In-Pavement Wireless Sensor Network for Vehicle Classification

AUTHORS:RAVNEET BAJWA, RAM RAJAGOPAL, PRAVIN VARAIYA AND

ROBERT KAVALER

PRESENTER: XIANGYI GU

In-Pavement Wireless Sensor Network for

VehicleClassification

Outline

MotivationIntroductionDescriptionCommunication Protocol DesignExperiment SetupPerformanceConclusion & Future Work

Motivation

Intrusive technologies Piezoelectric sensors, inductive loops (examples) High installation and maintenance costs

Non-intrusive technologies Infrared, video imaging(examples) Sensitive to traffic and weather condition

Propose an alternative system base on a WSN that is both cost effective and insensitive to environmental conditions

Transportation agencies collect vehicle classification information to plan highway maintenance programs, evaluate highway usage and optimize the deloyment of various resources on the road

Problem Statement

Cars, buses, three-axle single unit trucks, and five-axle single trailer trucks (classifying vehicles)

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, easyto deploy, WSN basedsystem for counting axlesand axle spacing

Outline


Wireless Vehicle Detection Sensor

Measures the changes in magnetic field to infer the local presence of a vehicle

Synchronous Nanopower Protocol(SNP), aTDMA based protocol Last 10 years with a single 7200 mAhr battery

Given the arrival times tai and taj at the twosensors i and j, the speed v will bev = dij / |taj – tai|

Estimate the length(L) of the vehicleL = v(tdj - taj)

Wireless Vibration Sensor

Sensor needs to be insensitive to the vehicles traveling in the neighboring lanes

Sample fast enough to capture the transient vibrations

Insensitive to the truck engine and environmental noise

The sensor has to be well coupled to the road way and be resistant to heavy vehicle traffic

Challenges

•Sample the analog output of an accelerometer and transmit the data via a radio•Designing a sensor that measures pavement vibrations for axle detection have many unique challenges

•Sensor resolution target is 500ug•Bandwidth 50Hz•Sampling frequency 512 Hz( > 5 times Nyquist Frequency)-Power consumption increases for higher sampling rates

Axle detection and counting

Given vehicle speed measurement and reliable measurement from the wireless vibration sensor, we still need to construct an axle detection algorithm that has good performance

There are two important challenges in detecting individual axles:

A B.The vibration

signals from successive axles tend to blend.

In wide highway lanes, vehicles can experience significant wander

Sensor Design

Resolution: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

Noise: Filters for mitigating sound noise

Accelerometer is sensitive to soundMS9002.D behaves like a microphone under

the device’s bandwidth3rd 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 isolationProtect the electronics from

rain water and oil spill on theroad

Circuit Description

2.5 V supply voltageAmplifier with gain 10The gain of 10 reduces the range of the accelerometer to ≈±225mgThis 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 noiseThe reduced range is still sufficient

For heavy trucks ± 200 mg

Outline


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

Results of ADET on truck49( two single axles and one tandem axle), a(n) is the measured acceleration in mg, e(n) is the scaled energy in mg2, and s(n) is smooth energy in mg2. The red asterisks on s(n) are the axle locations found by ADET. By reducing the minimum axle sepatation, the individual axles in the tandem axle can also be detected as shown by black circle

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 optionalMinimum time separation ζ(v) was chosen by

assuming that the axles are at least 6ft apart

Wide Lane ADET Algorithm

Wander movement in a laneCombining vibration readings from multiple

sensorsDelay Di = di / v sennor2 will measures the peak enery a little later

than sensor 1, so the individual energy measurements nedd to be appropriately delayed

System representation of the adjustment made to correct vehicle wander. The energy if the total signal at time n is the maximum of the energy of the individual signals ei(n) is each sensor i.

Outline


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, rangingfrom pickup trucks to 5-axle commercial trucks

The WSN setup at Suno; site. DHMN are vehicle detection sensors shereas I,J,K,L are vibration sensors

Installation

Boring a 4-inch diameter hole approximately 2.25 inches deep

Installed on a road in less than 20 minutesInstallation 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%) (compare 50 feet away)

retransmit packets with a delay of 1 packet drop rate is almost 0 Packet 1, 2, 1again, 2again

Vehicle Wander Because vehicles are not taveling stright in a lane we would like

to choose data from vehicle sensor that was closest to the tires use Wide Lane ADET algorithm

Sensor failure Sensor k did not work Vibration data was available from 3 sensors

Outline


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( Strongly affected by truck wander

Performance of ADET using individual sensors and combinations of sensors. Count Err. Is the difference between the ground truth and ADET estimate. Under each sensor column is the observed frequency of the errors.

Axle Spacing

Left: for tandem axleMiddle: pick up trucks, small two axle

commercial trucksRight: axles of trailers

Distribution of estimated axle spacings. There are three clusters in the data separated by empty bins. The dotted lines represent the means of there clusters

Outline


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 technologiesThe installation procedure and sensors themselves are

much cheaperThere 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 transmittedReduce the sensor power consumption

Thank you very much!

In-Pavement Wireless Sensor Network for Vehicle Classification

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