Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 1

Detection Probability Models for Bluetooth Re-identification Technology

Stanley Ernest Young

Center for Advanced Transportation Technology (CATT), University of Maryland

2200 Technology Ventures Building, 5000 College Avenue, College Park, MD 20742

Phone: (301) 403-4593

Fax: (301) 403-4591

Email: seyoung@umd.edu

Elham Sharifi

Department of Civil and Environmental Engineering, University of Maryland

1173 Glenn L. Martin Hall, College Park, MD 20742, USA

Phone: (301) 405-6550

Fax: (301) 405-2585

E-mail: esharifi@umd.edu

Hadi Sadrsadat

Department of Civil and Environmental Engineering, University of Maryland

1173 Glenn L. Martin Hall, College Park, MD 20742, USA

Phone: (301) 405-6550

Fax: (301) 405-2585

E-mail: hadisadr@umd.edu

Nayel Urena Serulle

Department of Civil and Environmental Engineering, University of Maryland

Jeong H. Kim Engineering Building, College Park, MD 20742

Phone: (650)-387-9117

Email: nus@umd.edu

Kaveh F. Sadabadi

Center for Advanced Transportation Technology (CATT), University of Maryland

2200 Technology Ventures Building, 5000 College Avenue, College Park, MD 20742

Phone: (301) 403-1605

Fax: (301) 403-4591

Email: kfarokhi@umd.edu

Submission Date: 07/31/2012

Text Word Count: 3902

Figures: 2

Tables: 8

Total Word Count: 6402

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 2

ABSTRACT Traffic monitoring technology based on identifying a portion of the traffic at an upstream and

downstream sensor provides direct samples of travel time as well as a proportional measure of

through traffic volume. Referred to as re-identification technology, this method has become more

accessible with the introduction of BluetoothTM

based technology since 2008. BluetoothTM

traffic

monitoring (BTM) utilizes anonymous electronic identifiers in wireless communications

providing roughly a 5% sample of through traffic, and is cost effective enough for consideration

on many roadway types. For these reasons BTM is being considered for deployment on

freeways, arterials, and local streets to provide traffic data to support real-time operations,

traveler information, planning, and signal management. Successful applications require

consideration and understanding of the detection properties of BluetoothTM

technology. The

objective of this paper is to provide a model for understanding the expected detection rate and

probability of detection to properly plan a deployment.

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 3

INTRODUCTION

The Bluetooth concept is attractive because of its low capital costs and the high resolution data

that can be obtain from it. However, there is little guidance on the appropriate use of this new

technology (1). Several hardware and software considerations need to be taken into account to

obtain the highest probability of detection. Empirical research in Texas yielded guidance on this

matter. They found that the device needs to be cost-effective, compact, meet the environmental

demands (i.e., withstand extreme temperatures), and be able to transfer the information through

common ports (e.g., USB and Ethernet). Furthermore, they recommend the coupling of a Class 1

adapter and 1db antenna for most traffic applications for acceptable detection rates. Bakula, et al.

learned that the discovery process is probabilistic in nature (2). Given this, they defined the

match probability as the probability that a single vehicle containing a discoverable Bluetooth

radio will be detected by two different scanning radios. The authors specified that the effective

range of the radios and vehicle speed have significant influence in the probability of target

detection. When the effective range of detection approaches 200 meters, 100 meters on each side

of the scanning radio, the impact of vehicle speed is not significant. On the other hand, when

effective range is less than 20 meters the probability for a match could decrease to values lower

than 10%. The device’s antenna is one of the main factors that affect the effective range of

detection, among other factors such as transmission power, channel conditions, and channel

obstructions. Malinovskiy, et al. tested two types of antennae, omni-directional and directional,

to determine the effects of antenna selection on travel time data collection (3). Omni-directional

sensors were found to have a larger detection zone than the directional sensors, which yields a

bigger sample size. However, they subject to more noise and bigger spatial errors, as a vehicle

may be detected anywhere within the zone. Furthermore, research has shown that using an array

of antennas (two to four), instead of a single one, in Bluetooth monitoring stations yields and

average increase in detection between 30% and 50% (4). The reader is reffered to Porter, Kim

and Magaña (5) for more details on Bluetooth data collection devices, its components, and

deployment recommendations.

Successful application of Bluetooth requires consideration and understanding of the

detection properties of its technology. The objective of this paper is to provide a framework for

understanding the expected detection rate and probability of detection to properly plan a

deployment. Also, this paper contributes to the literature by presenting results of empirical

research regarding the effects of antenna, sensor class selection, and base scanning period on

detection rate.

BLUETOOTHTM

DETECTION PROPERTIES A new data collection method based on Bluetooth

TM (BT) technology for travel time

measurement was introduced in 2008. In this new method, BT devices located within vehicles in

the traffic stream are observed by an upstream and downstream BT sensor in order to sample the

travel time of the traffic stream between the two sensors. BluetoothTM

traffic monitoring (BTM)

was originally developed and applied to high-speed freeway applications, specifically for travel

time assessment. On freeways, sensors are placed one mile or more apart, and the BT sensor

power and antenna range are maximized to increase the likelihood of detection. Although on

occasions freeways present some challenging topology for deployment, due to constrictions or

impinging right-of-ways, such situations are rare. Since 2008, BTM has progressed from

sparsely-spaced sensors for high speed freeways applications to characterize the central tendency

of travel time, to more-densely spaced sensors on lower speed arterial facilities to characterize

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 4

both the central tendency and the distribution of travel time to assess the quality of progression

along the corridor. The fundamental detection properties of BTM are reviewed in this section,

developing a detection model that provides guidance for designing BTM deployments along any

type of facility.

Detection Mechanics

Bluetooth standards provide a means for electronic devices to communicate wirelessly using the

license free 2.4 GHz spectrum (6). Standards are maintained by the BT Special Interest Group

(SIG) Full details of the wireless electronic communications standards are beyond the scope of

this document, however, BluletoothTM

properties that impact its use as a traffic monitoring

technology are reviewed to construct a detection model for guiding deployments.

Bluetooth is primarily a cable replacement technology. As such, the communication

range of off-the-shelf BT equipment reflects distances ranging from 1 to 100 meters. A

commercial BT device is one of three power classes with nominal ranges of 100, 30, and 1 meter

for class I, II, and III respectively. The maximum detection range of a roadside BT sensor to a

BT detectable device in a vehicle is determined by the respective power class of the sensor and

the detectable device, and their respective antenna properties. This maximum range and resulting

probability of detection is reduced by other factors such as terrain, antenna placement and

orientation, noise in the 2.4 GHz spectrum, occlusion by other vehicles, and clock

synchronization between devices.

In order for two BT devices to exchange information, they must be paired. Pairing

requires either that the devices be pre-programmed to recognize each other, or they must initiate

a handshaking protocol that allows two unknown devices to exchange identification and

synchronize clocks, the basic information needed to initiate digital communications. In this

handshaking protocol, called the device discovery mode, BT devices provide electronic

identifiers known as a Media Access Control identifier (or MAC IDs). It is the MAC IDs that

allow BT devices to be used for re-identification of vehicles and thus derive traffic information

similar to license plate matching or toll tag data.

During the pairing process, one device, referred to as the master, sends out a standard

inquiry message. The other BT device, referred to as the slave, receives the inquiry message and

responds with a standard message containing its ID and clock synchronization data, as well as

other secondary attributes. As BT is a spread-spectrum, frequency-hopping protocol, the inquiry

message and subsequent response is not issued on a single distinct frequency (or channel), but

rather it is broadcast on various channels and at various times in a sequence and time pattern

prescribed by the BT protocol. The pattern of inquiry is designed to maximize the likelihood that

two un-synchronized devices will pair within a reasonable timeframe, typically cited as 10

seconds.

The minimum time cycle to issue an inquiry and listen for a response on all channels is

1.28 seconds – referred to as a scan cycle. Multiple scan cycles increase the likelihood of pairing

by extending the prescribed sequence of channel hopping. Multiple scan cycles are not simply

repeating the channel hopping sequence of the initial scan, but rather extending the channel

hopping pattern into new patterns to increase pairing likelihood. If two devices are within

communication range, the derived probability of pairing as a function of the number linked scan

periods is summarized in Table 1 based on implementation of version 1.1 of the inquiry scan

specification (7). The length of time to achieve 99% probability of discovered, can be further

reduced with implementation of version 1.2 of the specification and interlacing. However,

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 5

measured results differ from derived due to variation in the implementation of the BT inquiry

standard.

TABLE 1 Probability of Discovery as a Function of Scan Cycles

Scan Cycles Scan Time Percent Discovered

1 1.28s 36.71%

2 2.56s 48.96%

3 3.84s 86.71%

4 5.12s 98.95%

5 6.40s 99.98%

Based on Table 1, in order to achieve 95% or higher probably of detection, a minimum of

4 scan cycles, equivalent to 5.12 seconds between initiation of a new scan period, is necessary.

These probabilities are based on two devices within physical communication range, and assume

no obstruction to the communication signal during the scan time.

Detection Range

The fundamental detection range of a BT sensor is determined by its rated power (indexed by its

Class) and its antenna. The nominal communications range of BT transceivers based on its class

is nominally 100m, 30m, and 1m for Class 1, 2 and 3 respectively. These ranges are based on

identically configured devices using isotropic antennas, an antenna that emits power equally in

all directions.

Antenna can be utilized to distribute the radiated power in various patterns. Because BT

subsystems are typically found on consumer and mobile devices in which the orientation of the

device is variable, most BT radios in consumer equipment are equipped with antennas that

mimic isotropic patterns (0 dB gain). The orientation of a BT sensor can be controlled when it is

deployed, and thus non-isotropic antennas can be used to concentrate the radiated power and

extend the sensor range. Dipole antennas are frequently employed to transform the spherical

distribution into a toroidial pattern (donut shaped) to extend transceiver range laterally when the

dipole antenna is mounted perpendicular to the ground. A typical horizontal and vertical field

pattern for a dipole antenna is shown in Figure 1. Dipole antennas with gain of 3dBi or greater

are common for Bluetooth applications, extending the nominal range in the plane of the toroid by

a factor of two or more. The higher the gain of the antenna, the more sensitive the receiver is to

deviations from vertical in the orientation of the antenna, limiting the practicality of higher gain

antennas. Antenna with gain greater than 10 dB may be sensitive to vibration, wind and other

effects that could impact its orientation. Other antenna configurations and patterns are possible,

but are beyond the scope of this document

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 6

FIGURE 1 Sample Vertical and Horizontal Coverage Patterns for a 3 DBi di-pole Antenna

Impact of Vehicle Speed

A model to estimate the probability of detection of a BT device is illustrated in Figure 2, in

which a BT sensor is offset from the roadway a distance h, with a detection range of radius r. A

vehicle containing a detectable BT device is on a trajectory such that it enters and exits the

detection zone at points A and B respectively, forming the chord ⃗⃗⃗⃗ ⃗. The time in the detection

zone while on trajectory | ⃗⃗⃗⃗ ⃗| determines the probability of detection. From the geometric

relationships, | ⃗⃗⃗⃗ ⃗| √ . If the detection range is large compared to the offset from

the roadway (>5x), | ⃗⃗⃗⃗ ⃗| can be approximated by 2r. This also forms a maximum bound on the

length of the detection path for any given BT device passing through a sensors detection zone.

Note that this model accounts only for the class of the sensor, characteristics of the target BT

device may also impact the distance at which it may be detected by the sensor and thus degrade

the results.

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 7

FIGURE 2 Model to Estimate in Detection Zone

The time within the detection zone is determined by speed along the path ⃗⃗⃗⃗ ⃗. Three

factors limit the design and placement of field equipment: the anticipated maximum speed of the

vehicle, the fundamental BT sensor detection range, and the probability of detection from Table

1. Vehicles should remain within the detection zone for a minimum of four scan cycles to

increase the probability of detection to greater than 95%. For highway operations with expected

speeds of 60 mph (88 feet/second), the minimum detection zone width, ⃗⃗⃗⃗ ⃗, corresponding to

four scan cycles is approximately 450 feet. Table 2 provides the minimum detection zone width

for various speeds and probability of detections. In practice, it is recommended to design toward

twice the value in the top row associated with 95% probability with a 5.12 second scan cycle.

TABLE 2 Detection Zone Based on Speed and Scan Periods

P(Detection) Scan

Period

Speed (mph)

60 50 40 30 20 10

95% 5.12 451 375 300 225 150 75

85% 3.84 338 282 225 169 113 56

50% 2.56 225 188 150 113 75 38

Height of Antenna

Signal propagation in the 2.4 GHz is primarily line-of sight. Structures that block the line-of-

sight between the BT sensor and target devices inhibit reception, particularly conducting

surfaces, such as metal structures. Several studies have documented the relationship between

antenna height above the roadway and resulting BT detection rate. Day tested 0 ft, 2.5 ft, 5 ft,

7.5 ft and 10 ft for transceiver antenna height and found 7.5 ft the best one for roadside location

(8). Ground deployed sensors detect generally half the number of vehicles as sensors mounted

eight feet or higher.

BT Sensor

A B

C

h

r

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 8

Variability in Detectable Devices

The model in Figure 2 assumes that each detectable device is identical, and that any externalities

act on all BT devices equally. In practice, each device receives signals with differing level of

sensitivity, and emit signals at differing power, and (probably having the most impact) are

located at various positions in the vehicle resulting in varying propagation characteristics as to

when and how long the BT sensor is in range. The combined effect results in a probabilistic

distribution about the fundamental detection range. The detection range for any particular device

may not be symmetric about the sensor. For instance, if the device is on the dash of a truck, it

may easily detectable on the approach to the sensor, and much less detectable on the regress

from the sensor.

Fundamental Detection Rate

The BluetoothTM

fundamental detection rate is defined as the maximum possible sample that can

be obtained from BTM equipment. If every vehicle that contains a detectable device were

captured at both the upstream and downstream sensor, then the ratio of matched-pairs to roadway

volume would equal, or closely approximate the fundamental detection rate.

Various tests on freeway segments suggest that the sampling rate obtained by using

BluetoothTM

sensors is between 2% and 8% of the traffic volume and its average is about 5% (9).

This range of sampling rate reflects many differences in deployment, (ground mount vs

elevated), and varying placement of BT with respect to opportunities for merging and diverging,

diminishing the percentage of through traffic volume.

The BT fundamental detection rate is dependent only on natural occurrence of detectable

BT devices in the vehicle population. The fundamental detection rate can be estimated

experimentally by deploying BT sensors alongside a traffic volume counter on a segment or

roadway with no access points. The BT sensors should be elevated, and of sufficient class and

antenna gain to insure vehicles are within the detection zone for > 10.24 seconds. This

corresponds to a Class 1 transceiver with a 3 dB gain antenna mounted at a nominal 10 feet

above the roadway surface for freeways.

It is critical that no roadway access points are within the test corridor. The placement of

the traffic counter (between or on either side of the BT sensors) is not critical. The ratio of BT

matched-pairs divided by the volume will approximate the BT fundamental detection rate in this

configuration.

FIELD DATA

Data collected at various deployments in Maryland were analyzed to determine the extent to

which data agree with the models for probability of detection given in BluetoothTM Detection

Properties section.

Probability of Detection based on Scan Period

Data from BT sensors deployed on I-95 between Washington D.C. and Baltimore, Maryland

were used to analyze the impact of scan period on the probability of detection. Three sensors are

deployed in the median. The first sensor, A, is deployed in the median just north of the

interchange with MD-100. The second sensor, B, is deployed in the median approximately three

miles to the south of sensor A, north of the interchange with MD32. However, due to elevation

change between the northbound and southbound lanes of I-95, sensor B is elevated about 10 feet

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 9

above northbound lanes, but approximately at road level height for southbound lanes. The third

sensor, C, is deployed three miles south of sensor B, between the interchanges with MD216 and

MD198. The scan period for sensors A and C were set to four during the analysis. The scan

period for sensor B was alternated from four, to three, to two scan periods over the course of

three weeks of data collection. Table 3 presents the percentage of the traversals from sensor A to

sensor C that was captured at sensor B for the various scan period settings.

TABLE 3 Probability of Detection versus Scan Period

I-95 Traffic Direction Scan Cycles

4 3 2

Northbound 92.0% 89.5% 15.3%

Southbound 64.7% 58.9% 29.2%

Northbound results for four scan periods are consistent with results from adjacent sensors

(discussed in next section). As the scan period was reduced to 3 and then 2, the detection

percentage decreased, though not consistently with the proportions predicted in Table 1.

Southbound results for a scan period of four were in line with expectations of a ground deployed

BT sensors, capturing only 64.7% of the traversals from C to A. The impact of changing the scan

period for southbound traffic was consistent as predictions based on Table 1.

Probability of Detection with Adjacent Sensors

Data collected on I-270 as part of a region wide deployment BTM technology was analyzed to

determine the probability of detection of a BT device. BT sensors are deployed along I-270 in

Montgomery County, Maryland as described in Table 4. All sensors were deployed at

approximately 10 feet above the roadway, were Class 1 with a 3dBi dipole antenna.

TABLE 4 Location Descriptions

Sensor Route Direction Location

A I-270 NB On Shoulder Pole of Overhead Sign Sructure

Between Montrose Rd and Tuckerman Lane

B I-270 NB On Shoulder RTMS Pole

Just before the Rt 28/Gude Dr. Overpass

C I-270 SB On Shoulder Pole of New Overhead Sign Structure

Just South of Diamond Ave (117) on Ramp

D I-270 SB On Shoulder Pole of Variable Message Sign Structure

Approx. 0.75 Mile South of Middlebrook Rd

E I-270 Median On Median Pole of Overhead Sign Structure

Approx. 1.5 Miles North of Father Hurley Blvd/Ridge Rd 27

Sensors A and E bound the study area were used to isolate a set of through trips, or

traversals. Traversal between A and D are also known to pass by sensors B, C, and D. For each

confirmed traversal between AE, data from B, C and D were tested to determine if the particular

BT device was detected. Table 5 provides the results in the form of possible permutations of

detections at locations B, C and D. Note all data in Table 5 is conditioned upon detection at

sensors A and E.

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 10

TABLE 5 Probability of Detection at Consecutive Sensors

The overall probability of detection at B, C, and D, as derived from the totals in Table 5

are provided in Table 6. Along with the individual probabilities of detection at B, C, and D, all

permutations of joint probability and conditional probability are derived from the data and

contrasted to calculations based on individual probabilities and assuming independence. In all

cases of joint and conditional probability, the measured probability indicates a degree of

correlation.

30 1868 1282 68.6% 68 3.6% 53 2.8% 23 1.2% 242 13.0% 66 3.5% 66 3.5% 68 3.6%

1 1838 1251 68.1% 78 4.2% 47 2.6% 30 1.6% 206 11.2% 79 4.3% 85 4.6% 62 3.4%

2 1908 1341 70.3% 63 3.3% 51 2.7% 27 1.4% 198 10.4% 89 4.7% 90 4.7% 49 2.6%

3 2077 1438 69.2% 73 3.5% 59 2.8% 35 1.7% 206 9.9% 74 3.6% 123 5.9% 69 3.3%

4 2437 1727 70.9% 96 3.9% 65 2.7% 41 1.7% 235 9.6% 94 3.9% 98 4.0% 81 3.3%

5 2057 1417 68.9% 92 4.5% 52 2.5% 28 1.4% 222 10.8% 114 5.5% 61 3.0% 71 3.5%

6 1914 1306 68.2% 98 5.1% 50 2.6% 28 1.5% 216 11.3% 96 5.0% 63 3.3% 57 3.0%

7 1899 1332 70.1% 69 3.6% 47 2.5% 27 1.4% 195 10.3% 94 4.9% 83 4.4% 52 2.7%

8 1872 1309 69.9% 65 3.5% 58 3.1% 29 1.5% 206 11.0% 91 4.9% 64 3.4% 50 2.7%

9 1849 1349 73.0% 60 3.2% 34 1.8% 32 1.7% 160 8.7% 84 4.5% 82 4.4% 48 2.6%

10 2119 1512 71.4% 69 3.3% 45 2.1% 29 1.4% 218 10.3% 95 4.5% 97 4.6% 54 2.5%

11 2465 1780 72.2% 90 3.7% 57 2.3% 36 1.5% 220 8.9% 105 4.3% 91 3.7% 86 3.5%

12 2239 1503 67.1% 93 4.2% 68 3.0% 39 1.7% 246 11.0% 118 5.3% 86 3.8% 86 3.8%

13 2058 1328 64.5% 87 4.2% 80 3.9% 42 2.0% 230 11.2% 108 5.2% 95 4.6% 88 4.3%

14 1839 1282 69.7% 58 3.2% 62 3.4% 31 1.7% 186 10.1% 67 3.6% 98 5.3% 55 3.0%

15 1816 1211 66.7% 71 3.9% 72 4.0% 36 2.0% 154 8.5% 102 5.6% 102 5.6% 68 3.7%

16 1969 1383 70.2% 64 3.3% 51 2.6% 32 1.6% 208 10.6% 76 3.9% 93 4.7% 62 3.1%

17 2118 1464 69.1% 59 2.8% 63 3.0% 37 1.7% 223 10.5% 85 4.0% 116 5.5% 71 3.4%

18 2416 1649 68.3% 88 3.6% 77 3.2% 58 2.4% 247 10.2% 116 4.8% 88 3.6% 93 3.8%

19 2201 1507 68.5% 72 3.3% 64 2.9% 45 2.0% 232 10.5% 114 5.2% 83 3.8% 84 3.8%

Totals 40959 28371 69.3% 1513 3.7% 1155 2.8% 685 1.7% 4250 10.4% 1867 4.6% 1764 4.3% 1354 3.3%

Day

Number of Trips Detected by Sensors

AE TripsDetected by All Detected by 1 out of 3 Detected by 2 out of 3 Not Detected

P(BCD) P(BCD) P(BCD) P(BCD) P(BCD) P(BCD) P(BCD) P(BCD)

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 11

TABLE 6 Individual, Joint and Conditional Probability of Detection at Consecutive Sensors

Probability Measured Derived

(Assuming Independence)

P(B) 87.9%

P(C ) 86.8%

P(D) 79.1%

P(BC) 79.6% 76.3%

P(CD) 73.6% 68.6%

P(BD) 73.8% 69.5%

P(BCD) 69.3% 60.3%

P(BCD)' 3.3% 0.3%

P(B/C) 91.8% 87.9%

P(B/D) 93.4% 87.9%

P(C/B) 90.6% 86.8%

P(C/D) 93.0% 86.8%

P(D/B) 84.0% 79.1%

P(D/C) 84.8% 79.1%

Impact of Sensor Class and Antenna

The sensitivity to sensor Class and antenna configuration was tested in the same corridor.

Sensors were deployed at two locations as described in Table 7.

TABLE 7 Location Descriptions

Sensor Route Direction Location

Reference Sensor I-270 NB On Shoulder Pole of Overhead Sign Structure

Just before Wootton Pkwy Overpass

Control Sensor &

Test Sensor I-270 NB On Shoulder RTMS Pole

Just before the RT 28 / Gude Dr. Overpass

Over a period of successive weeks, a different configuration of BT test sensor was

deployed. In each configuration, the control sensor was mounted directly above the test sensor

on the same pole. The control and reference sensor were a Class one radio with the 3 dBi dipole

antenna, each mounted about 10 feet above the roadway on the east side of the road. The number

of matched pair between the control and reference sensor were compared to the number of

matched pairs between the test sensor and the reference sensor. During week one the test sensor

was configured with a Class one BT radio and an isotropic antenna. Week two the test sensor

was configured with a Class 2 radio, and a 3dBi dipole antenna. Week three the test sensor was

configured with a Class 2 radio and an isotropic antenna. The comparison of the number of

northbound and southbound traversals registered is shown in Table 8.

The value in the total column indicates the overall performance. In northbound direction

the Class I with an isotropic antenna and a Class II with a 3dBi antenna performed similarly,

capturing 53.3% and 55.1% of the traversals respectively. The Class2 Isotropic antenna captured

35.1% of the traversals.

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 12

In southbound direction the Class I with an isotropic antenna captured 43.1% while Class

II with a 3dBi antenna captured 50.9%, and the Class2 Isotropic antenna captured only 19.4% of

the traversals. The Class 2 with isotropic will have an effective range of approximately 50 feet,

accounting for the 35% diminished detection in the northbound direction. This is amplified in the

southbound lanes where mounting on the east shoulder will further diminish the coverage range

in the southbound lanes.

The captured traversals were also analyzed by the total number of traversals in a 5

minutes period in Table 8. The Class 2 with the 3dB antenna performed relatively constant in

both directions, while the Class 1 with an isotropic antenna appears to vary with the density of

available Bluetooth devices. Note that the power rating of the sensor applies to its transmission

capability only while any antenna gain amplifies both the transmission as well as the received

signal from the BT device. The pattern indicates that the 3dB antenna is more critical to

consistent detection than the broadcast power of the transceiver. However, such patterns may

also be dependent on the manufacture and resulting characteristics of the radio.

TABLE 8 Percent of Traversals vs. Control Sensor

Number of Detections

in 5 minutes Class 1 - Isotropic Class 2 - 3dBi Dipole Class 2 - Isotropic

Northbound

0-10 82.2% 62.6% 43.1%

10-20 79.8% 54.5% 34.0%

20-30 59.8% 54.1% 35.4%

30-40 40.7% 55.4% 35.1%

40-50 37.6% 54.9% 33.0%

50-60 30.6% 53.3% 32.4%

60-70 33.9% 57.1% -

Total 53.3% 55.1% 35.1%

Southbound

0-10 67.2% 54.2% 22.0%

10-20 37.3% 49.6% 18.7%

20-30 32.6% 49.7% 19.3%

30-40 57.1% 53.0% 19.6%

40-50 78.4% 57.7% 19.4%

50-60 - - 5.9%

60-70 - 31.1% -

Total 43.1% 50.9% 19.4%

SUMMARY AND CONCLUSION Successful application of Bluetooth

TM traffic monitoring technology requires consideration and

understanding of the detection properties of BluetoothTM

technology. Detection properties vary

with the Class of radio, scan period, antenna gain, and antenna height. Due to the relationship

between time in the detection zone and probability of detection, deployment should be planned

so that vehicles spend 10 seconds or more within the detection range of the BT sensor with a

scan period of 5.12 seconds or greater. On freeways, this equates to a Class 1 radio with a 3dB

Young, Sharifi, Sadrsadat, Urena Serulle and Sadabadi 13

antenna. On slower speed facilities, lower powered radios and/or lower gain antenna may be

used without significantly diminishing the probability of detection. The probability of detection

when sensors are mounted at appropriate height (about 10 feet) and properly sized approaches

90% as demonstrated in the analysis of consecutive sensors.

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