Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and...

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Integrated Approach for Nonintrusive Detection of Driver Drowsiness Xun Yu Department of Mechanical and Industrial Engineering University of Minnesota, Duluth

Transcript of Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and...

Page 1: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Integrated Approach for Nonintrusive Detection of Driver

Drowsiness

Xun Yu

Department of Mechanical and Industrial EngineeringUniversity of Minnesota, Duluth

Page 2: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Project Background and Objective

Driver’s drowsiness is one of the major causes of deadly traffic accidents.

(NHTSA, more than 100,000 crashes are caused by drowsy drivers every year in the US)

Objective:To detect driver drowsiness via biosensors on steering wheel.

Page 3: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Previous Results

Heart rate measurement systems

- Method 1: using conductive fabric as electrodes to measure the electrocardiogram (ECG) signal

- Method 2: using piezo-polymer PVDF (polyvinylidene fluoride) films to measure the force aroused by the heart pulse wave signal

Page 4: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Previous Results7 human subjects were tested on a driving simulator. HRV signal was analyzed and LF/HF ratio was chosen as the index of drive sleepiness stages.

The LF (low frequency)/HF (high frequency) ratio decreases with time, indicating a drowsiness trend.

However, LF/HF ratio has high variability and has different decrasing ratio for different drivers.

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Page 5: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Proposed studyWe propose to use multiple parameter to access the driver’s drowsiness

- LF/HF ratio of HRV signal, it will decrease with drowsiness

- VLF (very low frequency ) of HRV, it will decrease with drowsiness

- RRV (moving average of heart rate time-interval) of HRV signal, it

will increase with drowsiness

- Gripping force variability, it will decrease with drowsiness

- Steering wheel motion: steering angle and angular velocity phase will be used in this study for their high correlation with drowsiness.

Find these gains will be a major task of this study

Page 6: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

System

EEG Measurement as the “gold” standard

Driving simulator

driver Wave Rider 2Cx

PVDF Sensor

Conditioning

Circuit

Data Acquisitio

n CardPCI 6221

Computer

Computer

Heart pulse wave measurement

Steering wheel signal

Page 7: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Correlation analysis between the EEG signal and ECG & steering

wheel signal

Page 8: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Correlation analysis between the EEG signal and ECG & steering wheel signal

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High correlation between EEG and the combined signal array!

Page 9: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

Summary

The combined signal (ECG and steering wheel signal) has high correlation with EEG signal EEG signal is deemed as an accurate way of detecting driver drowsiness) the combined signal could detect driver drowsiness more accurately that using ECG signal alone.

System modeling and tests are underway.

Page 10: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

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Intelligent Pavement for Traffic Flow Detection

Xun Yu, Ph.D Department of Mechanical and Industrial Engineering

University of Minnesota Duluth

Page 11: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

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Objective and Research ApproachEnable the concrete pavement itself to have a sensing capability: traffic flow detection, pavement structural health monitoring, e.g., cracking detection. Sections of a given roadway are paved with piezoresistive carbon-nanotube (CNT)/cement composites. CNTs can also enhance the mechanical strengthAdvantages:

Long service life and low maintenance cost Spot and area detection possibilities for traffic flow behavior

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ExperimentsMethod #1: covalent surface modification with acid treatment

Method #2: non-covalent surface modification with surfactant,

Surfactants, such as sodium dodecyl sulfate (SDS) and dodecylbenzene sulfonate (NaDDBS), can be wrapped around the nanotubes, which in turn can render CNTs to be dispersed in water and mixable with cement

Page 13: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

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Lab TestExperiment Set-up

Page 14: Integrated Approach for Nonintrusive Detection of Driver Drowsiness Department of Mechanical and Industrial Engineering University of Minnesota, Duluth.

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Lab Test Results – Method #2 (NaDDBS)

Piezoresistive response of the CNT/cement composite (CNT: 0.2 wt %)

CNT composite fabricated with method #2 (NaDDBS surfactant)

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Piezoresistive Response Mechanism

Several mechanisms can contribute to the composite’s piezoresistive property: - Intrinsic CNT piezoresitive properties

- Contact resistance changes under stress

- Tunneling effect could be dominant (separation distance between CNTs decreases)

Matrix

Nanotuberesistance

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Effects of CNT doping level and water contend level

The piezoresitive sensitivity does not increase linearly with CNT doping level and water content level.

High CNT doping level can shorten the tunneling channel, but it will be stabilized if over the percolation threshold.

The field emission effect on the nanotube tip can be enhanced by the adsorption of water molecules

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MP

a)f (

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Future Challenges and Plan

Challenges:Need effective large-scale CNT/cement composite fabrication methodsNeed to study the piezoresistive response of CNT enhanced concrete (which has 15~20% of cement)Configuration design for wide area detection

Work plan:Address above challengesRoad tests Explore the civil structural health monitoring application (working with Mn/DOT on a FHWA project)

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Acknowledgement

Funding supported by the Northland Advanced Transportation Systems Research Laboratory, University of Minnesota Duluth, ITS of the University of Minnesota.

Dr. Eil Kwon

Dr. Baoguo Han (Research Associate in our group)

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Road TestTested in NARSRL outdoor research facility

EmbeddedSensors

Sensors array

1.2m

We are dealing with some issues of sealing etc.

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Road TestMeasurement system

Si

Si

Si

Si

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Road Test ResultsFrom the Nickel-particle/cement self-sensing sensors