Final Report. Madison Metro Transit On-board Survey. Approach, Findings, and Analysis

Transcription

1 Approach, Findings, and Analysis Final Report prepared for Transit Consortium (City of Madison, Dane County, WisDOT), Madison Area Transportation Planning Board, and Metro Transit prepared by Cambridge Systematics, Inc. with Dikita Enterprises, Inc. University of Wisconsin, Madison September

2

3 report Madison Metro Transit On-board Survey Approach, Findings, and Analysis prepared for Transit Consortium, Transit Consortium (City of Madison, Dane County, WisDOT), Madison Area Transportation Planning Board, and Metro Transit prepared by Cambridge Systematics, Inc. 115 South LaSalle Street, Suite 2200 Chicago, IL with Dikita Enterprises, Inc. University of Wisconsin, Madison date September 2015

4

5 Table of Contents 1.0 Introduction Understand Rider Patterns Support Transit Planning Report Structure Questionnaire Design Survey Structure and Contents Comparison with 2008 Transit On-board Questionnaire Definition of a Completed Survey Trip-level Information Socio-demographic Information Supplementary Questions Sampling Plan Survey Approach Route Information Targets Sampling Plan Time Periods Sampling Approach Completes Per Hour Selection Procedure Sampling Results Survey Management Plan Identify Key Challenges Typical On-board Survey Challenges Project Specific Challenges Survey Fieldwork Methodology Methods to Engaging Riders On-to-Off Survey Procedures Passenger Count Procedures Self-Administered Survey Procedures Tablet-based Personal Interviews Cambridge Systematics, Inc. i

6 Table of Contents, continued Field Operations Coordination Field Data Retrieval Surveyor Training Interlined Route Assessment Survey Assignments Survey Pretest On-to-Off Survey Findings Finding # Finding # Finding # Finding # Finding # Finding # Boarding and Alighting Counts Findings Paper On-board Survey Findings Findings Tablet On-board Survey Findings Issue # Issue # Issue # Issue # Issue # Field Implementation Training and Recruiting Daily Management ii Cambridge Systematics, Inc.

7 Survey Timeframe Track Data Collection Trends Analyze Data Collection Metrics Track Surveyor Performance Track Paper Questionnaires Data Retrieval On-to-Off Survey Data Boarding and Alighting Counts On-Board Tablet Survey Data On-Board Paper Survey Data Entry Survey Data Cleaning and Expansion Preliminary Survey Cleaning Preliminary Data Collection Results Geocoding Efforts Automated Geocoding in Tablet Geocoding in Data Entry Portal Automated Geocoding in the Handheld Devices Back End Geocoding Final Dataset Survey Data Expansion Data Processing Steps Survey Expansion Steps Expansion Type Expansion Type Expansion Type Survey Expansion Checks Planning District Comparison Bus-Stop Level Comparison Route Decomposition Results and Findings Travel Patterns Time-of-Day Distribution Trip Purpose Mode of Access and Egress Trip Purpose and Number of Transfers Socio-Demographics Cambridge Systematics, Inc. iii

8 Table of Contents, continued A. Sampling Plan... A-1 B. Logistics and Implementation... B-1 Crew Transportation... B-1 Field Supervisor Role... B-1 Field Surveyor Equipment... B-2 Survey Fieldworker Role... B-3 Survey Staging Location... B-5 C. On-board Survey Responses... C-1 D. Route Profiles... D-1 iv Cambridge Systematics, Inc.

9 List of Tables Table 3.1 Sampling Plan Design Table 7.1 Surveys Returned Table 7.2 Trips Surveyed During Field Effort Table 7.3 Usable Records by Mode of Data Collection Table 7.4 Usable Surveys by Route Table 7.5 Survey Expansion Types Table 7.6 Survey Expansion Results Table 7.7 Comparison of Total Boardings at District Level Table 7.8 Comparison of Most Used Stops Table 7.9 Transfers by Route Table 7.10 Route Decomposition Analysis Table 8.1 Weighted Results by Route Table 8.2 Access and Egress Mode Table 8.3 Trip Purpose and Number of Transfers Table 8.4 Trip Purpose and Household Size Table 8.5 Trip Purpose and Number of Employed Workers in Household Table 8.6 Trip Purpose and Number of Vehicles in Household Table 8.7 Fare Type and Frequency of Transit Use Table 8.8 Race and Annual Household Income Table B.1 Surveyor Supplies by Collection Method... B-3 Table C.1 Trip Origin Characteristics... C-1 Table C.2 Access Mode to Bus Stop... C-1 Table C.3 Transfers Before Boarding this Bus... C-2 Table C.4 Transfers After Exiting this Bus... C-2 Table C.5 Egress Mode from Bus Stop... C-2 Table C.6 Trip Destination Characteristics... C-3 Table C.7 Total Number of Transfers... C-3 Table C.8 Fare Payment Method... C-4 Cambridge Systematics, Inc. v

10 List of Tables, continued Table C.9 Senior/Disabled or Youth Fare... C-4 Table C.10 Frequency of Riding Metro Transit... C-4 Table C.11 Respondent Age... C-5 Table C.12 Respondent Gender... C-5 Table C.13 Respondent Employment Status... C-5 Table C.14 Respondent Possession of Driver License... C-6 Table C.15 College/University Student... C-6 Table C.16 Hispanic/Latino/Spanish Origin... C-6 Table C.17 Respondent Race... C-7 Table C.18 Speak English Well... C-7 Table C.19 Languages Spoken at Home... C-8 Table C.20 Past Use of Metro Transit... C-8 Table C.21 Household Size... C-9 Table C.22 Employed Workers in Household... C-9 Table C.23 Number of Vehicles Owned by Household... C-9 Table C.24 Vehicle Availability... C-10 Table C.25 Annual Household Income... C-10 Table C.26 Level of Satisfaction with Metro Transit Service... C-11 vi Cambridge Systematics, Inc.

11 List of Figures Figure 2.1 Metro Transit 2015 Transit On-board Survey Questionnaire Figure 2.2 Metro Transit 2008 Transit On-board Survey Questionnaire Figure 4.1 Tablet Interview Screenshot Figure 7.1 District Geography Figure 8.1 Trip Purpose Cambridge Systematics, Inc. vii

12

13 1.0 Introduction The 2015 Metro Transit on-board survey aims to understand the travel behavior and characteristics of transit riders in the Madison area. Through the administration of an on-board survey of bus passengers and the subsequent analysis of the results, the study will provide a variety of travel and ridership information in the region. The survey was administered in spring 2015 by a team led by Cambridge Systematics (CS). Dikita Enterprises, Inc and the University of Wisconsin also supported in the data collection efforts. CS staff managed the 2015 on-board survey project. CS also managed the sampling plan development for both the on-board and on-to-off surveys, oversaw the QA/QC process for the project, and was responsible for survey expansion and data analyses. The UW staff conducted much of the field work and provided local knowledge. Dikita Enterprises provided survey supervisors for all survey efforts. Additionally, Dikita staff also provided the technology for conducting on-tooff surveys and tablet interviews, and conducted training for field interviewers by documenting the best use of technology prior to survey implementation. In addition, Dikita staff were responsible for the retrieval of data from the tablets and developed a database engine to support data entry for the paper surveys. The 2015 on-board transit survey for Metro Transit has multiple, but related, goals. Broadly, the study goals of the project were to: Collect ridership demographics and travel patterns to aid short-range service planning and meet Title VI requirements, and Support long-range regional transit planning and travel demand forecasting, including ridership forecasting for the planned bus rapid transit system. 1.1 UNDERSTAND RIDER PATTERNS The key to understanding travel behavior and rider characteristics in the region and the foundation of the entire project is the design and administration of the on-board survey questionnaire. Thus, the successful development and deployment of the on-board survey was an early, important interim goal of the project team. The survey questionnaire was designed to collect information about a rider s travel behavior and their personal characteristics. Cambridge Systematics, Inc. 1-1

14 To improve the quality of data obtained from the survey, the project team administered the questionnaire using a hybrid approach which leverages new technology and traditional methods. On high-use and other selected bus routes, a tablet-based questionnaire was primarily used in a personal interview based format 1. The results from these interviews were compiled nightly. For the other bus routes, a traditional paper questionnaire was used. Handheld scanners were employed by the on-board survey teams to scan each questionnaire s printed bar code to allow for accurate identification of boarding and alighting locations. In addition to the on-board surveys, passenger boarding and alighting counts and on-to-off surveys using cards handed to passengers were conducted on some routes. The primary goal of these boarding/alighting and on-to-off counts was to collect basic ridership patterns with a larger sample size to support survey expansion. The goal of the study was to get on-board survey returns from approximately 4,500 riders and on-to-off data from about 6,000 riders. By combining the data points from the surveys and the on-to-off counts, the project team built a rider profile consisting of rider origins and boardings; alightings and destinations; plus their mode of access to Metro Transit s services, travel purpose, bus routes used, and transferring patterns. In addition, demographics and rider opinions were also collected through the on-board survey questionnaire. Taken together, the aggregated survey response data allow for ridership segmentation. Using the final dataset, Madison Metro Transit will understand who their customers are, where they are going, and the trip purpose. 1.2 SUPPORT TRANSIT PLANNING Detailed analyses of the travel behavior and rider characteristics database obtained through the on-board survey can provide comprehensive support for transit planning goals. The Federal Transit Administration (FTA) requires recent ridership and survey data to calibrate and validate travel forecasting models. The most recent on-board survey for Madison Metro Transit was conducted in 2008 and was used to test the model s performance. It is fully expected that the current survey iteration will be used to make improvements and refinements to the regional travel demand model. The study team coordinated with the 1 Because of the block scheduling, a mix of methods was used on most routes. This mix also helps addresses possible differences in responses based on the two methods. 1-2 Cambridge Systematics, Inc.

15 FTA to seek approval of the survey sampling plan prior to the survey administration in early Additionally, the new on-board transit survey data can be used to support Title VI and equity analyses. The questionnaire was designed with a focus on capturing information relevant to Title VI analysis. 1.3 REPORT STRUCTURE The rest of the report is organized as follows: Section 2 discusses the survey questionnaire design and contrasts it against the 2008 survey questionnaire; Section 3 describes the sampling plans designed to administer the survey; Section 4 discusses the key features of the survey management plan; Section 5 outlines the survey pretest and identifies the key areas for improvements; Section 6 outlines the field implementation effort; Section 7 outlines the data retrieval procedures and the survey expansion methodology; and Section 8 provides a detailed analysis of the retrieved dataset. Cambridge Systematics, Inc. 1-3

16

17 2.0 Questionnaire Design The primary goal of the 2015 Metro Transit On-board Survey was to collect representative rider data to study the travel behavior of Metro Transit riders, including their origins and destinations, boardings and alightings, mode of access and egress, travel purpose, routes used and transfer patterns, and demographic information. The data collected through this survey will be used to provide insights into the characteristics and behavior of Metro Transit riders and will also be used make improvements to the Dane County regional travel demand model. The design of the survey and the language used in the questions was refined to reflect local terminology to ensure that respondents provide robust information that can be used to meet project goals. This section of the report focuses on two key elements: First, it summarizes the structure and content of the 2015 Metro Transit Onboard Survey questionnaire. Second, it compares and contrasts the 2015 version of the questionnaire with the questionnaire from the previous survey conducted on Metro Transit routes. 2.1 SURVEY STRUCTURE AND CONTENTS The information that is customarily collected through a transit on-board survey includes the following information. Origin and destination Modes of access and egress Boarding and alighting location Trip purpose Routes taken in the trip and transfer information Fare payment Usage of transit service Socio-economic characteristics Opinions regarding Metro Transit service and facilities The 2015 survey questionnaire was organized into five main sections (Figure 2.1): Cambridge Systematics, Inc. 2-1

18 Introduction. This section provides riders with a brief introduction about the survey and provides directions of how to return the completed survey to the fieldworkers. Trip Information. This section covers typical transit trip information such as the origin and destination, mode of access and egress, boarding and alighting place, routes taken and transfer information, fare payment and transit usage. In Madison, there is significant route interlining. Therefore, the questions were structured to focus on the current bus route as opposed to the current one-way trip that is more commonly used. All questions in this section are considered critical and must be completed in order for a survey to be deemed complete. Personal Information. This section contains questions about individual socio-economic information such as age, gender, employment status, possession of a driver s license, race, ethnic group, college/university student status, and languages spoken. Household Information. This section collects information about household size, household income, number of employees, vehicle ownership and vehicle availability. Some of the questions in this section, such as household size and vehicle ownership/availability, are also considered critical from a survey completion standpoint. Attitudes and Preferences. This section asks the respondent to rate the quality of transit service in Madison using a four-point scale. Rating questions span several topics including safety, comfort, travel times, and bustracking. Mailback Option. The survey questionnaire allowed respondents to complete the survey after they got off the bus and mail the survey back to Madison Metro Transit with prepaid postage. This option was also available in the previous iteration of the Madison Metro Transit survey and had proven to be a reliable option to collect responses. Web Survey. The survey questionnaire was also coded into a web program by Cambridge Systematics. This web-based questionnaire served as an additional option for riders that could not complete the survey on the bus. This option did not exist in The web program was designed to work with a log in (survey number) so that the data collected from the survey could be linked back to the appropriate trip to validate the information collected. The paper questionnaire included information about the link to access this web questionnaire. 2-2 Cambridge Systematics, Inc.

19 Figure 2.1 Metro Transit 2015 Transit On-board Survey Questionnaire Cambridge Systematics, Inc. 2-3

20 2-4 Cambridge Systematics, Inc.

21 2.2 COMPARISON WITH 2008 TRANSIT ON-BOARD QUESTIONNAIRE The 2015 survey questionnaire was developed using the 2008 questionnaire as a template (Figure 2.2). Three major changes were implemented in the 2015 survey based on discussions with Madison Area Transportation Planning Board and Metro Transit staff. These changes are listed below. First, more questions about socio-economic information were added to collect information necessary to support fare equity analysis and to understand how transit serves minority and low-income population. Second, more emphasis was given to the transfer information collection due to interlining in Madison. The sequence of bus ride questions was also restructured to reflect and remind riders of their trip sequence: from the true origin of the trip, to accessing the first bus-stop, to the boarding location for the current route, all the way until the information about the final destination. Third, as discussed in the previous section, questions were carefully worded capture information about current route as opposed to the one-way trip. Other differences between the two questionnaires include the following items. Information about the route number and the time when the rider got on the bus was included in 2015 to serve as a validation check in the event that the bar-code scanner that captures this information malfunctions. More fare payment options were included in 2015 to support fare equity analysis. New options in the survey include: unlimited ride pass, 31-day pass, 31-day pass (low income), EZ rider youth pass. Additionally, respondents were requested to answer if they availed of any senior/disabled or youth fares when making the trip. A question about student status was included in the 2015 survey. This information, when used in conjunction with questions such as household size, income, and vehicle availability can shed light about how students, especially college students at the University of Wisconsin, utilize the transit system. Racial group and ethnic information are collected in 2015 using two questions. Both questions are consistent with the language observed in the 2010 Census. Two language related questions are included in the 2015 survey questionnaire. These questions may be used to assess whether marketing materials need to be printed in multiple languages. Cambridge Systematics, Inc. 2-5

22 The household income categories in the 2015 survey were also changed to match the 2010 Census income categories. More Metro Transit service quality assessment criteria are included in the 2015 survey. Topics being assessed include personal safety at transfer point, maps and schedules, online trip planning, and bus tracking. 2.3 DEFINITION OF A COMPLETED SURVEY During the survey s design, key questions essential from a modeling and data analysis perspective were identified. Only questionnaires that have each of these questions filled out with reasonable information were considered complete. A full list of these questions is provided below: Trip-level Information Where did you BEGIN this trip? How did you arrive at the FIRST bus stop at the BEGINNING of this trip? At what bus stop did you get ON THIS ROUTE? At what bus stop will you get OFF THIS ROUTE? How will you get from your LAST bus stop to your FINAL destination for this trip? What is your FINAL destination for this trip? Socio-demographic Information Of what racial/ethnic group do YOU consider yourself a member? Including yourself, how many people live in YOUR household? Including yourself, how many people in YOUR household are employed? How many motor vehicles are available to people in YOUR household? Were any of these vehicles available today for YOU to make this trip? Supplementary Questions There were a few other questions that were also deemed necessary, but that could be imputed from information provided in the survey sheets and in the mandatory questions listed above. These include the following: ROUTE NUMBER? What time did you get on THIS ROUTE? Did you TRANSFER or CHANGE to THIS ROUTE? Will you TRANSFER or CHANGE ROUTES to complete your trip? 2-6 Cambridge Systematics, Inc.

23 How many TRANSFERS or ROUTE CHANGES will you make on this trip? What ROUTES (in order) will you take on this trip? Cambridge Systematics, Inc. 2-7

24 Figure 2.2 Metro Transit 2008 Transit On-board Survey Questionnaire 2-8 Cambridge Systematics, Inc.

25 Cambridge Systematics, Inc. 2-9

26

27 3.0 Sampling Plan The data collected from the 2015 transit on-board survey will be used to study transit rider patterns and to support regional travel demand forecasting. Therefore, it was vital that the data collected from the survey spanned all weekday routes, throughout the day and included information from all route directions. In order to ensure this, a detailed sampling plan was developed to support field implementation. The survey includes Metro Transit weekday main-line fixed routes other than the UW circulator routes, i.e. Routes Routes 80-84, Supplemental School Day routes, and paratransit were not included in the survey. 3.1 SURVEY APPROACH The 2015 transit on-board survey was a function of three different survey efforts: An on-to-off survey that captures detailed information about rider boarding to alighting patterns; An on-board survey that was either self-administered using a pen and paper approach or through a personal interview format using a tablet; and Boarding and alighting counts that were conducted in conjunction with the on-board survey. Route Information The routes covered in the on-to-off survey include: 2, 3, 4, 5, 6, 10, 13, 14, 15, 16, 18, 19, 28, 30, 38, 40, 47 and 70. These routes either average over 500 boardings per day or are regarded as routes with unique rider patterns. Routes included in the on-board sampling plan are divided into two categories: pen-and-paper routes and tablet routes. Crews were instructed to staff one bus for a certain amount of time. Due to route interlining, most routes had a mix of tablet and paper surveys. Routes targeted in the tablet portion of the survey were 2, 4, 5, 6, 13, 16, 18, 20, 21, 22, 32, 40, 50, 51, 52, 67 and 70; and Routes 1, 3, 10, 11, 12, 14, 15, 17, 19, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 44, 47, 48, 49, 55, 56, 57, 58, 71, 72, 73 and 75 were mostly surveyed using traditional paper surveys. Targets The primary goal for the 2015 transit on-board survey was to collect information from at least 10 percent of riders on the routes of interest in Madison using either Cambridge Systematics, Inc. 3-1

28 pen-and-paper forms or personal interviews (tablet). The estimated weekday ridership on the routes included in the survey was about 45,000 riders based on a sample of farebox boarding records from Metro Transit. Therefore, the number of usable surveys is expected to be about 4,500. The target for the on-to-off sampling plan was to survey at least 20 percent of trips on the 18 routes of interest. The routes included in the on-to-off survey report nearly 35,000 daily boardings. The expectation was that on-to-off surveys would be collected from an overwhelming majority of riders on the sampled trips. The goal was to collect on-to-off data from about at least 6,500 riders on these routes of interest. 3.2 SAMPLING PLAN The sampling approach was designed to meet the survey data requirements at a disaggregate route-direction-tod (time-of-day) level. This was done to ensure that the data collected are truly representative of transit riders in the region. Time Periods Trips that occur between 6:00 AM and 9:00 PM on weekdays were obtained from the December 2014 block database provided by Madison Area Transportation Planning Board staff. These trips formed the universe for the survey process and were included in a database that served as the input for the sampling plan. Each trip was assigned to one of the four unique time periods: AM Peak (6:00 AM - 9:00 AM), Mid-Day (9:00 AM 3:00 PM), PM Peak (3:00 PM 6:00 PM) and Night (6:00 9:00 PM). Trips that started before 6:00 AM or after 9:00 PM were not included in the database for developing the sampling plan. In total, 1,658 trips were identified in the trip database in the periods of interest. Our analyses reveal that the 1,658 trips of interest were distributed across 197 blocks. These blocks were further broken down by time-of-day, which resulted in 423 sub-blocks. Each sub-block consists of routes belonging to one time period. The sub-blocks were viewed as the smallest units for the sampling plan. If a sub-block was selected, then every trip within a sub-block would be surveyed. Conversely, if a sub-block was not selected, then no trip in that sub-block would be included in the survey sampling plan. 3-2 Cambridge Systematics, Inc.

29 Sampling Approach A three-step approach was utilized in developing the sampling plans: Survey Targets Separate targets were established at the outset for the on-board and on-to-off surveys. These targets became a key part in the development of the sampling plan. For the on-to-off survey, 20 percent of the trips on the routes of interest were targeted to be surveyed with a goal of collecting on-to-off information from percent of riders on these trips. These trips were distributed for every unique combination of route, direction, and time-of-day that were included in the on-to-off data collection plan. The on-board sampling plan (both paper surveys and tablet surveys) targeted surveys from at least 10 percent of riders on every combination of route, direction and time-of-day. Completes Per Hour Routes surveyed using personal interviews had a lower completion rate per trip than pen-and-paper surveys. Based on previous efforts, it was determined that each surveyor would be able to complete three to four personal interviews per hour (combination of participation rates, loads, and survey length). The team assumed that three surveyors would be assigned on each vehicle to ensure that the targeted number of surveys may be attained. For the paper surveys, response rates from the previous Madison on-board survey were utilized to determine the number of trips to be included in the sampling plan. Selection Procedure The blocks in the database were categorized according to time-of-day: (up to) four categories AM peak (6:00 AM 9:00 AM), Mid-Day (9:00 AM 3:00 PM), PM Peak (3:00 PM 6:00 PM) and Night (6:00 PM 9:00 PM). These unique combinations of blocks and times-of-day served as the unit of selection for the sampling process. An optimization sampling engine was developed in excel to select sub-blocks according to priorities until the surveying targets were met. Sampling Results An excel-based optimization engine was developed to support three different sampling plans on-to-off survey sampling plan, tablet-based on-board survey sampling plan, and paper-based on-board survey sampling plan. Three simple rules were established to support the trip selection: Cambridge Systematics, Inc. 3-3

30 Sub-blocks that had a higher percentage of usable trips were prioritized over other sub-blocks. If a sub-block for a particular time period was selected, the team aimed to include other sub-blocks from the same block in the sampling plan. This allowed survey teams to ride on the same vehicle for a longer duration; thereby minimizing layover times. If a certain block was included in the sampling plan for the tablet survey, then it was not included in the paper survey (and vice-versa). Table 3.1 summarizes the number of sub-blocks selected, the number of trips selected and the estimated vehicle revenue hours involved in the sampling plan for the on-to-off survey and on-board survey at an aggregate level. The trips included in the sampling plan were reviewed twice but found to be sufficient to meet survey targets. The two reviews were conducted at the following times: Findings from the pretest were reviewed to determine whether additional trips were to be included for some routes. Additionally, the team also continuously monitored the survey effort to identify whether any major weather events would impact ridership and/or affect the team s effectiveness. Table 3.1 Sampling Plan Design Sampling Plan Total Qualified Trips Total Selected Trips Total Sub-blocks Selected Selected Vehicle Hours On-to-Off Survey 1, Pen-and-Paper Survey Tablet Survey Source: Sampling Plan Developed by Cambridge Systematics in January Cambridge Systematics, Inc.

31 4.0 Survey Management Plan After the development of the sampling plan, a detailed survey management plan was laid out by Dikita Enterprises. This survey management plan was used to outline the requirements and expectations of the onboard survey. In addition, the survey management plan was designed to provide the survey team with a detailed understanding of the challenges associated with data collection and to outline the best practices and frameworks to collect data effectively. This section of the report outlines the survey management plan developed for the Madison Metro Transit on-board survey. 4.1 IDENTIFY KEY CHALLENGES The data collection effort in Madison was extremely complex and required careful planning by team members. Consideration was required to ensure that the final sample collected through the effort would be consistent with industry standards. At a very early stage, the team identified key challenges that must be addressed in order to deliver a high quality product. The complexities fall into two categories typical on-board survey challenges and project-specific challenges and include the following: Typical On-board Survey Challenges Multiple Surveys. For the Madison on-board survey effort, the team conducted two survey types. The first survey was an on-to-off survey that was conducted during the first week of data collection. The purpose of this survey was to collect information about boarding and alighting bus stop pairs and supplement it with boarding and alighting counts at each stop. Passengers were not required to fill in any information; instead, they were handed a card upon boarding the bus, and were asked to hand the card back when they alighted the bus. The second survey was a typical on-board questionnaire in which passengers were asked details about their transit trip, household demographics, and person-level information. Boarding and Alighting Counts at Stop Level. It is necessary to determine the average number of boarding passengers for each trip to support survey weighting and expansion methodologies. During the On-to-Off survey, boarding and alighting pairs along with boarding/alighting counts at each stop will be collected. These sample trips are likely to be included in the onboard survey and therefore that data will be used for expanding the survey responses from the onboard survey. However, there will be trips that will be sampled in the on-board survey that may not have been included in the On-to-Off. In those instances, boarding and alighting counts will be collected simultaneously with the onboard survey. Cambridge Systematics, Inc. 4 1

32 Project Specific Challenges Interlining Routes. In Madison, a bus may change routes at the end of a previous route s trip. The complexity from an on-board survey perspective manifests when a passenger boards the bus on Route A and alights on Route B. When collecting on-board survey data, information is typically synthesized by route. As a part of quality control routines, boarding and alighting stops are validated for a specific route. When passengers are inquired about the route they took, the stop that he/she boarded and what stop he/she alighted, special consideration must be given to the possibilities that these stops may not be on the same route. Ordinary business rules may not apply, and post collection processing must account for these multi-route movements before assessing whether the record is reasonable or not. Different Survey Methodologies. The collection methods included paper surveys, online surveys, and personal interviews using tablets. Each methodology required different software, hardware, processing, and training considerations. The paper surveys and the online surveys were completed by the passenger with little to no intervention by the surveyor while the personal interviews were managed exclusively by the interviewer. Every survey received, whether by paper or as a data file (via tablets and online) needed to be tracked and related to a trip, which is related to route, time, and direction. Each methodology, therefore, required certain protocols to ensure that each survey was associated to its proper trip. Scheduling of UW-Madison Students. UW students recruited by the Traffic Operations and Safety Laboratory needed to be trained to administer the surveys. The availability of students for long assignments needed to be considered given their varying class schedules and other commitments. Crowding in the UW Campus Area. The Metro system is used for short trips on crowded buses near the University of Wisconsin campus and near downtown. There are some challenges associated with such type of crowding particularly related to survey completion using a personal interview approach. Therefore, the survey team had to be flexible in carrying paper forms on the tablet trips to ensure that respondents had alternative means of completing surveys. Each of these challenges was considered when designing and finalizing the survey approach. 4.2 SURVEY FIELDWORK METHODOLOGY There are many interrelated activities involved in survey planning, beginning with the creation of necessary documentation for training, processes, and survey procedures. This section outlines the survey methods and modes that were used, 4 2 Cambridge Systematics, Inc.

33 survey techniques, and day-to-day procedures. The planning and approach described here were applied for both the on-to-off and the on-board surveys. Methods to Engaging Riders A multi-mode survey approach was proposed and utilized for this effort in order to adequately capture respondent information through best practices when it comes to variations in route type such as high (crowding) and low ridership routes, short trippers, and key interest routes. Another benefit of using multimode collection was to give the respondent multiple options to complete the survey. The Madison Metro Transit on-board survey consisted of two separate surveys for collecting passenger s travel and trip characteristics. The first survey collected boarding and alighting pairs and counts at each bus stop on selected trips. The second survey collected origin and destination data, along with other passenger demographic data. A total of 18 routes were included in the on-to-off survey while the remaining 34 routes had boarding and alighting counts conducted at the bus stop level. Passengers were surveyed using the tablet instrument on a total of 17 bus routes. The remaining 35 routes were surveyed using a self-administered questionnaire approach. Different approaches were designed to administer the surveys. approaches are discussed below for each survey type. On-to-Off Survey Procedures These This survey focuses on collecting boarding to alighting information from riders along with total boarding and alighting counts at the stop level on trips selected in accordance with the sampling plan. Routes selected for the on-to-off survey were prioritized using the following criteria: Either have a weekday average daily ridership of over 500; or Be deemed routes of special interest by Madison Metro Transit (or both). The goal was to target a response rate of 90 percent on the selected trips/itineraries. Riders would be handed a bar-coded survey card as they boarded the bus by an interviewer standing at the front entrance. The card would then be collected from each passenger as they alighted the bus by interviewers standing at each available bus door. On most trips that have are known to have at least 20 passengers, the survey team would place one surveyor at each door on each bus for selected vehicle trips. Cambridge Systematics, Inc. 4 3

34 Each surveyor would be tasked to carry a handheld device that includes a barcode reader to scan each card as it is distributed and collected. Typically, the surveyor in the front of the bus would focus on scanning and distributing the cards to boarding passengers at each stop as well as collecting the cards from exiting passengers. The surveyor at the rear would focus on scanning and collecting the cards from alighting passengers. This process allows the collection of boarding and alighting pairs as well as conducting counts at the bus stop level. If a passenger refused to take the card when boarding the vehicle or when exiting the vehicle, surveyors would scan a barcode to indicate a refusal at that stop, thereby capturing the boarding and/or alighting count. The on-to-off survey was designed to be performed prior to the on-board survey to avoid any procedural issues during data collection. The survey was performed between Monday and Thursday and no data was collected on Friday, Saturday, or Sunday. Passenger Count Procedures For those trips included in the on-board survey but not the on-to-off survey, boarding and alighting locations counts would be collected at the bus stop level. Two separate methods and approaches for collecting the boarding and alighting counts were implemented. For routes surveyed using the tablet-based personal interview method, one individual was placed on the bus with a handheld device in order to enter the number of boarding and alightings per stop. For routes surveyed using the self-administered questionnaire, each surveyor (located at the front door and back door) was equipped with a handheld scanning device. These surveyors scanned the barcode of the questionnaire as the passengers take the survey upon boarding the bus and then scanned the barcode of the survey when the passenger returns the survey at their alighting stop. Passengers that refused the survey would be scanned a default number so that all counts at the stop would be reflected accurately. Self-Administered Survey Procedures Surveyors were asked to distribute surveys and pencil to all boarding passengers and scan the bar-coded serial numbers of each survey distributed at the time of distribution to capture the boarding location using the scanner. For most routes, there were two surveyors on each trip (one each located at the front and back doors) that were tasked with distributing surveys and pencils, assisting respondents with any survey related questions and collecting the surveys and pencils back from the passengers as they alight the vehicle. 4 4 Cambridge Systematics, Inc.

35 For routes not included in the on-to-off survey, surveyors employed a methodology that also captures the counts at the stop level using the handheld scanners. Passengers were encouraged to complete the survey before alighting and instructed to return by mail if they cannot complete it before departing. These passengers were also offered an option to take the survey online. Tablet-based Personal Interviews For trips personal-interview trips using a tablet, a slightly different methodology was employed (Figure 4.1). In order to have an adequate number of completed surveys on each trip, a minimum of two interviewers conducted interviews. Using a randomized method, surveyors approached passengers with a tablet in hand and collected responses to preprogrammed questions. In addition to the survey questions found on the paper survey, each tablet survey contained the following: Surveyor ID Trip ID Vehicle number Date and time of survey A completion score (valid, review, discard) Duration of survey Number of completions by surveyor Validation rules especially for transfers When a passenger reported not having time to complete a survey or reported that personal interviews were inappropriate, alternative means were employed. The first additional option was a web option (online survey). The surveyor was trained to provide the rider with a card labeled with a web address pin number (which will become his login ID). This login system allows the programmer to identify which route, direction, and time of day the rider received the web invitation. Further, it ensures that the passenger was actually invited to take a survey. The second additional option was for the surveyor to hand out a paper survey to complete and mail back. As in the case of the web survey, the paper survey was tracked. It must be noted that procedure is a departure in previous efforts where it was determined that different methodologies (tablet-based personal interviews vs. paper self-administered surveys) should not be mixed. Mixing the methods did not pose a problem since the paper surveys were tracked and a passenger counter was used to track boarding and alighting information on the bus. Cambridge Systematics, Inc. 4 5

36 Figure 4.1 Tablet Interview Screenshot 4 6 Cambridge Systematics, Inc.

37 Field Operations Coordination The data collection schedule was shared with Metro Transit operations departments and staff. The team coordinated with garage/division, security, and administrative staff to share information about scheduled data collection dates, data collection locations, routes being surveyed, and the number of supervisory and survey staff that will be on property. The equipment used during the survey administration included ten-inch tablets loaded with tablet program etrip, and a proprietary mapping software. The handhelds were equipped with GPS and barcode scanning technology and loaded with Ridecheck Plus software. The hardware was tested for performance, and the battery was charged each night to ensure that there were no issues during data collection the following day. Field Data Retrieval All data collected by all modes (tablet, paper, and web) were uploaded into a custom data management system, called Trip, in Microsoft Access format. The team developed a data coding scheme that ensured that all closed ended responses would be attributed with unique coded values and open ended items would be coded at the back-end, if necessary. Once response choices were assigned individual numeric values during design, the survey was programmed to capture passenger responses using these pre-selected coded values. Open ended responses were researched and coded when applicable. For example, if a respondent mentions that their trip purpose is other and writes in sightseeing, it will be recoded to the recreation purpose. Surveyor Training A customized Surveyor Training Manual that outlined the project s purpose, administrative matters, transit terminology, survey equipment, on-board procedures, and daily routines was developed. This manual was finalized after the pilot test. In order to provide surveyors with a head start, prior to the training session, each surveyor was required to view a set of training videos that provided them with details about the technology to be used for the on-board survey. All surveyors were cross trained in order for the surveyor to be able to: Conduct the On-to-Off survey Conduct the intercept passenger survey using the tablet devices Conduct the self-administered survey (pass out paper surveys and complete trip logs) Capture the boarding and alighting counts at the stop level Cambridge Systematics, Inc. 4 7

38 Since there was a lot of cross-training among survey staff to maximize surveyor efficiency, the training session went over, in great detail, the key information for each collection method being used for this study. Fieldworkers were also trained on the importance of interpersonal skills as it relates to interacting with the passengers to improve efficiency. Interlined Route Assessment Trips were surveyed in clusters of consecutive trips within a run or block. The use of trip clusters sampled from the same run or block allows for efficient sampling and, therefore, reduces data collection costs. The use of clustering consecutive vehicle trips also has the advantage of stratification by direction, because most runs consist of trips alternately traveling inbound and outbound (or east/west), and over different times-of-day. Because interlining is so prominent in Madison, there were several opportunities to survey multiple routes in a single assignment. However, this sampling methodology poses some challenges. For instance, passengers may board a surveyed trip and remain on the vehicle after the trip ends and the vehicle changes to a different route. For such occurrences, surveyors were trained on how to appropriately interview passengers to determine if they were transferring to another route but remaining on the bus after a route change. For the self-administered paper questionnaire, the data entry website was designed to capture boarding and alighting locations from both the current trip as well as the next/previous trip. Bus-stops were recoded to the first/last stop on the appropriate trip if it was identified that riders rode on the system for more than one trip. Survey Assignments Survey assignments were generated based upon the sampling plan parameters. Survey plan administrators identified which blocks/runs need to be surveyed, at what time of day, and using which approach. Once generated, assignments were clustered together by geography and surveyor availability to maximize efficiencies in staff and materials to the extent possible. Starting points for most assignments for both the on-to-off survey and the onboard survey began at either the Metro Transit bus garage located at 1101 East Washington Avenue, which is centrally located on the Madison Isthmus, or at transfer centers, such as the North Transfer Point. Survey administrators, keeping in mind the availability of the student surveyors, clustered assignments for particular days around a common location with other similar assignments, to the extent possible. Clustering assignments geographically also allowed surveyors to begin and end their runs at the same 4 8 Cambridge Systematics, Inc.

39 location, which played an important role in crew transportation, which is discussed in the next sub-section. Efforts were also made by survey administrators to minimize the effects of interlining on the surveying results. The assignment of non-sampled trips on to trips that needed to be surveyed were identified and avoided. To help facilitate the assignment of survey runs, supervisors asked students to supply their availability to work in advance. Scheduling software was employed to help distribute individual assignments to the student surveyors. A number of other logistical challenges must be addressed in every on-board transit survey effort. Survey plan administrators must develop assignments which adhere to the sampling plan, distribute those assignments to crew members while balancing project needs and crew availability, help facilitate the transportation of the surveying crew in the field to their assignments, and satisfy the other various technical and material needs of the crews. Detailed information about the logistics and implementation are included in Appendix B. Cambridge Systematics, Inc. 4 9

40

41 5.0 Survey Pretest Cambridge Systematics, in association with Dikita Management Services and University of Wisconsin executed a survey pretest on January 28 and 29, The pretest was conducted to test the variety of topics including survey equipment, hardware and software, field implementation methodology, and questionnaire design. All on-to-off and on-board survey methodologies were tested including scanning, paper distribution, boarding and alighting counts, and personal interviews. Special attention was assigned to streamline the handling of interlined routes in an assignment, especially when passengers did not alight at the end of a trip. Dikita supervisors trained staff on the night prior to the pretest on both the uses of the handheld and the tablets, as well as the proper procedures to associate each survey to a trip or stop. A few key observations from the pretest are listed below: 5.1 ON-TO-OFF SURVEY FINDINGS The methodology for the on-to-off pretest incorporated a handheld computer with preloaded trip information route, trip, bus stops, latitudes/longitudes and scheduled bus stop arrivals. The handheld included a barcode reader and GPS technology to allow the surveyor to associate each serial-numbered form to a route/trip/bus stop at both the boarding and alighting stop. The software in the handheld allowed the displayed stops to advance as the bus traveled along its route. Two surveyors per bus were used in the pretest. One surveyor was positioned in the front and the other at the rear. The surveyor in the front was responsible for scanning and distributing the scan on barcode for all boarding passengers and scanning the off barcode for those alighting from the front of the bus. The surveyor in the rear was responsible for scanning off of all passengers returning the card as they alighted. Four trips were tested for the on-to-off survey procedures. In total, 176 on-to-off surveys were collected by the crew on these trips. Key findings, along with survey recommendations are listed below: Finding #1 Issue. At stops that typically included excessive boardings and alightings, the survey teams found difficulty recording the patterns using the scanners. In fact, at certain stops, especially those involving the boarding and alighting on the UW Cambridge Systematics, Inc. 5 1

42 campus, the surveyors were unable to handle 12 or more people getting on or off without interrupting the flow of passenger traffic. Recommendation. For stops with excessive boardings and alighting, the survey team decided to devise an alternative strategy. A ridecheck form with pre-printed stops that gives the surveyors an opportunity to use a pen and paper to write the range of sequential serial numbers at the appropriate stops without scanning each form was given on high activity routes. Under this approach, the team would scan the returned serial numbers to the appropriate bus stop at the end of the trip. For high activity alighting stops, surveyors could bundle all surveys returned at a particular stop with the stop id on the top of the bundle. The surveyor could then scan all the forms within the bundles and assign them to the appropriate bus stop. Finding #2 Issue. It was observed that surveyors did not always scan refusals correctly. Scanning refusals is important for two reasons: First, including refusals helps develop a correct control total for total boarding and alighting activity at a bus stop. Second, including refusals in the total counts allows the team to develop response rate metrics, if required. Recommendation. It goes without saying that the surveyors must be trained to use the proper bar code properly so the counts are accurate. The team decided to emphasize scanning during training. Specifically, it was explained that every passenger must be included either as a participant or a refusal in order to have accurate boarding counts. The team also redesigned the survey clipboards and the trip log sheet such that the refusal codes were readily available on both equipment pieces. Finding # 3 Issue. In reviewing the collected data, it was observed that some surveyors scanned on when they should have scanned off, or vice versa. Recommendation. The barcode reader is programmed not to allow scanning of the same barcode on the same trip using the same barcode reader. In other words, if the surveyor on the front of the bus scans a serial number on, then scanning on again on the same trip by this same surveyor will not be recorded as a valid entry. However, if the surveyor in the rear of the bus scans the same serial number on instead of off, it will register on again. Therefore, it was determined 5 2 Cambridge Systematics, Inc.

43 that the only way to correct this issue would be through detailed training and post-processing based on timestamp and handheld number. Finding #4 Issue. The GPS device on the scanner was observed to flicker and stall on certain locations in the campus. The surveyors did not know how to disengage the GPS. In addition, one of the scanners malfunctioned. Recommendation. Surveyors can be trained to disengage the GPS and manually advance to the appropriate stops. These techniques were subsequently covered during training. Finding #5 Issue. Occasionally, the surveyors tried to manually use the number pad to key in boardings and alightings. When conducting the on-to-off, only one method may be utilized on the scanner scanning barcodes either as on, off, refusal on, or refusal off and nothing else. Recommendation. It was decided that the appropriate methods to use to record different types of information would be discussed during training. Combining different methods using the scanner was determined to result in inaccurate results. Finding #6 Issue. There were a few instances where the passenger boarded a trip and did not alight until a subsequent trip (interlining). Recommendation. In order to determine passengers who boarded on a trip and alighted on a subsequent trip, it was determined that careful examination during post processing will be required. Matrices for subsequent trips may help identify and remedy these situations 5.2 BOARDING AND ALIGHTING COUNTS FINDINGS The same handhelds used in the on-to-off surveys were also used for conducting boarding and alighting counts. Boarding and alighting counts are necessary for those trips where on-board surveys are conducted but not on-to-off surveys. Two assignments covering seven trips over two days were covered as part of the pretest. The surveyors were able to count the boarding and alighting passengers (one surveyor at each door) using the scanner s numeric keys. There were no apparent issues with technology or methodology. During the actual survey, if there is only one surveyor performing boarding and alighting counts, the surveyor must be positioned mid-way in the bus to observe both doors. Cambridge Systematics, Inc. 5 3

44 5.3 PAPER ON-BOARD SURVEY FINDINGS The 2008 on-board survey had been conducted entirely using a paper survey approach. Several of the University of Wisconsin staff that were supporting the pretest had participated in this effort and were very familiar with the procedure. The goal of the effort was to hand out a survey to every passenger as they boarded the bus. Surveys would be scanned using the same scanner used for the on-to-off survey. The scanner would record the stop information using a GPS and this information would serve as an additional validation check for boarding and alighting information provided by the respondents in the surveys. Paper surveys were distributed on 15 trips for three assignments over two days. As with the on-to-off, crowding became an issue at certain times. Distributing or attempting to distribute surveys to each boarding passenger was a challenge because some passengers walked by the surveyor before the surveyor had a chance to hand out the survey to them. The handheld was also used to track a refusal code when a passenger refused to participate in the survey to ensure that the total counts were accurate. A total of 189 passengers boarded over the 2 day period, of which 138 (73%) accepted the survey. Of those who accepted the survey, 114 (83%) returned (mailbacks not included). Of the 114 returned surveys, almost 50percent were easily geocoded and validated without any additional processing while another 38percent needed additional processing. Only 13percent were unusable. Findings Paper questionnaires were of the 8.5 X 14 variety and were provided in unfolded packages of 50. They were a little cumbersome to carry, but a clipboard improved the surveyors performance. There was a minor change in procedure from 2008 to improve the quality of the data collected. It was deemed important that the surveyors fold the surveys when they are returned to put them into the envelope for the appropriate trip to avoid any confusion about the trip on which the survey was collected. Trip logs were also utilized to record the range of serial numbers distributed on the trip. The data were processed via an integrated website program that allowed the assimilation of scans from the handheld, trip logs, and returned paper surveys to be processed simultaneously. Geocoding and validation routines were executed as the survey data were entered, giving the data entry personnel opportunities to correct obvious errors. 5 4 Cambridge Systematics, Inc.

45 5.4 TABLET ON-BOARD SURVEY FINDINGS It was extremely helpful for the tablet programmer to be part of the pretest exercise. Because Madison is heavily interlined, there was a concern that people may not know what route they boarded/alighted or could possibly board on one trip and alight on another. As a part of the initial programming, the ability for the surveyor to have a list of the bus stops on the prior and subsequent trips was included in the tablet program. In total, 12 trips over four assignments were surveyed over the course of two days. A total of 137 people were approached, 77percent agreed to participated in the survey (84 accepted the personal interview, while 22 passengers agreed to take a paper survey with them). Of the 84 passengers interviewed, 73 (87%) completed the survey. Of those who completed the survey, total of 86percent were deemed usable without any additional processing, and an additional 2 usable surveys were returned by mail. Issue #1 Observation. The average number of minutes to complete the survey was twelve minutes. There were surveys that were seven minutes long and there were some surveys that were over 25 minutes long. The program calculated the duration by recognizing the time when the surveyor began and the time the surveyor closed the last screen. Upon careful review, it was determined that surveyors did not close the survey in many instances, allowing time to elapse which resulted in longer survey times. Therefore, this measure cannot be used reliably to predict performance in the pretest. Recommendation. It was decided that surveyors would be trained to close the final survey screen so survey completion metrics may be tracked properly. Issue #2 Observation. Certain questions were deemed critical and must be answered in order that the survey be considered a usable and completed survey. In the pretest design, some of those questions were asked in the latter half of the survey. It was felt that completion rate could be improved by moving those questions earlier in the interview. Recommendation. The team redesigned the tablet interview questionnaire and moved the vital questions as close as feasible to the beginning of the interview. These questions include information about race, household size, employment, auto availability, and number of vehicles in the household. The interlining questions were also redesigned to get better responses. Cambridge Systematics, Inc. 5 5

46 Issue #3 Observation. Surveyors were concerned about standing while conducting the interviews due to crowding. They were jostled among passengers who were trying to move past the interviewers to the exit locations, and the surveyors were concerned about dropping the tablet. Recommendation. While not ideal, it was suggested to surveyors to hand the tablet to the respondent to complete the survey, if crowding became a major issue. This was especially true for the demographics questions that had a lot of options and could be completed faster by the respondent themselves. Issue #4 Observation. The survey team referred to the assignment using the term blocks while the bus drivers understand the term run. This becomes important when surveyors are trying to make sure that they are getting on the right vehicle for the survey. Recommendation. Since the survey team did not have the run numbers, the recommendation was to instruct the surveyors to refer to route and start time when confirming the right bus to board. Issue #5 Observation. Although battery life was not challenged during the pretest, it was observed that the decrease in battery life was evident. The team noted that battery life may become an issue if the surveyor did not hibernate the device when not in use. Recommendation. The Dikita team decided to increase the number of tablet units to the inventory to ensure backup tablets would be available during the field implementation. Also, the team anticipated that they would have to load more assignments on the spare devices during implementation. Issue #6 Observation. Crowding is not uncommon in Madison for short periods of time on certain sections of the system. Personal interviews are more difficult when the surveyor doesn t have a seat next to the passenger. Recommendation. The option of allowing the passengers to take a paper survey proved to be a viable option for overcrowding, short trips or time constraints. On routes that are standing room only, it may be desirable to distribute paper surveys and record the serial numbers for tracking purposes. On short routes or routes where we may miss an opportunity to interview passengers in hard-to-reach areas, more than two surveyors may be needed to collect enough surveys. 5 6 Cambridge Systematics, Inc.

47 Issue #7 Observation. Many challenges will be overcome with proper training. Recommendation. The team estimated that at least 2 sessions of classroom training may be necessary to learn all the techniques required to conduct the different surveys. In addition, a field training dry run would be very useful. The training video was also revised so that students who did not attend the initial training could learn via video, training manual, and OJT (on-the-job training). It was also proposed that extensive training would be conducted during surveyor orientation with an emphasis on how to use the tablets, how to approach passengers, and how to phrase the questions to obtain the correct data. Cambridge Systematics, Inc. 5 7

48

49 6.0 Field Implementation Data collection is perhaps the most important part of the entire on-board transit survey task. The quality of the end product the final database containing the raw details from which route, trip, and ridership profiles are built is dependent upon a well-executed and well-managed data collection process. This process hinges on the flawless implementation of the main survey in the field. The field implementation process includes the application of lessons learned during the survey pretest (Section 5); surveyor training, the daily management of surveying efforts; the definition of, and emphasis on collecting, valid surveys; and, the quick retrieval of data for tracking purposes, and the geocoding of trip locations. The complete list of subtasks associated with field implementation reflects the complex nature of on-board data collection. The advent of technology and a greater emphasis on certain data have pushed these jobs onto the front burner of survey administrators in the field. All of these subtasks must be addressed in real time during data collection for the survey to reach its overall project goals. 6.1 TRAINING AND RECRUITING Based on the parameters outlined in the sampling plan, administrators concluded that surveyors and six supervisors would be needed to adequately staff the field survey throughout its entirety. This number also reflected the need to compensate for surveyor attrition and the unforeseen unavailability of staff. The University of Wisconsin-Madison, as stated previously, was responsible for recruitment of surveyors, while supervisors were drawn from the employed staffs of all three firms. The vast majority of surveyors were hired from the ranks of graduate and undergraduate students affiliated with the school s College of Engineering, and more specifically, attached to the college s Traffic Operations Safety Laboratory (TOPS Lab). Thus, these surveyors had a working knowledge of statistical sciences and transportation engineering and modeling, fields related to key aspects of the on-board transit survey project. A small number of surveyors were recruited from outside of the University, hired as short-term temporary workers to fill minor gaps in the scheduling where no student surveyors were available due to their regimented class schedules. Cambridge Systematics, Inc. 6 1

50 Some of the surveyors were recruited and hired in time for the pretest survey, which took place over three days in late January These surveyors underwent one day of classroom training followed concurrent training and field data collection. The bulk of the surveyors were recruited following the pretest and they, along with most of the original pretest surveyors, undertook comprehensive training prior to the start of the main field test. Supervisors and technicians from Dikita conducted this comprehensive training session the weekend prior to the first week of the main field survey, during which on-to-off surveys were scheduled to be collected. Topics covered by the trainers included the fundamentals of survey data, data collection procedures, quality protocols, and the management and manipulation of field equipment and technology. A field training session followed the classroom session, overseen by Dikita and UW staff. A supplemental classroom training session, focusing exclusively on the onboard paper and tablet questionnaires and handheld devices used for the boarding and alighting counts, was conducted on March 2, 2015, at the College of Engineering. As the main field on-board survey progressed, supervisors administered individualized on-the-spot training for surveyors as needed. 6.2 DAILY MANAGEMENT Without careful management from survey administrators, it s possible some routes will be over-surveyed, while others will be under-surveyed, and the resulting data will stray too far away from the requirements of the sampling plan. Without careful oversight, some surveyors may be overworked, while others underutilized, and still others are in need of additional training. In short, a number of issues can materialize without daily management of the field implementation and deep analysis of various metrics gleaned from raw survey and trip data in real time. Survey Timeframe Survey administrators needed to track trends in survey collection, data processing, and logistics, all while working within a limited timeframe. Surveyors conducted the on-to-off survey for four days beginning February 23. After the completion of this task, the paper and tablet on-board surveys, plus boarding and alighting counts, were conducted for four days a week for three weeks beginning March 2. As in any surveying effort, surveyors missed some scheduled trips. The primary cause for missed trips was surveyor unavailability. To collect data on these missed trips, two weeks of supplemental surveying were scheduled 6 2 Cambridge Systematics, Inc.

51 for mid-april as part of the survey administration plan. The first week of this supplemental survey was earmarked for missed on-to-off survey trips, while the second week was allocated for missed on-board survey trips. These dates were chosen by Metro Transit and the Madison Area Transportation Planning Board to capture their observed annual peak ridership period late Winter/early Spring, a time when the Autumn and early Winter holidays are over, university students are in school, and some commuters have yet to turn toward their bicycles as their commuting mode of choice. Track Data Collection Trends One of the key daily managerial tasks for survey administrators pertained to daily monitoring of data collection efforts. As part of the sampling plan, goals for the number of valid surveys were established for each route by time of day. Schedules were built off the sampling plan that assigned crews to survey passengers of each unique combination of route, direction, and time of day that would meet these targets. The most critical application of the data analyses regarded the adherence of the field implementation results to the sampling plan. If the data collected over- or under-sampled many routes or time periods, then the final database of route, trip, and ridership information is likely to be less accurate for some system segments. Thus, it is crucial for survey administrators to develop tools to quickly parse data from several streams of input and develop an accurate picture of the progress being made by surveyors in the field. To ensure these goals were met, a tracking tool was developed. This tracking tool allowed administrators, analysts, and supervisors to view data collected by route and time of day. These data included the number of valid surveys, the number of questionable surveys, the number of refusals, and other operations metrics collected in the field. From these data, survey administrators were able to track the number of trips surveyed, surveys collected, and measure progress against anticipated rates and goals as dictated by the sampling plan. Figure 6.1 shows a portion of the tracking tool developed by CS to monitor the field implementation of the survey. Cambridge Systematics, Inc. 6 3

52 Figure 6.1 Tracking Tool for On-Board Survey Analyze Data Collection Metrics Through a constant analysis of this information, administrators made adjustments to the field implementation plan as needed. Administrators directed resources from routes where data collection exceeded goals and expectations and toward routes where data collection was proving to be difficult. Other routes which showed higher refusal rates were assigned additional trips. After identifying this higher refusal trend for certain routes clustered near the South Transfer Point, administrators responded by placing the best performing surveyors and crews on those assignments. In addition to analyzing data and making necessary adjustments to assignments, survey administrators also used the tracking data to monitor data entry processes. This was important for two reasons, one immediate and the other long term: First, decisions regarding changes such as retraining individuals whose trips had incomplete data were made using these data; and, Second, the quality of information stored within the final survey results database is dependent on the accurate transfer of data from paper questionnaires and electronic devices to a database format, and this can be tracked using the data entry dataset. Data collected during the on-to-off survey and boarding and alighting counts via the handheld scanners were designed to be uploaded nightly, processed quickly, and reviewable for administrators. However, data processing tasks associated with the handheld scanners were not done in real time. But, because there were no issues with the on-to-off data process, these delays had no impact on survey data quality. 6 4 Cambridge Systematics, Inc.

53 On-board survey data collected via electronic tablets also were uploaded nightly and ready for review the next morning. These data were then incorporated into tools which tracked the progress of the field survey and also integrated into the final survey database. Track Surveyor Performance Other important metrics tracked daily by administrators and supervisors included the performance of individual surveyors, surveying crews, electronic equipment, and the supply of paper surveys. The tracking of individual surveyors and surveying crews afforded supervisors with an opportunity to provide constructive feedback to surveyors, while the tracking of the performance of tablets and scanners allowed technicians to troubleshoot issues and improve hardware and software functions. Metrics collected included the number of paper questionnaire refusals per surveyor and the average elapsed time of tablet interviews, among other statistics. Tracking surveyor and crew data also allowed administrators to identify the strongest surveyors on each survey platform. Tracking workforce metrics allowed supervisors to determine which surveyors were working too many hours and which were being underutilized. Track Paper Questionnaires In 2008, surveyors distributed the self-administered paper questionnaires on board buses atop a clipboard. This constrained the number of surveys distributed on a trip to the number of clipboards carried by the surveying crews. For the 2015 on-board self-administered paper questionnaire, a method was used in which surveyors were placed at the front of the bus and handed surveys to all passengers. Therefore, in 2015, the number of surveys distributed was constrained only by refusals of riders to participate. With a goal to collect of 4,500 valid surveys, roughly 60percent of which were likely to be from paper questionnaires, an initial printing of 4,000 paper questionnaires in English was ordered in mid-february from Alphagraphics in Madison. This followed a printing of 300 paper questionnaires for the pretest survey in January. Additional printings were required owing to higher than expected participation rates. Administrators noticed the increased demand for paper questionnaires via the tracking tools. Cambridge Systematics, Inc. 6 5

54 So, during the third and last week of the on-board survey, 1,000 more paper questionnaires were printed. This supply was nearly exhausted and two more printing runs of 1,000 surveys each were authorized for the supplemental on-board survey in April. In total, 7,000 English-language paper questionnaires were printed from mid- February to mid-april, excluding the 300 surveys printed for the pretest survey. In addition to the 7,300 total English-language surveys created, the MATPB requested surveying crews have available questionnaires in two other languages Spanish and Hmong. Staff selected these two languages based on their relative high usage rates of the system. Translations of the paper questionnaire were made by Interpreters Cooperative of Madison (ICM), a consortium of local experts and native speakers. Not many responses were collected using non-english surveys. For Hmong, the Hmong Daw, or White Miao, dialect was chosen for the survey upon the recommendation of ICM since it utilizes the Romanized alphabet and was the most commonly spoken Hmong dialect in the Dane County region. Moreover, the Hmong White Miao dialect is usually understood by all Hmong speakers. For the main field survey, 500 Spanish-language and 250 Hmonglanguage questionnaires were printed by Alphagraphics. 6.3 DATA RETRIEVAL This section highlights how data from different parts of the survey were retrieved and entered for final use. On-to-Off Survey Data For the on-to-off survey, data were collected in the handheld scanner devices carried by each member of the surveying crew. The scanners were tasked with recording the paired boarding and alighting locations of passengers as they boarded and got off the vehicle. Surveyors standing at the front of the bus scanned preprinted survey cards with unique bar code identification numbers and handed one to each rider as they boarded the vehicle at a bus stop. The scanners, equpped with a GPS unit and specialized software loaded with trip data, would record the boarding location associated with a particular bar code number. 6 6 Cambridge Systematics, Inc.

55 As passengers alighted, the cards were handed back to the surveyors to scan again, at which point the scanner would record an alighting location for the unique bar code number and store all of the information in a database. These data were then converted into an electronic database which tracked the boarding and alighting stop for each survey record. Refusals were tracked using a special refusal code number. The on-to-off survey database was provided in a ready-to-use format that can support survey expansion and included information about the route, direction, time-of-day, boarding bus-stop and alighting bus-stop. When all the data, including refusals were counted, this dataset served as the input for boarding and alighting counts. Boarding and Alighting Counts The procedures for the boarding and alighting counts are similar to that of the on-to-off count data since both data collection methodologies utilize the same equipment and software. For trips included in the on-board survey that were not surveyed as part of the on-to-off, the surveyor sitting at the rear end of the bus was given a scanner and asked to record boarding and alighting counts. The boarding and alighting count database does not provide information about travel patterns. Instead, they only provide a measure of activity at each stop. The scanner data were converted into an electronic database which recorded boarding and alighting activity for each stop for every trip that was surveyed. On-Board Tablet Survey Data The electronic tablet devices used by surveyors to conduct on-board personal interviews includes all the data to be collected. In addition, the software was also used to perform checks to determine the validity of the information being reported. Additionally, Dikita technicians loaded the tablets with trip and assignment data, surveyor information, and other features which can be used to develop tracking reports. At the end of each surveying night, supervisors initialized the tablets, accessed the internet, logged into a data portal created by Dikita for data collection, and uploaded the survey data collected on that day to the site and to a separate master database. Overnight, a series of reports were generated which could also be accessed by survey administrators through the Dikita web portal. On-Board Paper Survey Data Entry Unlike the electronic data collection platforms, there is no automated system by which data collected from the self-administered paper questionnaires can be uploaded quickly into a database. Cambridge Systematics, Inc. 6 7

56 Dikita developed a web portal through which UW data entry staff could enter the specifics of each paper questionnaire, along with trip log information for each assignment including refusals and other conditions of the assignment This data portal platform was designed to also act as the data reporting and retrieval system utilized by administrations (Figure 6.2). Data were entered through this portal even during the data collection process, and the data entry process was accelerated at the back end to ensure that the full dataset was turned over for analysis as soon as possible. The dataset could be accessed using any machine with internet access, and it provided enough flexibility for the survey team to enter at different locations, using different systems, and at different times of day. Both the data entry portal and the tablet survey program provided for onthe-fly geocoding of trip origins, boarding, alighting, and destinations using a custom geocoding engine (see Section 6.5). The web portal in which data were uploaded by UW supervisors was also used by survey administrators to download raw data, reports, and abstracts. A series of spreadsheets provided different data summaries useful to survey administrators. Figure 6.2 Dikita Data Entry Portal for Paper Questionnaires 6 8 Cambridge Systematics, Inc.

57 7.0 Survey Data Cleaning and Expansion The next stage in the project was to conduct a thorough analysis of the data collected, assess the quality of the records, and to perform a detailed survey expansion to ensure that the survey data represent regional travel patterns. The 5,900 survey records were given weights in order to represent the estimated 45,000 daily boardings while accounting for over- or under-represented responses. 7.1 PRELIMINARY SURVEY CLEANING During the survey s design, key questions essential from a modeling and data analysis perspective were identified, as described in Section 2.3. Only questionnaires either on paper or through the tablet that have each of these questions filled out with reasonable information were considered complete. For the purposes of tracking the progress of the field implementation of the survey, a nightly report detailing the number of completed surveys by route, trip, and time of date was generated. This report, complied through the tracking tool using data from UW supervisors and Dikita s data portal, also contained the number of surveys for two additional categories: questionable and rejected. Surveys submitted via paper questionnaire or electronic tablet that contained information for one or more of these questions which could not be immediately verified as reasonable were marked as questionable. Further, if a submitted survey either lacked information for any of these critical questions or had illegible or nonsensical information, the survey was marked as rejected. UW supervisors, to whom all trip logs and paper surveys were returned by surveying crews, were trained by CS staff to quickly scan the submitted questionnaires, located the key questions, determine if reasonable information was provided by the rider, and calculate the number of surveys in each of the three categories for each trip. Similar information for surveys collected through the tablets was provided by Dikita and its data web portal. 7.2 PRELIMINARY DATA COLLECTION RESULTS More surveys were collected than originally anticipated. This holds true for both the on-board survey and the on-to-off survey. Cambridge Systematics, Inc. 7 1

58 Table 7.1 shows the number of returned surveys for the on-to-off, paper, and tablet surveys. In total, nearly 8,000 on-board surveys (against targeted 4,500) and another 8,000 on-to-off surveys were collected as part of this effort. It is important to note that a significant number of questionable surveys, especially those listed in the tablet interview section were found to be valid using back-end reprocessing. The numbers in Table 7.1 also demonstrate the exceptional response to the self-administered paper questionnaire. The preliminary rejection rate for paper questionnaires calculated at this stage of data collection was 13 percent; The survey rejection rate for the tablet personal interviews was almost the same at 14 percent; This suggests that the quality of the paper-based on-board survey data was as good as the data collected from the tablet survey. Other categories examined include: Data from mailbacks, which are paper surveys returned to Madison Metro Transit via the prepaid postage address on the bottom back of the questionnaire; Surveys taken from the website, which riders accessed via a QR reader or web address listed on the questionnaire near the mailing label; and Personal paper interviews, which were personal interviews conducted using pen and paper questionnaires either at the request of the rider or due to technical difficulties with the tablets. Table 7.1 Surveys Returned Survey Type On-to-Off Survey Surveys Deemed Valid Surveys Deemed Questionable Surveys Deemed Rejected Total Surveys Collected Pen-and-Paper Survey 4, ,361 Mailbacks Website Tablet Survey 1, ,119 Paper Personal Interview Total 6, ,025 7,816 Source: CS Analysis of 2015 Madison Transit On-board Survey It must be noted that the data collection effort did not cover all the trips originally outlined in the survey sampling plan for two reasons: 7 2 Cambridge Systematics, Inc.

59 First, the survey response rates were much higher than expected, and therefore, survey targets were met far more quickly than originally anticipated. Second, due to the high response rates, the survey crews had to include three members on each trip, thereby limiting the total number of trips that the crews could cover within their allocated budget. Table 7.2 outlines the number of trips from which some valid survey information was collected. There may have been some additional on-board survey trips from which no valid information was collected. Table 7.2 Trips Surveyed During Field Effort Survey Effort AM MD PM NT Grand Total On-board Survey Paper On-board Survey Tablet Boarding-Alighting Counts On-to-off Survey Source: CS Analysis of 2015 Madison Transit On-board Survey 7.3 GEOCODING EFFORTS Valid surveys, as defined in the Madison Metro Transit on-board survey business rules, must contain accurate geographic data for all four components of a rider s trip. These four components in chronological order are the trip s origin, bus boarding, bus alighting, and destination locations. If accurate geocodes defined as valid locations of these trip components do not exist, then the survey data are largely useless for modeling and summary purposes. A valid location is any address, known landmark, intersection, or any other geographically-identifiable spot which can be converted into geographic coordinates on the Earth. These geographic data must exist either in the tablet or paper survey questionnaires or should be inferred using other data provided by the respondents. Typically, the presence of poor geographic data is one of the most common reasons for a survey to be rejected instead of being counted as valid. Therefore, the Madison Metro Transit on-board survey project team instituted a number of technical and procedural systems to improve the geocoding process across all survey platforms. These systems were designed to elicit better geographic data from the participants, surveyors, and data entry editors; to provide an enhanced Cambridge Systematics, Inc. 7 3

60 automated geocoding engine at the point of data entry; and to flag potential problems for review. These systems can be thought of as a three step process: Offline, real time geocoding of tablet data; Geocoding of information from paper surveys at the data entry stage; and An intense data-driven process conducted at the back end for locations which could not be geocoded by the tablet or data entry programs, yet that contained reasonable geographic information. This section describes each step of the geocoding process. Automated Geocoding in Tablet A number of features contained in the tablet program offer improvements to the typical geocoding process. The tablet system runs a program called etrip and contains proprietary mapping software. The etrip program shepherds the rider-surveyor team through the collection of the origin, boarding, alighting, and destination data, which can be viewed on one screen with four panels for each component. Riders provide addresses, intersections, known landmarks, and bus stops to satisfy the requirements of the survey, while the program works to transform these locations into geographic coordinates using an offline geocoding process. The panels are colored individually red or green depending on whether a valid geocoded location has been obtained through the data collected from the rider. A map of the proposed trip is generated on one of the next screens and serves as a visual aid for the surveyor to verify the survey data with the rider. At the end of the survey, the data are added to the etrip database for upload later that evening. Surveys with verified geocoded locations for the rider s origin, bus boarding, bus alighting, and destination are ready for analysis once added to the master database. Any questionable or rejected surveys that include some type of geographic data were deemed candidates for a more intensive, targeted geocoding process overseen by analysts at the back end of the data collection process. 7 4 Cambridge Systematics, Inc.

61 Geocoding in Data Entry Portal For the paper surveys, Dikita established a procedure by which UW data entry editors could perform geocoding as the data were entered into the data entry database portal. The process was not as comprehensive or interactive as the tablet etrip process, but editors were able to view a map of the trip which the data portal program builds using the trip information provided. Just like the tablet program, the data entry portal processing engine flags surveys as either questionable or valid. Any questionable or rejected surveys that include some type of responses to the geographic data question were deemed to be candidates for a more intensive, targeted geocoding process overseen by analysts at the back end. Automated Geocoding in the Handheld Devices While not technically considered geocoding, it is important to note that the handheld scanner devices employed for the on-to-off survey and boarding and alighting counts contained data and programs which recorded boarding and alighting location information. Data downloaded from this scanner served as a secondary source of information for data validation. Back End Geocoding CS analysts developed a detailed QA/QC method by which some of the records with missing geocoded information could be regeocoded. This process utilized the geocoding engine based in TransCAD. CS staff developed tools which corrected for errors in spelling or naming convention for addresses, intersections, and landmarks. Through this process, CS analysts regeocoded nearly 1,000 records with some of them being reclassified as valid surveys from an earlier label of questionable or rejected. 7.4 FINAL DATASET The on-board survey dataset was then tested for completeness using two additional steps: First, the team assessed whether the trips outlined by the respondents were reasonable based on the route on which the surveys were conducted; and Second, the team compared the on-board survey dataset against the boarding and alighting counts collected for the trips to ensure that there was consistency in travel patterns between the two datasets. After this round of analysis, the team identified nearly 6,000 usable records that served as the basis for survey expansion (Table 7.3). As expected, the information collected from the personal interviews had a higher usability rate (87 Cambridge Systematics, Inc. 7 5

62 percent) as compared to the self-administered surveys. Of the remaining 13 percent of tablet surveys that were not included in the final survey, a significant portion were discarded because the survey was not completed. Overall, nearly 76 percent of all surveys data collected during the effort were included in the final dataset. Table 7.4 breaks down the completed surveys by route. Table 7.3 Usable Records by Mode of Data Collection Method Total Surveys Collected Final Usable Surveys Usable Rate Self-Administered Survey 5,658 4,040 71% Personal Interview 2,158 1,874 87% All Modes 7,816 5,914 76% Source: CS Analysis of 2015 Madison Transit On-board Survey 7.5 SURVEY DATA EXPANSION To ensure that the survey dataset accurately represents regional transit usage and travel patterns, the on-board surveys must be expanded using the on-to-off survey and the boarding-alighting counts collected as part of the study. The goals of survey expansion include the following: Take into account of the effects of route, directionality and the temporal dimension on transit ridership. Accurately represent the information of transit flow patterns for every route segment. To the extent possible, the transit flow patterns were matched at a bus stop level. Accurate boarding and alighting data were collected at a bus stop level for every route, at different time periods. On-to-off information was also collected from the passengers of certain routes. These two datasets provided a more comprehensive picture of systematic travel patterns for the bus routes. Therefore, the on-board surveys were weighted to match the flow patterns captured by boarding/alighting count and on-to-off survey and the daily routelevel ridership information provided by Metro Transit. An iterative proportional fitting (IPF) process, which is a widely used mathematical application to estimate cell values of a multi-dimensional table, was used to support the survey expansion. In the process, the individual cells of a matrix are adjusted iteratively to match the row and column (marginal) totals of the matrix, which remain fixed. In cases where the on-to-off survey also exists, the on-to-off data serve as an input data to conduct matrix level modifications using simple adjustment factors. 7 6 Cambridge Systematics, Inc.

63 Table 7.4 Usable Surveys by Route Route Usable Surveys Route Usable Surveys Source: CS Analysis of 2015 Madison Transit On-board Survey Data Processing Steps The key steps in the survey expansion process are as follows: The survey expansion process was designed to be conducted at the most disaggregate level possible route, direction, and time-of-day. Cambridge Systematics, Inc. 7 7

64 All three datasets (on-to-off, boarding-alighting counts, on-board) were summarized by bus-stop. Both the on-board and the on-to-off were summarized for a pair of boarding and alighting bus-stops. For each route, direction, and time-of-day, attention was paid to break down bus-stops into different segments. This step helped the survey team to identify the best way to aggregate bus-stops to support a robust expansion procedure. The three different segments were: Bus-stops that had activity in all datasets; Bus-stops that only had activity in some datasets; and Bus-stops that had no activity in any of the datasets. Survey Expansion Steps All non-university routes in the Madison system were part of the on-board data collection process. However, some routes were part of the on-to-off survey while other routes only had boarding-alighting counts. Therefore, it was not possible to develop one standard expansion procedure for the entire database. In fact, three different survey expansion procedures were designed and implemented for this study (Table 7.5). The survey expansion was conducted for each unique combination of route, direction, and time-of-day. The survey expansion process was carried out using the programming software R. Table 7.5 Survey Expansion Types Expansion Type On-board Survey On-to-Off Survey Boarding/Alighting Count Expansion Type 1 Expansion Type 2 Expansion Type 3 Source: CS Analysis of 2015 Madison Transit On-board Survey Expansion Type 1 Routes that had all three types of data available, a three-step process was conducted. First, the on-board surveys were expanded to match the on-to-off flows using a matrix adjustment procedure. This adjustment process can be best described as follows: The adjustment was a simple cell-to-cell expansion for those bus-stop pairs where data existed in both the on-board survey as well as the on-tooff survey. For pairs of bus-stops that lacked data from either the on-board survey or from the on-to-off survey sample, adjacent bus-stops were combined until 7 8 Cambridge Systematics, Inc.

65 both on-board and on-to-off survey cells were non-zero and then the aggregated bus-stop pairs would be expanded as a group. The boarding and alighting count data were then summarized for each stop. The adjusted matrix from the first step then underwent an IPF to match the control totals from the boarding and alighting count data. For each iteration in this second expansion process, total boarding was the first dimension and total alighting was the second dimension. Multiple iterations were run until the adjusted matrix matched the boarding and alighting control totals. Finally, average ridership by route, direction and time-of-day was used as an additional control total. This data accounts for any day-to-day fluctuations observed in ridership on the days of data collection. Expansion Type 2 For those combinations of route, direction, and time-of-day that only had boarding and alighting count data to support survey expansion, the expansion process was simplified. The boarding and alighting count data were then summarized for each stop. A dual-stage IPF served was then employed. For each iteration in this second expansion process, total boarding was the first dimension and total alighting was the second dimension. Multiple iterations were run until the adjusted matrix matched the boarding and alighting control totals. After this step, average ridership by route, direction and time-of-day was used as an additional control total. This data accounts for any day-to-day fluctuations observed in ridership on the days of data collection. Expansion Type 3 For those combinations of route, direction, and time-of-day that only had on-tooff survey data to support survey expansion, the expansion process was as follows: A matrix adjustment of the on-board survey was conducted to match the flow information provided by on-to-off survey. The adjustment was a simple cell-to-cell expansion for those bus-stop pairs where data existed in both the on-board survey as well as the on-tooff survey. For pairs of bus-stops that lacked data from either the on-board survey or from the on-to-off survey sample, adjacent bus-stops were combined until both on-board and on-to-off survey cells were non-zero and then the aggregated bus-stop pairs would be expanded as a group. After this step, average ridership by route, direction and time-of-day was used as an additional control total. This data accounts for any day-to-day fluctuations observed in ridership on the days of data collection. Cambridge Systematics, Inc. 7 9

66 It must be noted that a majority of records were expanded using the most detailed expansion process (Table 7.6). Table 7.6 Survey Expansion Results Expansion Type On-board Survey On-to-Off Survey Boarding/Alighting Counts Number of Records Expansion Type 1 3,697 Expansion Type 2 1,126 Expansion Type Source: CS Analysis of 2015 Madison Transit On-board Survey 7.6 SURVEY EXPANSION CHECKS The survey expansion process discussed in the previous section adjusts the weights of the collected surveys in order to match the boarding and alighting patterns outlined by on-to-off survey and the boarding-alighting counts at a route, direction and time-of-day level. Since the procedure was data-driven and involved several different types of aggregations of bus-stops, the team felt the need to compare the results of the survey expansion process against independent, observed data summarized by Metro Transit. The data provided by Metro Transit summarized total rider activity at a busstop level for March Since the survey did not included University routes, weekday summaries from Routes 1-78 were used in the comparison. In total, the reported bus-stop activity was about 46,135 boardings. This is slightly different from the route-level ridership provided by Madison Metro Transit that was used in survey expansion (43,626). For comparison purposes, the Metro Transit reported bus-stop level boardings were scaled Using this robust database, two types of checks were conducted: Aggregate checks using activity measured for planning districts; and Disaggregate checks using activity measured for major bus-stops. Planning District Comparison Figure 7.1 outlines 25 planning districts that were used in the comparison of the weighted survey against the observed ridership data. As a first step, all the survey records were uniquely assigned to one of the planning districts. Similarly, each of the bus-stops in Metro Transit s database was also assigned to a planning district Cambridge Systematics, Inc.

67 Both the expanded survey database and Metro Transit s observed database were then aggregated using the planning district variable. Table 7.7 presents the total boardings for each of the 25 districts that derived from both on-board survey and are compared with the data provided by MPO. The table is sorted by total observed boardings because districts that have heavy transit activity are of greater importance from a planning perspective. As expected, District 11, which also includes the University, had the highest observed ridership at 12,400 boardings. This same district also has the highest observed ridership in the on-board survey database (12,500). The difference between the two datasets is only 1 percent. The survey results match pretty well with the targets for the top 5 districts. These top 5 districts constitute almost 63 percent of all the boardings in the region. In fact, there is only one district, District 17, where the absolute difference in numbers between the two datasets exceeds 500 boardings. This analysis suggests the survey database does a reasonably good job in matching observed boarding data. Cambridge Systematics, Inc. 7 11

68 Figure 7.1 District Geography Table 7.7 Comparison of Total Boardings at District Level District Survey Boardings MPO Boardings Percent Difference Difference 11 12,505 12, % ,679 4, % ,971 3, % ,833 3, % ,581 2, % ,958 2, % ,008 2, % ,159 1, % ,179 1, % ,432 1, % % % % Cambridge Systematics, Inc.