Bluetooth BlueTOAD Technology Evaluation in Sarasota County, Florida USA

Andy J. Lucyshyn, PE, PTOEAtkins North America

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A presentation on the Atkins study which tested the effectiveness of BlueTOAD, a travel-time device that utilizes Bluetooth technology.

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Agenda

• Methods of travel-time data collection• Probe vs. point-based

• What is BlueTOAD?

• Evaluating the product:• Distribution, match rates, speeds

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Methods of Travel-Time Data Collection

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Methods of Travel-Time Data Collection

● Point-based– Roadside device measures spot speed of passing cars– Spot speeds are averaged to determine travel time between points

● Probe-based– Roadside device reads unique identifier and adds time stamp– Time stamp differential of those unique identifiers provide travel

times

Benefit Point-Based Probe Based

Aging of Data N Y

Issue of Statistical outliers N Y*

More likely to accurately reflect travel conditions N* Y

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What is BlueTOAD?

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BlueTOAD Devices

Blue tooth

T ravel-time

O rigin

A nd

D estination

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Bluetooth Travel-Time Technology

BlueTOAD device detects MAC

address and adds time stamp

Cellular Modem / Ethernet inside

BlueTOAD devices send raw data to TCI

servers

Raw data is processed by TCI (MAC

addresses are matched)

Raw MAC address data is discarded by

TCI to preserve anonymity

Data is calculated (Travel times and origin-destination)

Data is filtered by TCI (statistical outliers

removed)

Data is sent to TCI web server (for client

use) and to client

In-device (on-site) functions

Off-site functions

Client-access

TCI = Traffic Cast International

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Evaluating the Product

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Sarasota County Test Location

Test Location

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Study Purpose and Methodology

● Test Product– Two solar/cellular BlueTOAD devices

● Control– Hi-Star NC-97 Nu-Metric devices

● Spot speeds● Volumes

● Data collected in June 2010● Test components– Data Distribution & Match Rate– Flow Speeds & Travel Times

Fruitville Road at:Honore AveBeneva Rd

~2 miles

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Data Distribution

PM Peak

Mid-Day Peak

AM Peak

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Sample Size for Accurate Readings

Statistical Patterns of Traffic Data and

Sample Size Estimation

Stanley Young, Ph.D., PE Center for

Advanced Transportation

Technology (CATT)University of Maryland

σ = 6.1

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Sample Size for Accurate Readings

● Sample size (N) = (z2)(σ2)/(H2)– Z is a coefficient of confidence

● Z = 1.96 at a 95% confidence level● Z = 2.475 at a 99% confidence level

– σ = 6.1 (as shown previously)– H = acceptable error range

● 3 mph for traffic operations● 2 mph for before and after studies

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Match Rates: Match Rate Criteria

Well placed sensors:3%-4% detection rate

Time Increment Before and After Studies Traffic Operations

15 Minutes 9 61 Hour 36 251 Day 864 600

Fruitville Road AADT between Honore Ave and Beneva Rd:~19,000 vehicles

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Match Rates

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Match Rates

Total daily average = 3.45%

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Flow SpeedsAM Peak Mid-Day

Peak

PM Peak

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Flow Speeds

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Study Conclusions

● Distribution– Matches evenly distributed across time– Data trend was consistent with Nu-Metric devices– Any inconsistencies are in off-peak intervals

● Match Rates– Achieved between 3-4% (25-36 matches per hour)

● Flow Speeds– Nu-Metric vs. BlueTOAD speeds within 2 mph on average– Nu-Metric vs. BlueTOAD travel-times within 13.8 seconds on

average

Segment: 1.9 miAvg: 42 mphAvg: 2.7 min

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Contact us

● Andy J. Lucyshyn, PE, PTOE– Atkins North America– Andy.Lucyshyn@atkinsglobal.com

● Efrain Duque, PE, PTOE– Sarasota County– eduque@scgove.net

● Whitney D’Annunzio, EI– Atkins North America– Whitney.DAnnunzio@atkinsglobal.com