Travel Survey and Model Update Final Report, Study notes of Calculus

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Arizona State University

Travel Survey and Model Update

Final Report

Maricopa Association of Governments

Acknowledgements

This MAG report is based on project deliverables provided to MAG by ASU. MAG staff would like to

specifically acknowledge Dr. Ram M. Pendyala, Dr. Sarah Elia Volosin, Dr. Daehyun You and Dr. Venu

Garikapati, who provided the contribution to the project.

List of Tables

• 1. Introduction
• 2. Arizona State University Travel Survey Design and Administration
  • University Travel Survey 2.1. Determination of Sample Size and Margin of Error in Travel Characteristics for the Arizona State
  • 2.2. Design of a Robust Survey Process
  • 2.3. Design of the Online Survey Instrument
  • 2.4. Survey Administration and Response Tracking
  • 2.5. Data Preparation and Quality Analysis
  • 2.6. Survey Data Expansion
• 3. Analysis of Observed ASU Student Travel Characteristics
  • 3.1 Demographic Analysis of Students
  • 3.2 Students’ versus Other Adults’ Travel Characteristics
  • 3.3 Undergraduate versus Graduate Student Travel
  • 3.4 Travel Characteristics by Living Arrangement
  • 3.5 Travel Characteristics by Working Status
  • 3.6 Exploration of Intra-Campus Trips
• 4. ASU Student Travel Demand Model Update
  • 4.1 Trip Generation Model................................................................................................................
    • 4.1.1 Model Framework
    • 4.1.2 Application of the Trip Generation Model
    • 4.1.3 Allocating ASU Trip Ends to TAZs
  • 4.2 Location Choice Model
    • 4.2.1 Model Framework
    • 4.2.2 Model Estimation
    • 4.2.3 Location Choice Models for Graduate Students
    • 4.2.4 Location Choice Models for Off Campus Undergraduate Students
    • 4.2.5 Location Choice Models for On-Campus Undergraduate Students
  • 4.3 Mode Choice Model
• 5. Conclusions
• 6. References
• Appendix A: Survey Instrument Design
• Appendix B: IRB Approval
• Appendix C: Publicity Materials
• Appendix D: Screenshots of ASU Survey Website
• Figure 2.1 Overall Survey Design Process List of Figures
• Figure 2.2 Flow of Survey Design Content
• Figure 2.3 Survey Screen: Map Interface for Identifying Locations
• Figure 2.4 Select Survey Advertisement Strategies
• Figure 2.5 Date and Day of Week Profile of Responses to ASU Travel Survey
• Figure 2.6 Percent of Total Trips Flagged
• Figure 2.7 Percent of Total Persons Filtered
• Figure 2.8 Unweighted versus Weighted Data for Undergraduate Student Sample..................................
• Figure 3.1 Student and Staff Time of Day Distributions
• Figure 3.2 Student and Staff Average Trip Length by Time of Departure...................................................
• Figure 3.3 Mode Share Within Each Trip Purpose by Student Level
• Figure 3.4 Undergraduate and Graduate Student Time of Day Distributions
• Figure 3.5 Mode Share Within Each Trip Purpose by Student Level
• Figure 3.6 Time Of Day Profiles for Students
• Figure 3.7 Time Of Day Profiles for Faculty and Staff
• Figure 3.8 Time of Day Distributions by Student Living Arrangement
• Figure 3.9 Mode Share Within Each Trip Purpose by Living Arrangement
• Figure 3.10 Time of Day Distributions by Student Working Status
• Figure 3.11 Mode Share Within Each Trip Purpose by Working Status
• Figure 3.12 Time of Day Distribution for Intra-Campus Trips
• Figure 3.13 Mode Share for Intra-Campus Student Trips
• Figure 4.1 Disaggregation of ASU-Based Trips
• Figure 4.2 Home Locations of ASU Students by Campus
• Figure 4.3 Filtering for Trip Rate Calculation
• Figure 4.4 ASU Campus Polygons................................................................................................................
• Figure 4.5 Example of ASU-based Trips using GIS Method
• Figure 4.6 Description Method of Identifying ASU-based Trips
• Figure 4.7 Identifying Home-Based ASU Trips
• Figure 4.8 Campus Buildings Allocated to Each TAZ
• Figure 4.9 ASU Parking Areas Allocated to Each TAZ
• Figure 4.10 Trip Generation Procedure
• Figure 4.11 Market Segmentation for Location Choice Models
• Figure 4.12 Location Choice Estimation and Calibration
• Figure 4.13 Iterative Process of Model Estimation
• Figure 4.14 Observed and Predicted Trip Lengths: Graduate Student Home-Based
• Figure 4.15 Observed and Predicted Trip Lengths: Graduate Students Non-Home Based Peak
• Figure 4.16 Observed and Predicted Trip Lengths: Graduate Students Non-Home Based Off Peak
• Table 2.1 Sample Size Calculations for Undergraduate Student Population
• Table 2.2 Sample Size Calculations for Graduate Student Population
• Table 2.3 Sample Size Calculations for Faculty Population...........................................................................
• Table 2.4 Sample Size Calculations for Staff and Administrator Population
• Table 2.5 Summary of ASU Travel Survey Sample Profile
• Table 3.1 Student Demographic Characteristics
• Table 3.2 Trip Rates by Purpose for Staff and Students
• Table 3.3 Trip Selected Travel Characteristics by Student Level
• Table 3.4 Daily Activity Participation by Student Level
• Table 3.5 Analysis of Trip Chaining Behavior
• Table 3.6 Selected Travel Characteristics by Living Arrangements
• Table 3.7 Daily Activity Participation by Living Arrangements
• Table 3.8 Selected Travel Characteristics by Working Status
• Table 3.9 Daily Activity Participation by Working Status
• Table 3.10 Intra-Campus Trip Counts for Various Student Groups
• Table 4.1 Number of Persons and Trips Available in the Modeling Dataset
• Table 4.2 Campus Polygon Buffer Size Sensitivity
• Table 4.3 ASU-Based Trips by Method of Identification
• Table 4.4 Results of Two Methods for Intra-Zonal Trip Consideration.......................................................
• Table 4.5 Trip Generation Rates
• Table 4.6 Allocation to ASU TAZ’s: Off Campus Undergraduates
• Table 4.7 Allocation to ASU TAZ’s: Graduate Students...............................................................................
• Table 4.8 Allocation to ASU TAZ’s: On Campus Undergraduates
• Table 4.9 Model Estimation Sample Sizes
• Table 4.10 Graduate Students Model: Home Location
• Table 4.11 Graduate Students Model: Non-Home Based Peak Location
• Table 4.12 Graduate Students Model: Non-Home Based Off Peak Location
• Table 4.13 Off Campus Undergraduates Model: Home Location
• Table 4.14 Off Campus Undergraduates Model: Non-Home Based Peak Location....................................
• Table 4.15 Off Campus Undergraduates Model: Non-Home Based Off Peak Location..............................
• Table 4.16 On-Campus Undergraduates Model: Dorm-Based Peak Location
• Table 4.17 On Campus Undergraduates Model: Dorm-Based Off Peak Location
• Table 4.18 On-Campus Undergraduates Model: Non-Dorm Based Peak Location
• Table 4.19 On Campus Undergraduates Model: Non-Dorm Based Off Peak Location...............................
• Table 4.20 Mode Choice Model Alternative Specific Constant Calibrated

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the train and it is time to take stock of the travel demand characteristics of ASU in light of the presence of

the light rail system. No study of ASU travel demand had been undertaken following the opening of light rail

service. The previous survey of ASU travel demand characteristics was undertaken in Fall 2007, a full year

before the opening of the light rail line. As such, it has been extremely valuable to undertake this ASU travel

data collection and model update effort so that the MAG regional travel demand model accurately reflects

current and emerging activity-travel patterns that may be attributed to Arizona State University.

ASU travel data collection effort was designed in such a way that it was possible to collect detailed

information about activity engagement, time use, and trip chaining patterns. The motivation behind this

approach to ASU travel data collection is that MAG is currently undertaking the development of an activity-

based travel demand model system. In order to eventually develop and estimate an ASU travel demand

model that is compatible with and may be seamlessly integrated with the MAG activity-based travel demand

model, the data collection effort was deliberately geared towards collecting travel information in the activity-

based behavioral context.

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2. Arizona State University Travel Survey Design and Administration

2.1. Determination of Sample Size and Margin of Error in Travel Characteristics for the Arizona State University Travel Survey

This section describes calculations to determine the sample size and the margin of error in travel

characteristics for the Arizona State University travel survey. In the previous ASU travel survey conducted in

2007, response rates were generally found to be about 4-5% of the respective market segments, namely,

undergraduate students, graduate students, faculty, and staff. With the enhanced web-based survey

implementation and the New Apple IPAD raffle draw for the 2012 survey, it was expecting that response

rates can be potentially doubled to about 8-10%. While it may be useful to determine sample sizes required

for various levels of desired precision on different travel characteristics, it is also of value to identify the

degree of precision that can be expected if the survey achieves the envisioned 8-10% response rate.

In order to make sample size calculations, two travel characteristics are considered. They are the basic travel

characteristics that one would like to achieve a high degree of precision. The first is overall average daily trip

rate per person, which is an appropriate measure of total travel demand. The second is percent of individuals

driving alone, which is a good measure of mode usage. All sample size calculations furnished in this memo

are based on a desired confidence level of 95%, the standard value that is used for statistical purposes. If d is

the degree of precision, then it can be said that the true population value of the characteristic of interest lies

within  d of the sample estimate. For example, suppose the estimated average trip rate is 4.2 trips per person.

For the sample size obtained, and assuming a 95% confidence level, let 0.2 be the value of d. Then, it can be

said that the true average trip rate for the population of interest lies between 4.0 and 4.4.

For purposes of this survey, four demographic segments are considered. They are as follows:

1) Undergraduate students

2) Graduate students

3) Faculty

4) Staff

Additional segmentation is possible, but it is sufficient to view the sample size and precision estimates for

these four demographic segments to understand the implications for any other type of demographic segment

that may be of interest (such as students living on-campus, students who attend classes Downtown ASU

campus, and so on). The sample size calculation formulas require that one specify a degree of precision and

a standard deviation (or variance) for the travel characteristic (variable) of interest. The tables furnished in

this report provide sample size estimates for a range of precision levels – showing how the sample size

requirement increases with increasing level of precision – and documents the assumptions made in the

context of developing each table. Before proceeding to sample size calculations, it may be of value to quickly

review the population sizes for each market segment – but recognizing that the population size itself does

not have a direct bearing on sample size requirements, except that smaller samples may be sufficient for

populations that are small in size.

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It should be noted that the number of students attending different campuses add up to a value substantially

larger than 70,440 because of the double- and triple-counting of students who attend classes on multiple

campuses.

The numbers of faculty and staff on ASU campuses are available as of Fall 2009. Since then, ASU has hired

new faculty and staff, but there has also been an approximately equal amount of reduction. As such, the total

faculty and staff numbers are unlikely to be much different from figures available for Fall 2009. The faculty

and staff composition, as of Fall 2009, is as follows:

• Total ASU Faculty and Staff 12,

o Faculty 2,

o Staff and Non-Faculty 9,

 Administrators 93

 Professionals 2,

 Classified Staff 3,

 Graduate Assistants 2,

For purposes of calculating sample sizes, the person trip rate may be considered a continuous variable while

the mode usage may be considered a proportion (discrete) variable. For the continuous variable, the sample

size needed to achieve a degree of precision of  d with a confidence of (1- )100% is given by: 2 2

d

z s

n'

α/

where n’ = required sample size

d = degree of precision

s = standard deviation of travel characteristic of interest

z  /2 = standard normal distribution value corresponding to a (1- )100% confidence level

For small populations, a finite population correction may be applied to obtain the true sample size required

to achieve desired precision and confidence levels:

N n' n' n   1

where n = final sample size

N = population size

When N >>>>> n’ , then n is very nearly equal to n’.

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In addition to providing values for the desired precision and confidence levels, the analyst must also provide

a standard deviation for the travel characteristic of interest (person daily trip rate in this case) to compute

the sample size. An appropriate assumption for this value may be made in the absence of prior information

regarding the value of this standard deviation.

In the case of a travel characteristic that is discrete and the variable of interest is a proportion, the formula

for calculating sample size is as follows:

2 2 2 1 d z p( p) n' α/  

where p is the proportion of individuals in the population exhibiting the trait of interest (say, using single

occupant vehicle as the mode of transportation for traveling to and from ASU). In the absence of prior

information regarding the value of p , the analyst must make assumptions regarding its possible value – but

noting that the use of p =0.5 would serve the most conservative calculation of sample size requirements

(maximum sample size requirement is at an assumption of p =0.5). In addition, d is provided in terms of

percentage points converted to a decimal value. For example, if it is desired to determine modal split within

1 percentage point of the true population value, then the value of d is 0.01.

Table 2.1 shows the calculations for undergraduate student population. In this tabulation, all undergraduate

students are considered a single population regardless of their level and on- or off-campus living arrangement.

As the population size does not impact sample size calculations, except at low population sizes, it is sufficient

to view sample size and precision calculations for the undergraduate student body as a whole. The same

values are going to apply to market segments within the undergraduate student body, except for the finite

sample correction that may be warranted at small population sizes. As the survey is capturing on-campus

(within campus) movements, the average trip rate is assumed to be 10 trips per person (as opposed to the

usual 4 trips per person) and the standard deviation is assumed to be 4, a value that is reasonably

conservative from a sample size calculation perspective. If one were to assume that trip frequency is

approximately normally distributed in large samples, then an assumption that the standard deviation is 4 and

the mean trip rate is 10 implies that about 95 percent of the undergraduate student body has a daily trip

frequency between 2 and 18 (i.e., within 2 standard deviations of the mean). The project team believes that

this is a reasonable assumption as it is very unlikely that students are going to report more than 18 trips in

the survey, even if they made more trips in reality. The accompanying spreadsheet provides the ability to re-

compute sample sizes on the fly by just changing the value of the standard deviation in the corresponding

cell.

The sample size calculations suggest that it should be possible to obtain average daily person trip rate

estimates from the survey within 0.1 trips at a 95% confidence level, even with a response rate that is less

than 10 percent. For a precision level of 0.2 trips, and assuming the same confidence level of 95%, it is found

that the sample size that is required is just about 1,500 persons suggesting that ASU travel survey will

inevitably provide high levels of precision in terms of overall person trip rate, which is a key indicator of travel

demand. For the sample size calculations related to the modal split (single occupant vehicle proportion), a

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The remainder of this section presents similar tables for graduate students, faculty, and staff/non-faculty.

Table 2.2 presents the sample size calculations for the graduate student body. The same assumptions

regarding mean and standard deviation of person daily trip rate are made for the calculations furnished in

Table 2.2. For this population, assuming a 10 percent response rate, it appears that the average trip rate can

be estimated within 0.2 of the true population value. This constitutes a high degree of precision. Even if the

response rate is only about 5 percent, the degree of precision is 0.3 trips per person.

Table 2.2 Sample Size Calculations for Graduate Student Population Graduate Students Population 13878 Person Trip Rate Average 10 Modal Split SOV 0. Std Dev 4 Non-SOV 0. Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction 0.10 1.96 6147 4257 0.010 1.96 9604 5671 0.15 1.96 2732 2282 0.011 1.96 7937 5046 0.2 1.96 1537 1383 0.012 1.96 6669 4502 0.3 1.96 683 651 0.013 1.96 5683 4029 0.4 1.96 384 374 0.014 1.96 4900 3619 0.5 1.96 246 242 0.015 1.96 4268 3263 0.6 1.96 171 169 0.016 1.96 3752 2952 0.7 1.96 125 124 0.017 1.96 3323 2680 0.8 1.96 96 95 0.018 1.96 2964 2442 0.9 1.96 76 75 0.019 1.96 2660 2232 1.0 1.96 61 61 0.020 1.96 2401 2046 1.1 1.96 51 51 0.021 1.96 2178 1882 1.2 1.96 43 43 0.022 1.96 1984 1736 1.3 1.96 36 36 0.023 1.96 1816 1605 1.4 1.96 31 31 0.024 1.96 1667 1488 1.5 1.96 27 27 0.025 1.96 1537 1383 1.6 1.96 24 24 0.026 1.96 1421 1289 1.7 1.96 21 21 0.027 1.96 1317 1203 1.8 1.96 19 19 0.028 1.96 1225 1125 1.9 1.96 17 17 0.029 1.96 1142 1055 2.0 1.96 15 15 0.030 1.96 1067 991

With respect to modal split, the calculations are made assuming a value of p =0.5. This is an extremely

conservative estimate and it is unlikely that one-half of graduate student trips are made by drive alone.

However, assuming that p =0.5, then a response rate of about 10 percent would yield a precision of 2.

percentage points. In other words, if the sample estimate of SOV proportion is 50 percent, then the true

population value lies between 47.5 and 52.5 percent at a 95 percent confidence level. This is once again a

reasonably narrow band within which modal split is being estimated. However, in view of the importance of

estimating modal split accurately (particularly for transit analysis), efforts should be made to maximize

response rate for graduate students. The 2007 survey of ASU students generally showed that graduate

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students are more likely to respond to the survey than undergraduate students; as such, achieving a 10

percent response rate should be very much within reach.

Table 2.3 Sample Size Calculations for Faculty Population Faculty Population 3000 Person Trip Rate Average 7 Modal Split SOV 0. Std Dev 3 Non-SOV 0. Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction 0.1 1.96 3457 1606 0.010 1.96 9604 2286 0.15 1.96 1537 1016 0.015 1.96 4268 1762 0.2 1.96 864 671 0.020 1.96 2401 1334 0.3 1.96 384 341 0.025 1.96 1537 1016 0.35 1.96 282 258 0.030 1.96 1067 787 0.4 1.96 216 202 0.035 1.96 784 622 0.5 1.96 138 132 0.040 1.96 600 500 0.6 1.96 96 93 0.045 1.96 474 410 0.7 1.96 71 69 0.050 1.96 384 341 0.8 1.96 54 53 0.055 1.96 317 287 0.9 1.96 43 42 0.060 1.96 267 245 1.0 1.96 35 34 0.065 1.96 227 211 1.1 1.96 29 28 0.070 1.96 196 184 1.2 1.96 24 24 0.075 1.96 171 162 1.3 1.96 20 20 0.080 1.96 150 143 1.4 1.96 18 18 0.085 1.96 133 127 1.5 1.96 15 15 0.090 1.96 119 114 1.6 1.96 14 13 0.095 1.96 106 103 1.7 1.96 12 12 0.100 1.96 96 93 1.8 1.96 11 11 0.105 1.96 87 85

Table 2.3 presents sample size calculations for the faculty segment. For faculty and staff, different

assumptions have been made regarding the mean and standard deviation of person daily trip rate, as it is

likely that faculty and staff do not undertake the same number of trips (particularly within campus trips) that

students undertake. The average person daily trip rate is assumed to be 7 trips per person and the standard

deviation is assumed to be 3. These assumptions imply that, in large samples and assuming an approximately

normal distribution for trip frequency, 95 percent of the population makes between 1 and 13 trips per day

(2 standard deviations of the mean). It is reasonable to expect that the vast majority of faculty fall within

this range of trip frequencies; even if some faculty members make more than 13 trips, it is unlikely that they

Page | 11 Table 2.4 Sample Size Calculations for Staff and Administrator Population Administrators & Staff Population 9500 Person Trip Rate Average 7 Modal Split SOV 0. Std Dev 3 Non-SOV 0. Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction Margin of Error Conf Level (z-value) Sample Size Finite Pop Correction 0.1 1.96 3457 2535 0.010 1.96 9604 4776 0.15 1.96 1537 1323 0.015 1.96 4268 2945 0.2 1.96 864 792 0.020 1.96 2401 1917 0.3 1.96 384 369 0.021 1.96 2178 1772 0.4 1.96 216 211 0.022 1.96 1984 1641 0.5 1.96 138 136 0.023 1.96 1816 1524 0.6 1.96 96 95 0.024 1.96 1667 1418 0.7 1.96 71 70 0.025 1.96 1537 1323 0.8 1.96 54 54 0.026 1.96 1421 1236 0.9 1.96 43 42 0.027 1.96 1317 1157 1.0 1.96 35 34 0.028 1.96 1225 1085 1.1 1.96 29 28 0.029 1.96 1142 1019 1.2 1.96 24 24 0.030 1.96 1067 959 1.3 1.96 20 20 0.031 1.96 999 904 1.4 1.96 18 18 0.032 1.96 938 854 1.5 1.96 15 15 0.033 1.96 882 807 1.6 1.96 14 13 0.034 1.96 831 764 1.7 1.96 12 12 0.035 1.96 784 724 1.8 1.96 11 11 0.036 1.96 741 687 1.9 1.96 10 10 0.037 1.96 702 653 2.2. Design of a Robust Survey Process

The overall survey process is depicted in Figure 2.1. It should be recognized that this figure represents a

substantial simplification of the survey process; trying to capture all of the process mechanisms and feedback

loops within the constraints of a single figure is difficult. Nonetheless, the figure embodies the essential

elements of the process and reflects the level of coordination and care that must be exercised in designing

and implementing a ASU population travel survey.

Page | 12 Figure 2.1 Overall Survey Design Process

At the outset, the project team contacted three major entities of ASU survey administration to facilitate

coordination of the survey effort and the Arizona State University Office of the Provost, which is in charge

of all academic and student affairs at ASU. The Office of the University Registrar, which houses all student

records, is a unit of the Office of the Provost. The administration of a survey to the entire student population

(as well as faculty and staff) can be accomplished only with the cooperation and consent of the Office of the

Provost which has access to the universal e-mail address databases and is the only entity on campus

authorized to send out mass e-mail messages requesting participation in the survey. The project team also

contacted ASU Parking and Transit Services Office (PTS) to coordinate survey administration. PTS conducts

its own surveys on a periodic basis to gather data and obtain feedback about transportation needs and

options for ASU population (they do not conduct the equivalent of travel diary surveys). This office has a

plethora of secondary data including parking capacity and price levels (parking supply), number of parking

permits sold by pricing level and facility (parking demand), number of subsidized transit passes sold by

semester and population market segment, amount of utilization of the transit passes, and ridership on inter-

campus shuttles. This office also provided valuable input on the design of the survey and the questions to

be included in the survey. PTS sends out news and announcements to the entire ASU population on a

frequent and regular cycle; the office agreed to include information and reminders about this survey in all of

its electronic transmissions during the survey administration period. Finally, the project team coordinated

with the University Technology Office (UTO) to facilitate the deployment of the web-based online travel

survey. The survey was hosted on a third party server, but all announcements and reminders about the