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Origin-Destination Study External-External Trip Analysis UPWP Task 2.3 Origin-Destination Survey

980 North Jefferson Street Jacksonville, FL 32209 (904) 306-7500 www.northfloridatpo.com

7077 Bonneval Road, Suite 600 Jacksonville, FL 32216 (904) 296-0207 www.hntb.com

June 15, 2018

http://www.northfloridatpo.com/

http://www.hntb.com/

Origin-Destination Study for External-External Trips

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EXECUTIVE SUMMARY This study identifies vehicular trips entering the North Florida Transportation Planning Organization (North Florida TPO’s) planning area that includes Baker, Clay, Duval, Nassau, Putnam and St. Johns Counties. This report summarizes the data collection and estimation of trips passing through the region, or external-to-external (EE) trips. The results will be used in the validation and calibration of the North Florida TPO’s travel demand model, the Northeast Florida Regional Planning Model – Activity Based (NERPM-AB) which is being updated as part of the 2045 Path Forward Long-Range Transportation Plan.

Data was collected by placing temporary BlueTOAD™ devices and traffic counters at 17 external stations or locations at the edge of the NERPM-AB model boundaries. In total, 1,053,467 vehicles and 90,662 trucks were counted and the 17 locations over seven days. The BlueTOAD devices identified 442,809 vehicles with a Bluetooth™ device that passed one of the external stations and another of the 150 temporary or permanently-installed BlueTOAD devices during the study period. A total of 73,850 EE trip vehicles were identified. The data was separated into days and a.m., p.m., midday and off-peak periods to match the NERPM-AB requirements. A statistically significant sample occurred at all locations on daily basis, but sample sizes were not significant during some periods at all sites. Potential sources of sampling errors were identified that included overcounting of Bluetooth devices, vehicles that pass more than one external station and sampling bias based on socio-economic factors for Bluetooth device ownership. Corrections were made in the data where appropriate. Origin-destination trip tables were developed for each period in the model and reasonableness checks were performed. Only the daily origin-destination table is presented in this report and the tables for the other periods are provided electronically.

Major accomplishments of this study included:

This project demonstrated that using Bluetooth™ or other probe vehicle technologies for origin-destination studies provides a cost-effective and robust data set.

By working with TrafficCast® additional analysis reports and data queries were included in the North Florida system. These reports will be used to complete additional origin-destinations studies underway for the major truck terminals in the area and can be used in future corridor studies.

EE origin-destination studies were completed for each model analysis period at the locations studied to be used in model validation and calibration of the 2045 Long Range Transportation Plan update to the NERPM-AB.

Truck origins and destinations can be reasonably estimated using this approach.

The following additional analysis is recommended as part of future phases.

Ensure the data downloads occur from portable devices and are uploaded to the BlueARGUS™ software to provide more accurate expansion factors of the data.

Smart phones and other Bluetooth devices are becoming ubiquitous, and over time the market penetration rates are expected to increase since prior studies were performed in the region. However, the observed penetration rate in this study was higher than expected. Additional data is available from BlueARGUS that can be used to verify these penetration rates at the permanent BlueTOAD™ devices; however, budget was not available in this study to pursue acquiring additional samples.


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CONTENTS

Executive Summary ....................................................................................................................... i

Introduction ................................................................................................................................... 1

Purpose ..................................................................................................................................... 1

Methodology ................................................................................................................................. 1

Locations ................................................................................................................................... 1

Analysis Period .......................................................................................................................... 1

Data Collection Method ............................................................................................................. 4

Origins and Destinations Volumes ......................................................................................... 4

Traffic Volume and Classification Counts .............................................................................. 6

Expansion Factors and Total Volumes ...................................................................................... 6

Data Analysis ................................................................................................................................ 8

Sample Size .............................................................................................................................. 8

Tests of Significance ................................................................................................................. 8

Potential Data Errors ............................................................................................................... 10

Overcounting of Bluetooth Devices ..................................................................................... 10

Sampling Bias ...................................................................................................................... 10

Expansion Factors ................................................................................................................... 11

Results ........................................................................................................................................ 12

Comparison to NERPM-AB 2010 ............................................................................................ 20

Comparison to Alternate Methods of Data Collection ............................................................. 22

Findings and recommendations .................................................................................................. 25

Findings ................................................................................................................................... 25

Recommendations .................................................................................................................. 26

End Notes ................................................................................................................................... 27


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Figures Figure 1 – External Station Locations ........................................................................................... 2 Figure 2 - Regional BlueTOAD Devices ....................................................................................... 5 Figure 3 – Average Vehicles Per Day ......................................................................................... 14 Figure 4 - Weekday A.M. Peak Hourly Volumes ......................................................................... 15 Figure 5 - Weekday Mid-Day Average Hourly Volumes ............................................................. 16 Figure 6 - Weekday P.M. Peak Average Hourly Volumes .......................................................... 17 Figure 7 - Average Trucks per Day (Weekdays) ......................................................................... 18 Figure 8 - Weekday Mid-Day Average Hourly Truck Volumes ................................................... 19

Tables

Table 1 - External Station Locations ............................................................................................. 3 Table 2 - Summary of Data Collected ........................................................................................... 7 Table 3 – Test of Significance for Sample Size ............................................................................ 9 Table 4 - Expansion Factors ....................................................................................................... 11 Table 5 - Estimate of Average Weekday EE Trip Volumes ........................................................ 13 Table 6 - Adjusted NERPM-AB EE Matrix (Average Weekday) ................................................. 21 Table 7 - Comparison to Other Origin Destination Study Methods ............................................. 23


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INTRODUCTION

Purpose This study identifies vehicular trips entering the North Florida Transportation Planning Organization (North Florida TPO’s) planning area that includes Baker, Clay, Duval, Nassau, Putnam and St. Johns Counties. This report summarizes the data collection and estimation of trips passing through the region, or external-to-external (EE) trips. The results will be used in the validation and calibration of the North Florida TPO’s travel demand model, the Northeast Florida Regional Planning Model – Activity Based (NERPM-AB) which is being updated as part of the 2045 Path Forward Long-Range Transportation Plan.

This data is used for the validation and calibration of the North Florida TPO’s travel demand model, the Northeast Florida Regional Planning Model – Activity Based (NERPM-AB). The NERPM-AB model relies on data to forecast the trips that travel external-internal, internal-external and external-external within the region. Data is needed to verify the current trips that will be used to forecast future year conditions through the year 2045.

This study was performed in coordination with a study on truck trip origins and destinations within the North Florida TPO planning boundaries prepared for the Florida Department of Transportation (FDOT). Several of the data collection locations were redundant, and by coordinating the data collection and analysis cost savings were achieved for both the North Florida TPO and FDOT. The truck study includes additional origins and destinations within the planning area. The EE truck trips are summarized in this report. The truck study is a separate report.

METHODOLOGY

The following summarizes the study design.

Locations Figure 1 shows the location of external stations where the EE trips were estimated. Table 1 describes their locations.

Analysis Period The data collection occurred from December 7 to December 13, 2017.

The analysis periods were established based on the NERPM-AB model periods as defined in the Northeast Regional Planning Model: Activity Based: Calibration and Validation Report (February 2012).


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Figure 1 – External Station Locations


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Table 1 - External Station Locations

Map ID Peggy Malone ID BlueTOAD Device ID

NERPM-AB Traffic Analysis Zone Road Description

1 45-37 20339 2550 I-95 North I-95, 1.5 mi north of Pecan Park Road 2 45-03 20300 2551 US 17 North SR 5 (US 17), 0.1-mile south of GA State Line 3 45-01 20303 2552 US 1 North SR 15 (US 1), 7-miles north of Hilliard at GA State Line 6 45-46 20344 2554 SR 121 SR 121, 0.2-miles south of CR 23-A

4B 45-38 20347 2559 I-10 Westbound I-10, westbound at the Baker County Line 4A 45-39 20330 2559 I-10 Eastbound I-10, eastbound at the Baker County Line 5 45-25 20324 2560 US 90 US 90 Eastbound Baker County Line 7 45-14 20313 2564 US 301 SR 200, 0.4-mile north of Bradford County Line 8 45-40 20331 2566 SR 16 SR 16, 0.1-mile north of SR 230 9 45-42 20329 2568 SR 100 North SR 100, 0.3-mile north of SR 21 (Keystone Heights)

10 45-41 20343 2569 SR 26 SR 26, 0.1-mile southwest of CR 219 11 45-10 20309 2570 SR 20 SR 20, at the Putnam County Line 12 45-28 20327 2573 SR 19 SR 19, southeast of Barge Canal Bridge 13 45-34 20336 2574 US 17 SR 15 (US 17), 0.2-mile north of CR 209 14 45-19 20322 2575 SR 100 SR 100, at the Flagler County Line 15 45-11 20310 2576 US 1 South SR 5, 0.2-mile south of CR 204 16 45-30 20332 2577 I-95 South I-95, at Flagler County Line 17 45-20 20314 2578 SR A1A SR A1A, 2.8-miles north of Flagler County Line


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AM Peak (6 a.m. to 9 a.m.) Midday Off-Peak (9 a.m. to 4 p.m.) PM Peak (4 p.m. to 7 p.m.) Night Off-Peak (7 p.m. to 6 a.m.)

The NERPM-AB also differentiates between weekday and weekend periods. One of the challenges with the NERPM-AB model periods is the continuity for the night off-peak period from 7 p.m. on one day to 6 a.m. on the next. The following periods were used: Monday: Sunday from 7 p.m. to midnight and Monday midnight to 7:00 p.m. Tuesday: Monday from 7 p.m. to midnight and Tuesday midnight to 7:00 p.m. Wednesday: Tuesday from 7 p.m. to midnight and Wednesday midnight to 7:00 p.m. Thursday: Wednesday from 7 p.m. to midnight and Thursday midnight to 7:00 p.m. Friday: Thursday from 7 p.m. to midnight and Friday from midnight to 7:00 p.m. Saturday: Friday from 7 p.m. to midnight and Saturday from midnight to 7:00 p.m.

(weekend) Sunday: Saturday from 7 p.m. to midnight and Sunday from midnight to 7:00 p.m.

(weekend) Alternatively, the night off-peak period could have been calculated using midnight to 6 a.m. and 7 p.m. to midnight on the same calendar day. However, because the volume during these periods are low compared to the average daily data and there was only slight variation in the data, both methods resulted in similar data. Tuesday, Wednesday and Thursday data are most representative of the average weekday conditions forecasted in NERPM-AB.

Data Collection Method Origins and Destinations Volumes TrafficCast’s BlueTOAD™ system was selected for use in this project. TrafficCast maintains a system of approximately 140 permanent count stations within the region. These devices are shown on Figure 2. Previous studies performed for the FDOT and North Florida TPO demonstrated that the travel time data and market penetration rates (percent of vehicles identified) would provide statistically meaningful results.i

BlueTOAD sensors identify Bluetooth® devices based on their Media Access Control (MAC) address which is a unique identifier assigned as a network address for most IEEE 802 network technologies, including Bluetooth, Ethernet and Wi-Fi. BlueTOAD units identify MAC addresses within 3 microseconds in a range of up to 150 meters. When a Bluetooth device passes a BlueTOAD readers, the location and time are recorded. When the same MAC address passes another BlueTOAD reader, travel times and the counts of pairs can be recorded.


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Figure 2 - Regional BlueTOAD Devices


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Origins and destinations were determined as the first device a MAC address was observed and the destination is the last device a MAC address was observed. Each MAC address can pass multiple devices and the data for each “path”, a series of devices is recorded.

The BlueARGUS™ software used by TrafficCast fully anonymizes the data so that none of the data collected can the related to any specific device address or owner. It also “scrubs” the data remove outliers and prepare the data for public use. The data can be provided in real-time or archived data can be used.

The BlueTOAD data matches were reported for the permanent and portable stations based on the time the device was at the origin location.

The EE trips and for the total number of Bluetooth devices that matched with other permanent or portable devices during the study period.

Origin-destination tables for each period, by day, were generated for portable and permanent BlueTOAD stations using the BlueARGUS software.

Many of these reports were previously not available in the BlueARGUS software. Based on this study, standard reports are now available to all BlueARGUS users in the North Florida TPO and FDOT District 2 maintained portal. They will also be used in the FDOT truck study.

Traffic Volume and Classification Counts Traffic volume and classification counts were performed at each of the external count locations. Video or tube counts were performed based on the based on the site conditions. Vehicles were classified according to the Federal Highway Administration’s (FHWA) vehicle classification system identified in their Traffic Monitoring Guide, Appendix C.ii Classes 7-13 (four or more axles) were identified as trucks. Video counts classify trucks based on the length of the vehicle (greater than 40-ft). Traffic counts were aggregated using 15-minute intervals. Where counts occurred for multiple days of the week (for example two Mondays), the data was averaged by period for the basis of the counts.

Expansion Factors and Total Volumes To estimate the total number of EE trips at each entry mode, the proportion of Bluetooth devices that were identified at each entry location that were EE was multiplied by the traffic counts in that period.

The percent of the entering EE trip that was destined for each external station was used to estimate the total volume destined for each external station.

The truck EE volumes were estimated using the same method.

The total data collected is summarized in Table 2.


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Table 2 - Summary of Data Collected

Road Total BlueTOAD Vehicles Matched

Total BlueTOAD EE Vehicles Matched

Traffic Count

Penetration Rate

Percent EE Matches Trucks Percent

Trucks

US 1 North 10,817 2,934 27,960 39% 27% 2,749 12%

US 17 North 3,265 1,362 12,304 27% 42% 619 6%

SR 20 4,252 1,570 27,662 15% 37% 666 3%

US 1 South 6,761 1,982 37,583 18% 29% 970 3%

US 301 36,817 7,595 69,810 53% 21% 10,558 19%

SR 100 4,088 1,821 11,632 35% 45% 998 11%

SR A1A 1,746 746 12,802 14% 43% 101 1%

US 90 6,420 1,869 14,687 44% 29% 1,721 15%

SR 19 3,585 1,319 11,984 30% 37% 892 9%

I-95 South 102,450 16,032 215,229 48% 16% 26,291 16%

US 17 25,059 2,726 116,088 22% 11% 1,926 2%

I-95 North 149,395 18,978 225,844 66% 13% 24,224 13%

I-10 Eastbound 74,714 10,040 127,829 58% 13% 16,141 16%

SR 16 3,146 824 24,987 13% 26% 936 5%

SR 26 2,064 697 22,549 9% 34% 778 4%

SR 100 North 4,139 1,663 38,236 11% 40% 784 2%

SR 121 4,091 1,692 56,281 7% 41% 308 2%

TOTAL 442,809 73,850 1,053,467 42% 17% 90,662 11% The data in the table is based on the total inbound volumes over the 7-day study period. Known outliers in the data are removed from this summary.


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DATA ANALYSIS

Sample Size Bluetooth devices were identified in 442,809 of the 1,053,467 vehicles inbound at these stations which is a market penetration rate of 42 percent. Smart phones and other Bluetooth devices are becoming ubiquitous, and over time the market penetration rates are expected to increase since prior studies were performed in the region. However, this rate is higher than initially anticipated.

Over 3.6 billion new Bluetooth-enabled devices were shipped worldwide in 2017 and more than 10 billion devices are installed. The number of new Bluetooth devices shipped grew by 12 percent per year (compound annual growth rate) over the last five years and is anticipated to continue to grow at this rate for the next five years. In 2018, 86 percent of all new vehicles will have Bluetooth devices installed.iii Considering the growth of Bluetooth devices and the long trips involved with the vehicles counted at these locations (making the likelihood of devices being on vehicles higher on local trips), the data was not adjusted in this study.

No data was stored at the portable devices for the total Bluetooth devices detected. This lack of data could skew the results by predicting a larger percent of EE trips. However, the permanent count station locations cover most of the major routes that are used within the region, so the number of vehicles that are not matched with another device is anticipated to be minor. Increasing the total number of devices at each entry node will increase the number of EE trips for this study which would produce unreasonable results.

Tests of Significance Tests of the statistical significance of the BlueTOAD data were performed to determine if an adequate number of Bluetooth devices were observed at each location and to draw meaningful results for the EE trips as an independent variable. For this analysis, the proportion of the vehicles (counts) that are EE trips detected by BlueTOAD devices. The data was stratified by period and clustered by location. The following methodology was used to determine the minimum sample size.

𝑛𝑛 =𝑁𝑁𝑁𝑁𝑁𝑁

(1 − 𝑁𝑁)(𝐵𝐵2

4 ) + 𝑁𝑁𝑁𝑁

Where: n is the minimum sample size for estimating a proportion (percent of trips that are EE) B (the bound of error for a proportion) = 5 percent N (population size), the count volume was used for this study’s purpose p (estimated proportion of the trips that will be EE) = 10 percent. At the entry nodes where one-way “entry” volumes were considered, 5 percent was used


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Table 3 – Test of Significance for Sample Size

Origins Traffic Counts (inbound only)

Bluetooth Devices

(origin only) R

Min. Sample

Size

% of Minimum Sample Size

Daily Weekday Evening Off Peak

Weekday 6 a.m. - 9 a.m.

Weekday 9 a.m. – 4 p.m.

Weekday 4 p.m. – 7 p.m.

I-95 North 225,844 27,800 12% 144 193.06 12.26 4.23 12.62 5.94

US 17 North 12,304 1,618 13% 142 11.39 0.13 0.29 2.00 1.56

US 1 North 27,960 3,615 13% 143 25.28 1.16 0.89 3.10 1.57

I-10 Eastbound 127,829 38,318 30% 144 266.10 15.81 8.19 17.17 8.81

US 90 14,687 2,524 17% 143 17.65 0.98 0.67 1.65 0.61

SR 121 56,281 2,806 5% 144 19.49 0.55 0.95 1.94 0.79

US 301 69,810 10,248 15% 144 71.17 4.50 2.22 5.04 2.30

SR 16 24,987 972 4% 143 6.80 0.14 0.34 0.80 0.07

SR 100 North 38,236 2,041 5% 143 14.27 0.68 0.76 1.26 0.39

SR 26 22,549 818 4% 143 5.72 0.22 0.14 0.69 0.25

SR 20 27,662 1,921 7% 143 13.43 0.55 0.38 1.96 0.47

SR 19 11,984 1,593 13% 142 11.22 0.46 0.38 1.58 0.99

US 17 South 116,088 3,528 3% 144 24.50 0.96 0.87 2.09 0.74

SR 100 11,632 2,145 18% 142 15.11 0.82 0.60 2.36 0.73

US 1 South 37,583 2,327 6% 143 16.27 0.42 0.38 2.35 1.06

I-95 South 215,229 23,715 11% 144 164.69 10.48 3.75 11.59 4.54

SR A1A South 12,802 878 7% 142 6.18 0.04 0.26 1.13 0.79


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Where the percent of the minimum sample size is less than 1.0, there were insufficient EE Bluetooth matches for a statistically significant sample (if the EE was a standalone variable). The results showed that for some locations and periods, the sample size was not statistically significant. This occurred primarily during off-peak periods and in low traffic volume periods or locations. A statistically significant sample occurred at all locations on daily basis.

Potential Data Errors Overcounting of Bluetooth Devices BlueTOAD units identify MAC addresses within 3 microseconds in a range of up to 150 meters. Because of this range, it is possible for a BlueTOAD unit to record a MAC multiple times if the device remains within the detection circle of a unit. For example, if a unit is near a parking lot and person is in a car in the parking lot with their phone on, the unit can capture that phone many times. TrafficCast uses algorithms to remove these outliers. Since the origin-destination tables for this analysis were generated using BlueARGUS, these potential outliers should have been removed based on the trip times observed. If the raw data were used to generate the origins and destinations, the logic built into BlueARGUS to remove outliers is not available and this logic would have to be repeated in the analysis.

Devices may incorrectly report devices moving in multiple directions. For example, two devices were used at the I-10 entry node and origins and destination pairs were shown at the same location. These data were removed from the analysis.

The BlueARGUS software removes multiple devices within the same vehicle. The data is corrected based on the number of devices identified within an interval developed by TrafficCast. The data are adjusted to the vehicle. No modifications were needed in this analysis.

BlueARGUS also removes outliers in the data based on the trip time where long “rest time” occur between devices.

There were trips that crossed several entry nodes (entering and exiting the model boundaries) along their route. The devices that were reported in multiple EE trip origins and destinations were not removed from the origin destination table generated from BlueARGUS since the trip times between these locations were reasonable. Their algorithms do not account for the modeling logic that a vehicle can have only one origin or destination along a tour or trip-chain. These data were not removed since the number of times this occurred is relatively small, will not significantly influence the results and the data processing to remove these devices would require replicating the other data scrubbing performed by BlueARGUS.

Sampling Bias Although smart phones and Bluetooth devices are nearly ubiquitous, not all vehicles may have Bluetooth devices. This could result in an under-reporting of EE trips for some socio-economic groups that have lower ownership rates. However, since household characteristics were not


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considered as part of this study and the sample sizes were significant, this was not a factor in this evaluation.

To assess the potential for overcounting of Bluetooth devices, we recommend using weekly adjustment factors to escalate the previous traffic counts and update the BlueARGUS data for the same week.

Expansion Factors By comparing the average directional (in-bound) vpd and the Bluetooth matches that we observed, expansion factors were estimated as summarized in Table 4.

Table 4 - Expansion Factors

Entry Location Vehicles Per Day Bluetooth Matches per Day

Bluetooth EE Counts per

Day Expansion

Factor

US 1 North 4,090 1,545 419 2.65

US 17 North 1,863 466 195 4.00

SR 20 4,165 607 224 6.86

US 1 South 5,689 966 283 5.89

US 301 10,013 5,260 1,085 1.90

SR 100 1,754 584 260 3.00

SR A1A 1,868 249 107 7.50

US 90 2,311 917 267 2.52

SR 19 1,666 512 188 3.25

I-95 South 28,503 14,636 2,290 1.95

US 17 18,441 3,580 389 5.15

I-95 North 32,080 21,342 2,711 1.50

I-10 Eastbound 18,742 10,673 1,434 1.76

SR 16 3,677 449 118 8.19

SR 26 3,469 295 100 11.76

SR 100 North 5,685 591 238 9.62

SR 121 8,554 584 242 14.65

Total 152,570 63,258 10,550 2.41


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RESULTS

Table 5 summarizes the average weekday EE trip vehicles resulting from this study. As demonstrated in the data analysis section, the study results in reasonable and statistically significant data that can also be used in other studies and analysis.

In addition to average weekday conditions, the EE trip volumes were also estimated during each period in the model.


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Table 5 - Estimate of Average Weekday EE Trip Volumes

Location US 1 North US 17 North SR 20 US 1 South US 301 SR 100 SR A1A US 90 SR 19 I-95 South US 17 I-95 North I-10 Eastbound SR 16 SR 26 SR 100

North SR 121 Total

US 1 North

145 137 155 329 139 80 74 101 323 155 394 361 41 23 80 51 2,588

US 17 North 197

103 137 21 95 116 16 96 145 23 618 208 9 5 12 13 1,814

SR 20 288 137

240 334 334 114 114 220 403 213 302 361 59 174 206 91 3,590

US 1 South 312 198 232

224 283 196 116 204 597 167 609 469 53 47 104 80 3,891

US 301 250 13 82 72

75 9 220 44 678 157 2,187 669 84 29 167 84 4,820

SR 100 143 69 147 127 121

63 46 119 177 98 146 176 33 97 213 46 1,821

SR A1A 178 200 168 225 35 153

18 185 255 38 128 215 8 23 20 20 1,869

US 90 100 19 42 51 295 44 14

35 181 81 165 218 22 13 45 244 1,569

SR 19 105 68 125 90 69 95 69 36

113 274 117 130 22 21 62 34 1,430

I-95 South 220 52 114 275 695 114 58 122 79

237 6,207 2,016 43 34 84 58 10,408

US 17 319 22 185 148 428 155 26 148 379 647

927 642 220 82 215 137 4,680

I-95 North 197 230 66 116 1,744 72 25 102 51 5,038 221

1,483 30 17 65 53 9,510

I-10 Eastbound 234 75 100 131 706 100 50 131 68 1,954 197 1,604

32 20 75 400 5,877

SR 16 123 19 68 76 374 93 14 71 66 177 409 147 145

98 246 123 2,249

SR 26 106 24 341 102 161 388 27 59 82 180 196 141 125 125

502 172 2,731

SR 100 North 298 42 314 199 766 757 26 164 231 410 401 420 410 212 446

237 5,333

SR 121 312 39 220 195 640 229 39 1,699 146 478 395 454 2,724 220 166 303

8,259

Total 3,382 1,352 2,444 2,339 6,942 3,126 926 3,136 2,106 11,756 3,262 14,566 10,352 1,213 1,295 2,399 1,843 72,439


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Figure 3 – Average Vehicles Per Day


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Figure 4 - Weekday A.M. Peak Hourly Volumes


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Figure 5 - Weekday Mid-Day Average Hourly Volumes


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Figure 6 - Weekday P.M. Peak Average Hourly Volumes


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Figure 7 - Average Trucks per Day (Weekdays)


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Figure 8 - Weekday Mid-Day Average Hourly Truck Volumes


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Comparison to NERPM-AB 2010 The 2010 NERPM-AB based their estimate of EE trips on the 2005 model EE and external to internal trip tablesiv and the results of a roadside survey EE origin-destination study that was conducted in 2000. As part of the model validation, average daily traffic counts at each of the external stations and the model volumes are compared. During this process, the EE and external-internal trips are factored - which changes the distribution of the EE trips. Therefore, the modeled volumes are less reliable and accurate than the volumes counted as part of this project.

The NERPM-AB model has 28 external stations, versus the 17 locations evaluated in this study. The model estimated a total of 54,942 Vehicles per Day (vpd) EE vehicles for all locations. About 97.5 percent of the EE vehicle trips (52,336 vpd) occurred at the 17 locations evaluated in study. The estimated 2017 EE trips in this origin-destination study are 72,439 vpd which is a 38.4 percent greater than the 2010 NERPM-AB modeled volumes.

Since 2010, the population in the six-county model area grew 8.27 percent and vehicle-miles traveled increased by 12.57v percent the 2045 NERPM-AB EE trips should increase commensurate with this growth. Table 6 shows an estimate of the 2017 EE trips using a 12.57 percent growth factor from the 2010 NERPM-AB EE trip table.

During model validation and calibration of the 2045 NERPM-AB, analysis of the balancing of trips that occurs to match the total volumes at the external stations should be balanced against the EE volumes counted in this study.


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Table 6 - Adjusted NERPM-AB EE Matrix (Average Weekday)

Location US 1 North

US 17 North SR 20 US 1

South US 301 SR 100 SR A1A US 90 SR 19 I-95 South US 17 I-95 North I-10 Westbound SR 16 SR 26 SR 100

North SR 121 Total

US 1 North 91 1 656 1 6 109 2 20 7 84 249 1 1,227

US 17 North 78 1 17 3 14 14

23 6 72 213 441

SR 20 91 78

120

124 80

65 1,074 156 1,361 115 3,264

US 1 South 1 1 120

1 1 6

20 3 11 114 331 1 610

US 301 656 17

1 77 11 1 4,763 630 32 6,188

SR 100 124 1

5 90 263 483

SR A1A 1 3 80 6

19 7 3 50 146 315

US 90 6 14 0 1 77 18 1 17 44 12 190

SR 19 65 1 5 46 133

250

I-95 South 109 14 1,074 6 11 6 18 8,267 719 132 606 1,758 8 12,728

US 17 156

1

1 1

7 115 335

616

I-95 North 2

1,361 20 4,763 1 19 17 1 8,267 1

2,749 74 638 1,866 8 19,787

I-10 Eastbound 20 23 115 3 630

7 719

2,749

101 108 315 17 4,807

SR 16 7 6 11 5 3 44 5 132 7 74 101 395

SR 26 84 72 114 90 50 46 606 115 638 108 1,923

SR 100 North 249 213 331 263 146 133 1,758 335 1,866 315 5,609

SR 121 1

1 32 12

8

8 17 79

Total 1,227 441 3,264 610 6,188 483 315 190 250 12,728 616 19,787 4,807 395 1,923 5,609 79 58,912


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Comparison to Alternate Methods of Data Collection Alternate methods for collecting origin-destination studies are available. Table 7 provides a summary of the alternate data collection methods, strengths and weaknesses and the estimated costs required to complete a similar study.

Roadside Surveys involve stopping vehicles and interviewing drivers about their origins and destinations, demographics and other information. Because of the costs and interruptions to the traveling public, roadside surveys are no longer permitted in Florida.

Mail back surveys, including travel diaries, are also used that request travelers to record their trips and other information.

In addition to Bluetooth-device identification technologies used in this study, other technologies are also available to continuously collect data. Traffic count data is also needed to update, verify and refine the analysis.


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Table 7 - Comparison to Other Origin Destination Study Methods

Factor Roadside Survey Mail-back Survey Bluetooth or Other Vehicle/device Recognition Technology

Time One-time One-time

Data is continuously counted at permanent counters that can be used to update, verify and refine the analysis. Supplementing with portable counters when needed is a lower cost option than performing a second one-time roadside or mail-back survey.

Data Quality (Summary) Better (estimated) Good (estimated) Best (measured and repeatable).

Sample Sizes

Target sample sizes are 300 at each location for peak periods and 100 vehicles at each period in the off-peak. The ability to obtain the desired number of samples is feasible by extending the number of days to achieve the minimum.

Target sample sizes are 300 at each location for peak periods and 100 vehicles at each period in the off-peak. There is no control on the ability to ensure an adequate number of sample sizes are obtained without call-back surveys to follow-up in locations and regions until the minimum number of samples are met.

1.6 million Bluetooth matches were identified in one week that included matches at all BlueTOAD devices in the region. There is no control to ensure a minimum sample size is obtained during each period.

Travel Times Estimated based on survey questionnaire but cannot be field verified.

Estimated based on survey questionnaire but cannot be field verified.

Field measurements for every vehicle with a matched pair.


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Factor Roadside Survey Mail-back Survey Bluetooth or Other Vehicle/device Recognition Technology

Sampling Errors

Potential for sampling errors, survey bias for respondents that may not provide accurate information. Weather or other events preclude data collection, which introduces bias into the survey results.

Potential for sampling errors, survey bias for respondents that may not provide accurate information. The return rates for respondents historically have been very low (less than 5 percent). The percent of respondents in recent years has improved with internet surveys.

May duplicate vehicles within the detection area. Obtain minimum number of samples per each period.

Origins and Destinations

No field equipment is needed at the origin or destination, and device matching is not required to capture all data points assuming the respondent answers truthfully.

No field equipment is needed at the origin or destination and device matching is not required to capture all data points assuming the respondent answers truthfully.

Multiple permanent or portable devices can be used to define destinations or zones. Intermediate sensors can identify paths. Although grouping of BlueTOAD sensors into traffic analysis zones, subarea, zip codes or other regions can be done, it may not be feasible to place enough sensors to capture all trips for an internal trip study (II or EI)

Costs for comparable

studies

The cost to complete a study with similar outcomes is $250,000 to $500,000vi to meet minimum sample size requirements. The cost to complete a study with the same level of participation as the vehicle ID technologies would be $900,000 to $1 million.

Mail-back surveys are estimated to cost $2.5 to $5 for each response. The cost to complete a similar study using mail-back only surveys is $175,000 to $350,000.

The cost of this study was $95,000.


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FINDINGS AND RECOMMENDATIONS

Findings The analysis of the EE trips did not produce results that were counterintuitive in terms of the travel patterns or magnitude of the EE trips. The key technical observations that occurred include:

The calculation of the off-peak nighttime periods as defined in the NERPM-AB was not straightforward. The NERPM-AB period begins at 7 p.m. and ends at 6 a.m. the following morning. Since this period is continuous, two analyses were performed: (1) a continuous period was created that went from 7 p.m. on one day through 6 a.m. on the next and (2) the 12 a.m. to 6 a.m. and 7 p.m. to 12 a.m. data for a single day was combined. Although theoretically useful in the model to provide a 24-hour total, the inconsistency that results from a continuous period extending across two days was less straightforward in this application.

Of the 1,053,467 vehicles counted, 442,809 or 42 percent were identified to have Bluetooth. The percent of the vehicle, or penetration rate was higher than expected.

Major accomplishments of this study included:

This project demonstrated that using Bluetooth™ or other probe vehicle technologies for origin-destination studies provides a cost-effective and robust data set.

By working with TrafficCast® additional analysis reports and data queries were included in the North Florida system. These reports will be used to complete additional origin-destinations studies underway for the major truck terminals in the area and can be used in future corridor studies.

EE origin-destination studies were completed for each model analysis period at the locations studied to be used in model validation and calibration of the 2045 Long Range Transportation Plan update to the NERPM-AB.

Truck origins and destinations can be reasonably estimated using this approach.


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Recommendations The following additional analysis is recommended as part of future phases.

Ensure the data downloads from portable devices occur and are uploaded to the BlueARGUS™ software to provide more accurate expansion factors of the data.

Smart phones and other Bluetooth devices are becoming ubiquitous. Over time, the market penetration rates are expected to increase, since prior studies were performed in the region. However, the observed penetration rates in this study was higher than expected. Additional data is available from BlueARGUS that can be used to verify these penetration rates at the permanent BlueTOAD™ devices; however, budget was not available in this study to pursue acquiring additional samples.


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END NOTES

i Congestion Management Process Plan and 2016 Annual Mobility Report, North Florida TPO (2014) ii https://www.fhwa.dot.gov/policyinformation/tmguide/tmg_2013/vehicle-types.cfm iii www.bluetooth.com iv Technical Report #4: Calibration and Validation Report, Northeast Regional Planning Model: Activity Based, North Florida TPO, (February 2015), page 85. v 2018 Annual Mobility Report, North Florida TPO, March 2018 vi Estimate based on $12 - $25 per survey, 30 surveys per period (5 periods), 17 locations, seven days of data, plus analysis and traffic counts.

origin-destination studynorthfloridatpo.com/images/uploads/o-d_study_-_ee...jun 15, 2018 ·...

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