% 0.2% 0.3%
0.8%
0.1%
0.2%
0.2%
0.1%
0.1%
0.5%
0.3%
1.3%
1.0%
0.7%
8.1% 1.0% 0.8%
0.7%
4.6%
2.8%
1.3%
26.2%
2.2%
2.6%
0.9%
12.2%
0.1%
1.0%
0.3%
0.2%
0.4%
0.2%
2.4%
0.2%
0.1%
0.8%
0.2%
0.3%
1.2% 0.8% 0.3%
0.1%
0.1%
0.1%
0.4%
0.1%
1.1%
0.3%
0.5%
2.0%
1.3%
2.4%
0.1%
2.4%
1.8%
0.2%
0.8%
0.2%
2.0%
0.3%
1.3%
0.0%
0.0%
0.1%
0.0%
1.6%
1.1%
0.2%
0.0%
0.0%
0.1%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
4.4%
0.1%
0.1%
0.5%
2.6%
0.9%
0.1%
0.1%
0.2%
0.3% 2.9%
0.1% 0.5%
0.2% 2.1%
4.6%
0.1%
0.1%
0.2%
3.4%
0.7%
0.1%
Convention Downtown Forest/
LBJ/
Mocking
At what station did 8th &
Garland Jupiter Illinois Kiest Skillman Ledbetter bird
Morrell Pearl St. Paul
you board this train? Corinth Akard Cedars Cityplace Center
At what station will you get off the train?
0.1% 2.2%
0.2%
0.1%
0.1%
0.1% 1.0% 0.1%
0.4% 0.2%
1.0% 15.9% 5.1%
0.1%
0.4%
3.5%
0.5%
1.8%
Total
1.0%
8.4%
0.4% 9.5%
0.2% 4.2%
4.6% 100.0%
3.3% 38.4%
0.3% 7.5%
0.4%
1.1%
0.1% 9.0%
3.3%
3.0%
0.5%
0.1% 3.2%
2.2%
0.3%
0.1% 1.5%
West White
End Rock Refused
0.0%
0.1%
0.8% 10.8% 2.3%
0.1% 1.6% 0.7%
0.1%
0.1%
2.1% 1.0%
0.2%
0.1%
VA
Medical
Union Center
1.6%
0.1% 0.3%
Tyler/
Vernon
LINE RESPONDENTS’ BOARDING AND ALIGHTING LOCATIONS
EXHIBIT A-2 BLUE
VI. APPENDIX C: SURVEY INSTRUMENT
VI-1
VI-2
VI-3
NCTCOG Executive Board 2005-2006
President
Wayne Gent
County Judge, Kaufman County
Director
Mike Cantrell
Commissioner, Dallas County
Director
Bill Blaydes
Councilmember, City of Dallas
Director
Bobby Waddle
Mayor Pro Tem, City of DeSoto
Vice President
Oscar Trevino
Mayor, City of North Richland Hills
Director
Tom Vandergriff
County Judge, Tarrant County
Director
Pat Evans
Mayor, City of Plano
General Counsel
Jerry Gilmore
Secretary-Treasurer
Chad Adams
County Judge, Ellis County
Director
Chuck Silcox
Councilmember, City of Fort Worth
Director
John Murphy
Mayor Pro Tem, City of Richardson
Past President
Bob Phelps
Mayor, City of Farmers Branch
Director
Bobbie Mitchell
Commissioner, Denton County
Director
Greg Hirsch
Councilmember, Town of Addison
Executive Director
R. Michael Eastland
Regional Transportation Council 2005-2006
Wendy Davis, Chair
Councilmember, City of Fort Worth
Cynthia White, Vice Chair
Commissioner, Denton County
Oscar Trevino, Secretary
Mayor, City of North Richland Hills
Terri Adkisson
Board Member
Dallas Area Rapid Transit
Bill Blaydes
Councilmember, City of Dallas
Ron Brown
Commissioner, Ellis County
Maribel Chavez, P.E.
District Engineer
Texas Department of Transportation,
Fort Worth District
J. Jan Collmer
Board Member
Dallas/Fort Worth International Airport
Bob Day
Mayor, City of Garland
Maurine Dickey
Commissioner, Dallas County
Charles Emery
Chairman
Denton County Transportation Authority
Herbert Gears
Mayor, City of Irving
Paul Geisel
Chair
Fort Worth Transportation Authority
Bill Hale, P.E.
District Engineer
Texas Department of Transportation,
Dallas District
Roger Harmon
County Judge, Johnson County
Jack Hatchell, P.E.
Commissioner, Collin County
John Heiman, Jr.
Councilmember, City of Mesquite
Kathleen Hicks
Councilmember, City of Fort Worth
Ron Jensen
Councilmember, City of Grand Prairie
Pete Kamp
Councilmember, City of Denton
Linda Koop
Councilmember, City of Dallas
Ken Lambert
Deputy Mayor Pro Tem, City of Plano
Kenneth Mayfield
Commissioner, Dallas County
Steve McCollum
Councilmember, City of Arlington
Becky Miller
Mayor, City of Carrollton
Jack Miller
Vice Chair, North Texas Tollway Authority
Rich Morgan
Citizen Representative, City of Dallas
John Murphy
Mayor Pro Tem, City of Richardson
Surface Transportation
Technical Committee
Renee Lamb, Chair
Mel Neuman
Mayor, City of Mansfield
Mike Nowels
Deputy Mayor Pro Tem
City of Lewisville
Ed Oakley
Councilmember, City of Dallas
Chuck Silcox
Mayor Pro Tem, City of Fort Worth
Grady Smithey
Mayor Pro Tem, City of Duncanville
John Tatum
Citizen Representative, City of Dallas
Maxine Thornton Reese
Councilmember, City of Dallas
Carl Tyson
Councilmember, City of Euless
Marti VanRavenswaay
Commissioner, Tarrant County
Bill Whitfield
Mayor, City of McKinney
B. Glen Whitley
Commissioner, Tarrant County
Kathryn Wilemon
Councilmember, City of Arlington
Michael Morris, P.E.
Director of Transportation, NCTCOG