Transcript In-Pavement Wireless Sensor Network for Vehicle

In-Pavement Wireless Sensor
Network for Vehicle
Classification
Ravneet Bajwa, Ram Rajagopal, Pravin Varaiya and
Robert Kavaler
IPSN’11
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Motivation
• Intrusive technologies
– Piezoelectric sensors, inductive loops
– High installation and maintenance costs
• Non-intrusive technologies
– Infrared, video imaging
– Sensitive to traffic and weather condition
• Propose an alternative system base on a WSN
that is both cost effective and insensitive to
environmental conditions
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Problem Statement
• Cars, buses, three-axle single unit trucks, and
five-axle single trailer trucks
• A vehicle travels in a traffic lane at some
varying speed and we wish to count the
number of axles and the spacing between
each axle in an accurate manner
Proposed WSN System
• Vibration sensor (accelerometer) embedded in the road
– Calculate the axle spacings
• Vehicle detection sensor (magnetometers)
– Report the arrival and departure times of a vehicle
• Access point (AP)
– Send commands to sensors
– Log the incoming data
• First in-pavement, easy
to deploy, WSN based
system for counting axles
and axle spacing
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Wireless Vehicle Detection Sensor
• Measures the changes in magnetic field to infer the local
presence of a vehicle
• Synchronous Nanopower Protocol(SNP), a
TDMA based protocol
– Last 10 years with a single 7200 mAhr battery
• Given the arrival times tai and taj at the two
sensors i and j, the speed v will be
v = dij / |taj – tai|
• Estimate the length(L) of the vehicle
L = v(tdj - taj)
Wireless Vibration Sensor
• Sample the analog output of an accelerometer and transmit
the data via a radio
• Sample fast enough to capture the transient vibrations
• Sensor needs to be insensitive to the vehicles traveling in the
neighboring lanes
• Insensitive to the truck engine and environmental noise
• Sensor resolution target is 500 ug
• Bandwidth 50Hz
• Sampling frequency 512 Hz( > 5 times Nyquist Frequency)
– Power consumption increases for higher sampling rates
Selecting an accelerometer
• SD1221-005 has higher sensitivity and lower noise
density
• However, it consumes more than 20 times the current
than MS9002.D and has to be operated at higher voltage
• Both devices achieved the aimed minimum resolution of
500 ug
– Select MS9002.D due to its low operating voltage and low
current consumption
Filters for mitigating sound noise
• Accelerometer is sensitive to sound
• MS9002.D behaves like a microphone under the
device’s bandwidth
• 3rd order low-pass filter with cutoff frequency of 50
Hz is sufficiently aggressive to filter out most of the
sound in the audible spectrum
Casing
• Sound isolation
• Protect the electronics from
rain water and oil spill on the
road
Circuit Description
• 2.5 V supply voltage
• Amplifier with gain 10
• The gain of 10 reduces the range of the
accelerometer to ≈±225mg
• This is necessary in order to ensure
that the quantization noise from the
ADC is less than the noise from the accelerometer
– Otherwise, the resolution of the system will be limited by ADC noise
• The reduced range is still sufficient
– For heavy trucks  ± 200 mg
Outlin
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Communication Protocol Design
• MAC Layer
– TDMA based
– Time is divided into multiple frames with each frames
about 125 ms long
– Each frame is further divided into 64 time slots
– Slot 0 is used by AP to send clock synchronization
information and other commands to the sensors
– AP assigns every node unique time slots and a node ID to
communicate with it.
Application Layer
• Sync Application
– AP sends sync packets on a periodic basis
– Sensor node listens to sync packets every 125 ms
– When the clock converges to steady state, then is listens
for a sync packet only once in 30 s
– Sync application is also used to send commands
– Set Mode, Reset, Set Timeslot, Set RF, Download Firmware,
Set ID
Application Layer
• Accelerometer Application
– Idle Mode: accelerometer and related circuitry are
turned off by disabling the voltage regulator
• Once every 30 s, the microcontroller and the
transceiver wake up and acquire the sync packet
Application Layer
– Raw Data Mode: microcontroller wake up every
1/512 s, and samples the analog output from
accelerometer
• 32 samples at a sampling freq. 512Hz, and each sample
containing 12 bits of information
• In every frame(125ms) we accumulate 96 bytes of
information to transmit
• To have a reasonable packet size, we fragment the data
in two parts, 48 bytes each, and transmit it using two
different time slots 62.5ms apart
Application Layer
• Download Firmware Application
– Reprogram the entire flash memory of a sensor node over
the air
– AP transmits new code repeatedly and the node updating
its code in small pieces
– Only the data that do not overwrite the current running
program are updated by the node
Axle Detection(ADET) Algorithm
Axle Detection(ADET) Algorithm
• Using data from 4 trucks at different speeds,
we observed the bandwidth of the energy
signal and empirically defined by M(v) = 900/v
• Low-pass filter is optional
• Minimum time separation ζ(v) was chosen by
assuming that the axles are at least 6ft apart
Wide Lane ADET Algorithm
• Wander movement in a lane
• Combining vibration readings from multiple sensors
• Delay  Di = di / v
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Experiment Setup
• 4 vibration sensors and 4 vehicle detection sensor were
installed on California Highway I-680
• Vehicles come from Sunol Weigh
Station
• Slow down at weigh station
– Easy to collect ground truth
• Data from 53 different trucks, ranging
from pickup trucks to 5-axle
commercial trucks
Installation
• Boring a 4-inch diameter hole approximately 2.25 inches deep
• Installed on a road in less than 20 minutes
• Installation of a small sensor is much cheaper and convenient
than installing special material pavements required for
piezoelectric sensors
Deployment Challenges
• Packet Drops
– Drop rate was low(1%)  retransmit packets with a delay
of 1 packet  drop rate is almost 0
• Packet 1, 2, 1, 2
• Vehicle Wander
– use Wide Lane ADET algorithm
• Sensor failure
– Sensor k did not work
– Vibration data was available from 3 sensors
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Vibration Sensor Performance
• Noise with no vehicle in vicinity
– 414 ug RMS
• Truck was parked on top of the sensor with
engine were on vs. truck blew its horn
– 7% vs. 4%
• With a heavy truck traveled in the closed lane
– Sensor did not register any noticeable peaks
Axle Count
• Error  difference between the ground truth axle count and
the estimated axle count
• By combining the measurements from all sensors, the
algorithm always gives the correct axle count
• Error results form the wander movement
Axle Spacing
• Left: for tandem axle
• Middle: pick up trucks, small two axle
commercial trucks
• Right: axles of trailers
Outline
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Motivation
Introduction
Description
Communication Protocol Design
Experiment Setup
Performance
Conclusion & Future Work
Conclusion
• A novel algorithm that estimates the axle count and spacing
from pavement acceleration was designed and tested on the
collected data
• ADET is simple enough to implement a sensor node with
limited processing power
• Majorities of the existing technologies are wired solutions
• Both the sensors and the AP are powered by batteries and
consume much less power than other technologies
• The installation procedure and sensors themselves are much
cheaper
• There is minimal maintenance compared to other
technologies
Future Work
• Find an optimal arrangement of sensors in order to
minimize the number of sensors deployed
• Reduce the amount of data transmitted
• Reduce the sensor power consumption