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
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