DARTLight Rail Expansion

Impact Analysis

Prepared byNuStats for

North Central Texas Council of Governmentsand Dallas Area Rapid Transit

January 2006

DARTLight Rail Expansion

Impact Analysis

Prepared byNuStats for

North Central Texas Council of Governmentsand 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 coordinatingfor 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 approximately12,800 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 votingrepresentative from the governing body. These voting representatives make up the GeneralAssembly 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 GovernmentsP. O. Box 5888Arlington, Texas 76005-5888(817) 640-3300

NCTCOG's Department of Transportation

Since 1974 NCTCOG has served as the Metropolitan Planning Organization (MPO) fortransportation 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 itstechnical 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. Departmentof 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 theFederal Highway Administration, the Federal Transit Administration, or the Texas Department ofTransportation."

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: rboward@nctcog.org 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-1

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-2

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.

II-1

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.

EXH

IBIT

II-1

H

OM

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NS

OF

ALL

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TS B

Y LI

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WH

ICH

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ERE

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EXH

IBIT

II-2

H

OM

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NS

OF

DA

LLA

S A

ND

CO

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CO

UN

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ND

ENTS

BY

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YED

II-4

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 full-

time 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-5

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 0.9% 0.9% 0.9%

Household Size 1 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+ 10.5% 14.1% 12.3% Household Vehicles

0 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 2.3% 2.2% 2.2%

Employment Status Employed Full Time 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-6

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 5.6% 6.7% 6.1%

Ride Time Peak 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 off-

peak 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-7

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 0.8% 0.9% 1.2% 0.9%

Household Size 1 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+ 13.8% 11.2% 13.5% 12.3% Household Vehicles

0 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 1.4% 2.3% 4.9% 2.2%

Employment Status Employed Full Time 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-8

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 5.3% 6.9% 4.3% 6.1%

Line 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-9

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%

Age

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 0.0% 1.4% 0.8%

Household Size

1 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 17.9% 22.8% 20.6%

Household Income

< $25k 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%

II-10

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.

EXH

IBIT

II-6

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0%10%

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EXH

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II-7

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II-13

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).

EXH

IBIT

II-8

TR

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AN

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4.2%

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100.

0%

II-15

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).

EXH

IBIT

II-9

TR

IP O

RIG

IN A

ND

DES

TIN

ATI

ON

S –

BLU

E LI

NE

DES

TIN

ATI

ON

TO

TAL

Orig

in

Hom

e Sc

hool

W

ork

Res

iden

ceH

ospi

tal /

D

r. O

ffice

St

ore/

M

all

Res

taur

ant

Chu

rch

Zoo

/ M

useu

m /

Aqu

ariu

mSt

ate

Offi

ce

Bld

g O

ffice

Bld

gO

ther

R

efus

ed

Hom

e

3.4%

22

.3%

4.

1%1.

2%2.

2%0.

1%0.

1%2.

8%0.

2%3.

0%13

.7%

53.1

%

Scho

ol

5.3%

0.

1%

0.4%

0.

1%0.

1%0.

1%6.

2%

Wor

k 16

.1%

1.2%

0.

2%0.

1%0.

2%0.

1%17

.9%

Res

iden

ce

1.6%

0.2%

0.

2%0.

1%0.

1%0.

1%0.

1%2.

5%

Hos

pita

l/ D

r. O

ffice

1.

8%

0.

1%

0.1%

0.1%

2.2%

Stor

e/M

all

1.1%

0.1%

0.

2%0.

1%0.

1%0.

1%1.

7%

Res

taur

ant

1.0%

0.1%

0.

2%0.

2%0.

1%1.

6%

Chu

rch

0.8%

0.

1%

0.

1%0.

1%1.

1%

Zoo

/ M

useu

m /

Aqu

ariu

m

0.3%

0.

1%

0.

4%

Stat

e G

ov’t

Bld

g 1.

0%

0.1%

0.1%

0.1%

1.3%

Offi

ce B

ldg

1.0%

1.

0%

Oth

er

1.2%

0.2%

0.

1%0.

1%0.

4%0.

1%2.

2%

Ref

used

6.

3%

0.3%

0.

2%

0.2%

0.1%

0.1%

1.6%

8.9%

Tota

l 37

.4%

4.

1%

24.9

%

5.3%

1.5%

2.7%

0.2%

0.1%

3.1%

0.3%

4.1%

16.2

%10

0.0%

II-17

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-18

EXHIBIT II-10 RED LINE BOARDING STATIONS BY TIME OF DAY

TIME OF DAY TOTAL At what station did

you board this train?

AM Peak (< 9 am) (N=99)

Mid-day (9 am – 2:59 pm)

(N=515)

PM Peak (3 pm – 6 pm)

(N=227)

Evening (after 6 pm)

(N=23)

Not recorded (N=66)

Parker Road 55.6% 35.0% 25.6% 17.4% 21.2% 33.2% Downtown Plano 2.0% 6.8% 5.7% 8.7% 6.1% 6.0%

Bush Turnpike 6.1% 4.1% 7.5% 6.1% 5.2% Galatyn Park 3.0% 1.4% 1.8% 1.5% 1.6%

Arapaho Center 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% 8.7% 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%

Lovers Lane 1.0% 1.3% 4.3% 3.0% 1.2% Mockingbird 3.0% 2.9% 4.0% 4.3% 4.5% 3.3%

Cityplace 4.0% 2.3% 4.0% 1.5% 2.8% Pearl 1.4% 2.2% 1.5% 1.4%

St. Paul 1.0% 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% Union 1.0% 1.7% 2.2% 1.6%

Convention Center

0.2% 0.4% 0.2%

Cedars 0.2% 1.8% 0.5% 8th & Corinth 0.6% 0.9% 3.0% 0.8%

Dallas Zoo 1.0% 1.0% 0.4% 0.8% Tyler/Vernon 0.0%

Hampton 1.0% 0.4% 0.4% 0.4% Westmoreland 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-19

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-20

EXHIBIT II-11 RED LINE ALIGHTING STATIONS BY TIME OF DAY

Time of Day Total At what station did you alight

from this train?

AM Peak (< 9 am) (N=99)

Mid-day (9 am – 2:59 pm)

(N=515)

PM Peak (3 pm – 6 pm)

(N=227)

Evening (after 6 pm)

(N=23)

Not recorded (N=66)

Parker Road 11.1% 17.1% 26.7% 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%

Galatyn Park 0.6% 0.4% 1.5% 0.5% 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% 2.3% 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% 13.0% 9.1% 6.0%

Cityplace 5.1% 2.7% 2.2% 2.6% Pearl 5.1% 4.7% 2.2% 4.3% 1.5% 3.9%

St. Paul 13.1% 3.5% 2.2% 3.0% 4.1% Akard 4.0% 4.3% 2.2% 4.5% 3.7%

West End 8.1% 14.8% 8.0% 13.6% 12.0% Union 2.0% 3.3% 3.1% 2.8%

Convention Center

0.2% 0.1%

Cedars 2.0% 0.4% 2.7% 1.1% 8th & Corinth 1.0% 0.2% 0.9% 1.5% 0.5%

Dallas Zoo 2.0% 3.5% 3.0% 2.4% Tyler/ Vernon 1.0% 0.2% 0.2%

Hampton 1.0% 0.2% 0.9% 0.4% Westmoreland 0.8% 2.7% 1.5% 1.2% Not provided 0.2% 0.1%

Total 2.0% 2.1% 1.3% 4.3% 3.0% 2.0%

II-21

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

Time of Day Total At what station did

you board this train?

AM Peak (< 9 am) (N=121)

Mid-day (9 am – 2:59 pm) (N=503)

PM Peak (3 pm – 6 pm) (N=193)

Evening (after 6 pm)

(N=11)

Not reported (N=97)

Downtown Garland 43.8% 39.0% 32.1% 36.4% 39.2% 38.2% Forest/Jupiter 8.3% 6.8% 6.2% 18.2% 11.3% 7.5% LBJ/Skillman 9.9% 9.3% 11.9% 2.1% 9.1% White Rock 9.1% 9.3% 12.4% 18.2% 7.2% 9.8% Mockingbird 4.1% 2.0% 5.2% 3.1% 3.0% Cityplace 1.7% 2.0% 2.1% 1.0% 1.8% Pearl 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% 9.1% 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% 0.1% Cedars 0.8% 1.0% 0.5% 8th & Corinth 0.8% 0.4% Morrell 0.6% 0.5% 1.0% 0.5% Illinois 0.8% 1.0% 1.0% 0.4% Kiest 0.8% 1.2% 1.0% 1.0% 1.1% VA Medical Center 1.0% 4.1% 1.0% Ledbetter 4.1% 3.8% 2.6% 1.0% 3.2% Not provided 1.7% 3.6% 6.7% 18.2% 6.2% 4.4%

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

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-22

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

Time of Day Total At what station did you alight from this

train?

AM PEAK (< 9 AM) (N=121)

Mid-day (9 am – 2:59 pm) (N=503)

PM Peak (3 pm – 6 pm)

(N=193)

Evening (after 6 pm)

(N=11)

Not reported (N=97)

Downtown Garland 25.8% 25.1% 28.6% 9.1% 28.4% 26.1% Forest/Jupiter 6.7% 8.0% 8.9% 9.5% 8.1% LBJ/Skillman 10.0% 12.0% 15.1% 9.1% 10.5% 12.2% White Rock 0.8% 4.6% 8.9% 18.2% 3.2% 5.0% Mockingbird 2.5% 5.0% 4.7% 3.2% 4.4% Cityplace 5.8% 2.0% 1.6% 9.1% 4.2% 2.7% Pearl 5.0% 2.2% 2.6% 9.1% 4.2% 2.9% St. Paul 13.3% 3.4% 1.0% 7.4% 4.6% Akard 10.0% 3.8% 3.1% 3.2% 4.4% West End 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% Cedars 0.4% 0.5% 1.1% 0.4% 8th & Corinth 1.7% 0.6% 0.5% 0.7% Morrell 0.4% 0.5% 0.3% Illinois 0.8% 2.6% 1.0% 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%

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

II-23

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.

EXH

IBIT

II-1

4 R

ED L

INE

BO

AR

DIN

G A

ND

ALI

GH

TIN

G S

TATI

ON

S IN

-BO

UN

D D

UR

ING

AM

PEA

K

(N=7

2)

At w

hat s

tatio

n w

ill y

ou g

et o

ff th

e tr

ain?

To

tal

At w

hat

stat

ion

did

you

boar

d th

is tr

ain?

Park

er

Roa

d Ar

apah

o C

ente

r Sp

ring

Valle

y LB

J /

Cen

tral

Fore

st

lane

W

alnu

t H

ill

Park

La

ne

Love

rs

Lane

M

ocki

ng

bird

C

itypl

ace

Pear

lSt

. Pa

ul

Akar

d W

est

End

Uni

on C

edar

s 8th

&

Cor

inth

Dal

las

Zoo

Ham

pton

Tyl

er /

Vern

onN

ot

repo

rted

Park

er R

oad

1.

4%5.

6%2.

8%2.

8%6.

9%5.

6%5.

6%5.

6%13

.9%

5.6%

8.3%

1.4%

2.8%

1.4%

1.4%

1.4%

2.8%

75.0

%

Dow

ntow

n Pl

ano

1.

4%1.

4%2.

8%

Bus

h Tu

rnpi

ke

1.

4%2.

8%1.

4%5.

6%

Gal

atyn

Par

k

1.4%

1.4%

2.8%

Arap

aho

Cen

ter

1.

4%2.

8%1.

4%1.

4%6.

9%

Wal

nut H

ill

1.4%

1.

4%2.

8%

City

plac

e

1.4%

1.4%

2.8%

Dal

las

Zoo

1.4%

1.

4%

Tota

l 2.

8%

2.8%

1.4%

2.8%

5.6%

5.6%

2.8%

6.9%

8.3%

6.9%

5.6%

18.1

%5.

6%9.

7%2.

8%2.

8%1.

4%2.

8%1.

4%1.

4%2.

8%10

0.0%

As s

een

in E

xhib

it II-

15, o

utbo

und

PM p

eak

Red

Lin

e rid

ers

wer

e m

ost l

ikel

y to

boa

rd a

t Wal

nut H

ill (2

3%),

Park

er R

oad

(9%

), C

itypl

ace

(8%

) or

Moc

king

bird

(7%

). M

ost (

47%

) alig

hted

at P

arke

r Roa

d, B

ush

Turn

pike

(12%

), D

ownt

own

Plan

o (9

%),

or S

prin

g Va

lley

(9%

).

EXH

IBIT

II-1

5 R

ED L

INE

BO

AR

DIN

G A

ND

ALI

GH

TIN

G S

TATI

ON

S O

UT-

BO

UN

D D

UR

ING

PM

PEA

K

(N=1

18)

At w

hat s

tatio

n w

ill y

ou g

et o

ff th

e tr

ain?

To

tal

At w

hat s

tatio

n di

d yo

u bo

ard

this

trai

n?

Park

er R

oad

Dow

ntow

n Pl

ano

Bush

Tur

npik

e Ar

apah

o C

ente

r Sp

ring

Valle

yLB

J/C

entra

lFo

rest

lane

Wal

nut

Hill

Moc

king

bird

C

itypl

ace

St. P

aul

Akar

d W

est E

ndC

edar

s

Park

er R

oad

0.

9%0.

9%0.

9%

0.9%

0.9%

1.7%

0.9%

0.9%

1.7%

9.4%

Bus

h Tu

rnpi

ke

0.

9%0.

9%G

alat

yn P

ark

0.

9%

0.9%

Arap

aho

Cen

ter

1.7%

0.

9%

2.6%

Sprin

g Va

lley

1.

7%

0.9%

2.6%

LBJ/

Cen

tral

1.7%

1.7%

Fore

st la

ne1.

7%

0.9%

2.

6%W

alnu

t Hill

12.8

%

0.9%

4.3%

0.9%

1.7%

0.9%

0.

9%0.

9%23

.1%

Park

Lan

e0.

9%

0.9%

0.9%

2.

6%Lo

vers

Lan

e0.

9%

0.

9%M

ocki

ngbi

rd2.

6%

0.9%

0.9%

1.7%

0.9%

6.

8%C

itypl

ace

4.3%

2.

6%

0.9%

7.7%

Pear

l0.

9%

1.7%

2.

6%St

. Pau

l4.

3%

0.9%

5.

1%Ak

ard

3.4%

1.

7%0.

9%

6.0%

Wes

t End

5.1%

1.

7%

6.8%

Uni

on0.

9%

0.9%

0.9%

0.9%

0.

9%4.

3%C

onve

ntio

n C

ente

r

0.9%

0.

9%C

edar

s1.

7%

0.9%

2.

6%8th

& C

orin

th

0.9%

0.

9%D

alla

s Zo

o0.

9%

0.

9%H

ampt

on

0.9%

0.

9%W

estm

orel

and

0.9%

0.

9%

1.7%

Not

repo

rted

2.6%

0.

9%2.

6%

6.0%

Tota

l47

.0%

9.

4%12

.09%

1.7%

9.4%

5.1%

3.4%

0.

9%1.

7%1.

7%2.

6%1.

7%1.

7%1.

7%10

0.0%

Mos

t of t

he in

-bou

nd B

lue

Line

ride

rs (7

0%) d

urin

g th

e AM

Pea

k ho

urs

boar

ded

at D

ownt

own

Gar

land

. Of t

hese

, a to

tal o

f 18%

alig

hted

at S

t. Pa

ul,

10%

at A

kard

, and

8%

at t

he W

est E

nd a

fter b

oard

ing

at D

ownt

own

Gar

land

. See

Exh

ibit

II-16

.

EXH

IBIT

II-1

6 B

LUE

LIN

E B

OA

RD

ING

AN

D A

LIG

HTI

NG

STA

TIO

NS

IN-B

OU

ND

DU

RIN

G A

M P

EAK

(N=6

8)

At w

hat s

tatio

n w

ill y

ou g

et o

ff th

e tr

ain?

To

tal

Stat

ion

Whe

re

Boar

ded

Trai

n?

Dow

ntow

n G

arla

nd

Fore

st /

Jupi

ter

LBJ

/ Sk

illman

Whi

te

Roc

k M

ocki

ngbi

rd C

itypl

ace

Pear

l St

. Pau

lAk

ard

Wes

t End

Uni

on

Con

vent

ion

Cen

ter

8th &

C

orin

th

Kies

t VA

M

edic

al

Cen

ter

Ledb

ette

r N

ot

prov

ided

Dow

ntow

n G

arla

nd

1.5%

1.5

%3.

0%

6.0%

7.5%

17.9

%10

.4%

7.5%

3.0%

1.

5%

1.

5%1.

5%7.

5%

70.1

%

Fore

st /

Jupi

ter

1.5%

4.5%

3.0%

3.0%

11.9

%

LBJ

/ Sk

illman

1.

5%

1.5%

1.

5%

1.

5%1.

5%

7.

5%

Whi

te R

ock

1.5%

1.5%

3.

0%

1.5%

7.5%

Moc

king

bird

1.

5%

1.

5%U

nion

1.

5%

1.

5%To

tal

1.5%

1.5%

4.5%

1.5

%4.

5%

7.5%

7.5%

22.4

%16

.4%

10.4

%3.

0%

4.5%

3.

0%1.

5%

1.5%

1.5%

7.5%

100

.0%

II-27

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-28

EXHIBIT II-17 BLUE LINE BOARDING AND ALIGHTING STATIONS OUT-BOUND DURING PM PEAK

(N=97)

At what station will you get off the train? Total Station where boarded train?

Downtown Garland

Forest / Jupiter

LBJ / Skillman

White Rock

Cityplace Pearl West End Union

Downtown Garland

1.0% 1.0% 2.1%

Forest / Jupiter

2.1% 1.0% 3.1%

LBJ/Skillman 6.3% 2.1% 8.3% White Rock 4.2% 4.2% 7.3% 1.0% 1.0% 17.7%

Mockingbird 10.4% 10.4% Cityplace 3.1% 1.0% 4.2%

Pearl 4.2% 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% Morrell 1.0% 1.0% Illinois 1.0% 1.0% 2.1%

Kiest 1.0% 1.0% 2.1% Ledbetter 1.0% 2.1% 2.1% 5.2%

Tyler / Vernon

1.0% 1.0%

Not provided

5.2% 3.1% 2.1% 1.0% 11.5%

Total 53.1% 16.7% 20.8% 3.1% 1.0% 1.0% 3.1% 1.0% 100.0%

Mos

t Red

Lin

e rid

ers

acce

ssed

the

train

by

wal

king

(27%

), tra

nsfe

rring

from

a b

us (2

6%),

or d

rivin

g al

one

(25%

). Fo

r the

Blu

e Li

ne

rider

s, 4

2% tr

ansf

erre

d fro

m a

bus

, 24%

wal

ked,

and

17%

dro

ve a

lone

. See

Exh

ibit

II-18

.

EXH

IBIT

II-1

8 A

CC

ESS

MO

DE

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Drive alo

ne

Drive w/oth

ers

Passeng

er (Drop

ped off

)Passeng

er (par

ked)

Bus

Walk

Bike

Refused

Blue

Line

Red L

ineTo

tal

As E

xhib

it II-

19 s

how

s, m

ost

resp

onde

nts

repo

rted

thei

r us

e of

DAR

T fo

r th

is p

artic

ular

trip

was

a p

erm

anen

t pa

rt of

the

ir tra

vel

beha

vior

. Tw

o-th

irds

(66%

) of R

ed L

ine

resp

onde

nts

and

69%

of B

lue

Line

resp

onde

nts

indi

cate

d th

at th

eir u

se o

f lig

ht ra

il fo

r thi

s tri

p

was

per

man

ent.

EXH

IBIT

II-1

9 TY

PE O

F TR

IP

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Tempor

ary

Permane

nt

Not Prov

ided

Blue

Line

Red L

ineTo

tal

II-31

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% Age

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 0.7% 0.7% 0.7%

Household Size 1 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% Household Vehicles

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 2.3% 1.8% 2.1%

Employment Status Employed Full Time 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%

II-32

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 4.3% 9.6% 6.8%

Trip Purpose Work/work related 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%

Alm

ost h

alf o

f the

resp

onde

nts

repo

rted

they

mak

e th

is tr

ip 5

to 7

day

s pe

r wee

k, a

s illu

stra

ted

in E

xhib

it II-

21. A

n ad

ditio

nal o

ne-fi

fth

of re

spon

dent

s in

dica

ted

they

mad

e th

e tri

p 2

to 4

tim

es p

er w

eek.

EXH

IBIT

II-2

1 H

OW

OFT

EN M

AK

E TH

IS T

RIP

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

5-7 da

ys/wk

2-4 da

ys/wk

once a

week

First tim

e

Several

times/

mthonc

e / mth

<1 per

mth

Refused

Blue

Lin

eR

ed L

ine

Tota

l

An e

qual

num

ber o

f rid

ers

(43%

) rep

orte

d us

ing

the

rail

one

year

or l

ess,

or 2

to 5

yea

rs. R

ed L

ine

user

s w

ere

mor

e lik

ely

to re

port

that

they

wer

e ne

wer

ride

rs (f

irst t

rip o

r rid

ing

one

year

or l

ess)

as

com

pare

d to

Blu

e Li

ne u

sers

. Blu

e Li

ne u

sers

wer

e m

ore

likel

y to

repo

rt ha

ving

mad

e th

is tr

ip fo

r the

last

2 to

5 y

ears

. See

Exh

ibit

II-22

.

EXH

IBIT

II-2

2 LE

NG

TH O

F TI

ME

MA

KIN

G T

HIS

TR

IP

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

First Time

1 yr or

less

2-5 ye

ars

6-10 y

ears

> 10 y

rs

Refused

Blue

Line

Red L

ineTo

tal

II-35

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-36

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-37

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-38

EXHIBIT II-25 EXPERIENCES AND INFLUENCES BY LINE

Red Line Blue Line Experience Influence 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-39

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

DART line the respondent boarded

Total

Red Blue 0 25.2% 22.2% 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%

Total 100.0% 100.0% 100.0%

II-40

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 before you started using light rail?

DART line the respondent boarded

Red Blue TotalDrove alone 52.5% 46.8% 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% 0.1% Total 100.0% 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 Blue TotalYes 30.2% 20.4% 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%

II-41

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% Age

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%

Household Size 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%

II-42

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 1.8% 1.1% 1.5%

Employment Status Employed Full Time 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 6.0% 4.2% 5.3%

Household Income < $25k 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 5.0% 4.2% 4.7%

Trip Purpose Work/work related 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 1.5% 6.9% 3.6%

Length of Time Making this Trip

First Time 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%

III-1

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-2

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 transit-

oriented 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-3

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-4

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-5

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-6

EXHIBIT III-2 ARTERIAL ADT IN THE NORTH CENTRAL CORRIDOR 2004

Intersection Average Daily Traffic Preston Road at Forest Lane 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-7

EXHIBIT III-4 ESTIMATED ADT IN THE NORTH CENTRAL CORRIDOR-NO-BUILD SCENARIO

Intersection Average Daily Traffic Preston Road at Forest Lane 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-8

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.

IV-1

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-2

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-3

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-4

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-5

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-6

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-7

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-8

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-9

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-10

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-11

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).

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0.

1%1.

8%

Con

vent

ion

Cen

ter

0.0%

0.1%

0.

1%

Dow

ntow

n G

arla

nd

0.3%

3.

0%0.

2%1.

5%0.

4%

0.1%

1.2%

0.8%

0.3%

2.

4%

1.1%

2.6%

0.2%

2.1%

3.

4%1.

6%

0.8%

10.8

%

2.3%

3.3%

38.4

%

Fore

st/J

upite

r

0.4%

0.1%

0.5%

0.1%

1.

1%0.

1%

0.2%

0.

2%0.

9%

0.7%

0.1%

0.3%

0.

1%1.

6%

0.7%

0.3%

7.5%

Ill

inoi

s

0.

3%

0.

0%

0.1%

0.4%

Ki

est

0.5%

0.2%

0.

2%

0.0%

0.

1%1.

1%

LBJ/

Skillm

an

0.1%

0.

5%0.

1%0.

4%

2.0%

0.7%

0.2%

0.3%

0.1%

0.5%

0.1%

0.5%

0.

2%

2.1%

1.

0%0.

1%9.

0%

Ledb

ette

r

1.

3%0.

8%

1.0%

0.

0%

0.2%

3.3%

M

ocki

ngbi

rd

2.4%

0.1%

0.

3%

0.1%

0.

1%3.

0%

Mor

rell

0.1%

0.2%

0.

2%

0.0%

0.

5%

Pear

l

2.

4%0.

2%

0.4%

0.

0%

0.1%

3.2%

St

. Pau

l

1.

8%0.

1%

0.2%

0.

0%

2.2%

Ty

ler/V

erno

n

0.

2%0.

1%

0.

0%

0.3%

U

nion

0.

8%0.

5%

0.1%

0.

0%

0.1%

1.5%

VA

Med

ical

C

ente

r

0.

7%0.

3%

0.

0%

1.0%

W

est E

nd

4.6%

1.3%

2.

2%

0.0%

0.1%

0.

1%

0.

1%8.

4%

Whi

te R

ock

0.2%

0.

1%0.

1%0.

3%

2.8%

1.0%

2.

6%

0.1%

0.1%

0.1%

0.

1%0.

2%

0.1%

1.0%

0.

1%0.

4%9.

5%

Ref

used

0.1%

0.1%

0.1%

1.

3%0.

7%

0.9%

0.

0%0.

2%

0.

4%

0.2%

0.2%

4.2%

To

tal

0.7%

4.

4%0.

4%2.

7%1.

0%

26.2

%8.

1%1.

0%0.

8%

12.2

%

1.6%

4.4%

0.3%

2.9%

4.

6%0.

1%2.

2%

1.0%

15.9

%

5.1%

4.6%

100.

0%

VI-1

VI. APPENDIX C: SURVEY INSTRUMENT

Surface TransportationTechnical CommitteeRenee Lamb, Chair

NCTCOG Executive Board 2005-2006

Regional Transportation Council 2005-2006

PresidentWayne GentCounty Judge, Kaufman County

Vice PresidentOscar TrevinoMayor, City of North Richland Hills

Secretary-TreasurerChad AdamsCounty Judge, Ellis County

Past PresidentBob PhelpsMayor, City of Farmers Branch

DirectorBill BlaydesCouncilmember, City of Dallas

DirectorPat EvansMayor, City of Plano

DirectorJohn MurphyMayor Pro Tem, City of Richardson

DirectorGreg HirschCouncilmember, Town of Addison

DirectorMike CantrellCommissioner, Dallas County

DirectorTom VandergriffCounty Judge, Tarrant County

DirectorChuck SilcoxCouncilmember, City of Fort Worth

DirectorBobbie MitchellCommissioner, Denton County

DirectorBobby WaddleMayor Pro Tem, City of DeSoto

General CounselJerry Gilmore

Executive DirectorR. Michael Eastland

Wendy Davis, ChairCouncilmember, City of Fort Worth

Cynthia White, Vice ChairCommissioner, Denton County

Oscar Trevino, SecretaryMayor, City of North Richland Hills

Terri AdkissonBoard MemberDallas Area Rapid Transit

Bill BlaydesCouncilmember, City of Dallas

Ron BrownCommissioner, Ellis County

Maribel Chavez, P.E.District EngineerTexas Department of Transportation,Fort Worth District

J. Jan CollmerBoard MemberDallas/Fort Worth International Airport

Bob DayMayor, City of Garland

Maurine DickeyCommissioner, Dallas County

Charles EmeryChairmanDenton County Transportation Authority

Herbert GearsMayor, City of Irving

Paul GeiselChairFort Worth Transportation Authority

Mel NeumanMayor, City of Mansfield

Mike NowelsDeputy Mayor Pro TemCity of Lewisville

Ed OakleyCouncilmember, City of Dallas

Chuck SilcoxMayor Pro Tem, City of Fort Worth

Grady SmitheyMayor Pro Tem, City of Duncanville

John TatumCitizen Representative, City of Dallas

Maxine Thornton ReeseCouncilmember, City of Dallas

Carl TysonCouncilmember, City of Euless

Marti VanRavenswaayCommissioner, Tarrant County

Bill WhitfieldMayor, City of McKinney

B. Glen WhitleyCommissioner, Tarrant County

Kathryn WilemonCouncilmember, City of Arlington

Michael Morris, P.E.Director of Transportation, NCTCOG

Bill Hale, P.E.District EngineerTexas Department of Transportation,Dallas District

Roger HarmonCounty Judge, Johnson County

Jack Hatchell, P.E.Commissioner, Collin County

John Heiman, Jr.Councilmember, City of Mesquite

Kathleen HicksCouncilmember, City of Fort Worth

Ron JensenCouncilmember, City of Grand Prairie

Pete KampCouncilmember, City of Denton

Linda KoopCouncilmember, City of Dallas

Ken LambertDeputy Mayor Pro Tem, City of Plano

Kenneth MayfieldCommissioner, Dallas County

Steve McCollumCouncilmember, City of Arlington

Becky MillerMayor, City of Carrollton

Jack MillerVice Chair, North Texas Tollway Authority

Rich MorganCitizen Representative, City of Dallas

John MurphyMayor Pro Tem, City of Richardson