Integrated Sensor Technologies Preventing Accidents Due to Driver Fatigue

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Integrated Sensor Technologies Preventing
Accidents Due to Driver Fatigue

• By
• Carl Tenenbaum
• David Haynes
• Philip Pham
• Rachel Wakim

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Us Vehicle Deaths
Roughly 100 Deaths per Day
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Causes of Car Accidents

1. Distracted Drivers (12 was Driver Fatigue)
2. Driver Fatigue
3. Drunk Driving
4. Speeding
5. Aggressive Driving
6. Weather

According to Sixwise.com
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Driver Fatigue Results

• The National Highway Traffic Safety
  Administration Yearly Statistics
• 100,000 police-reported crashes
• 1,550 deaths
• 71,000 injuries
• 12.5 billion in monetary losses.

It is difficult to attribute crashes to sleepiness
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Sense-Sensor Technology

• David Haynes

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Head Position Detection

• Sense changes in Head Position Tilt
• Gives off a warning if the Head Tilt is facing a
  downward angle. Does Not detect head backwards or
  turned.
• Head Position Down is the Last Stage of Sleep
  Onset. Usually too late and no warning to Driver.

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Behavioral Detection

• Sense Erratic Driving Behavior
• Stores Profile of Persons Driving Behavior
• Compares Profile as Drivers Steering and Braking
  Reaction Time

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Voice Detection

• Sense changes in Discrete Voice Parameters such
  as pitch, frequency, latency and amplitude.
• A complex detection algorithm compares normal
  voice to sample of potential fatigued voice
• Can be integrated in GPS or command oriented car
  systems

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Optical Detection

• A camera or system of cameras monitor the
  drivers facial features for signs of drowsiness.
• Computer algorithms analyze blink rate and
  duration. Infrared LEDs are used to enhance pupil
  detection.
• Yawning and sudden head nods are also detected.

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Biometric Detection

• Capacitive Array on vehicle ceiling detects
  changes in drivers body position.
• Sensors placed on steering wheel, seat, or
  wristwatch device monitor drivers vital signs
  for analysis.
• Low power Doppler radar monitors vital signs and
  body position for analysis.
• Artificial neural network software analyzes
  steering wheel behavior for indicators of fatigue.

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Biometric Detection
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Combining Sensor Technology and Real-world
Applications

• Rachel Wakim

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To be attractive, a vehicle sensor system should
be

• Fairly inexpensive,
• Accurate, with a quick response time,
• Integrated with the car design, or at least plug
  and play,
• Noninvasive,
• Discreet, and non-distracting,
• Adaptable to different user conditions i.e.,
  sunglasses, gloves.

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Head/eye Camera

• Measure head tilting/eye closing/yawning as signs
  of fatigue or drowsiness.
• Non-invasive, no need for user
• interface.
• Can be thwarted by sunglasses or hats. Driver
  movement may confuse the camera.
• 1/5 people do not show eye closure as a warning
  sign. US Dept. of Transportation

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Possible Camera Locations
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Wheel sensor

• Use sensors on steering wheel to measure skin
  temperature and conductivity, pulse, etc.
• Estimate heart rate variability can detect
  drowsiness.
• Combines many different
  metrics to get an overall
  assessment of the users
  state.
• Requires use of both hands,
  without gloves.

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Seat sensor

• Two pieces of conductive fabric on the drivers
  seat (backrest) can take an ECG
• measurement.

• Or on bottom of seat, with wheel as ground.
• Needs impedance compensation for the drivers
  shirt/coat, etc.

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Wireless wrist monitor

• Wristwatch capable of detecting heart rate, skin
  temperature and conductance.
• Example Exmovare Empath Watch
• Transmits via Bluetooth to phone which can signal
  out easily extended to cars, many of which
  already are Bluetooth compatible.
• Current design is 3.3 long, 1.7 wide, and 1.3
  tall.
• Can be bulky, and may
• not be appealing enough
• currently undergoing remodeling

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ACT Decision Making

• Philip Pham

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Corrective and Prevention Actions

• Elevated Alarms
• Provide Visual Alarm (lights, signs, etc.)
• Provide Audio Alarm (warning tone or voice)
• Recommend short nap (prevent car to start
  studies show 15-minute nap increases alertness to
  4-5 hours more)
• Mechanical and Electronic Stimulations
• Counteract to the effects (steering wheel turn,
  lane drifting, speed change, etc.)
• Apply brake to slow down to safety
• Dispatch for help if no response

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Corrective Flowchart Actions
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Mercedes Attention Assist
Daimler Chrysler Website
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Technology

1. Audio Video Warning Circuits
2. Starter-Disabled Circuit
3. Auto-Pilot Control
4. Communication Protocol

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Current Driver Fatigue Products
Products Price Accurate Non-Invasive Effective Overall Score Company Detection Type
Driver Nap Zapper 25 50 3 3 5 No Nap Motion
Nap Alarm (LS888) 500 80 5 6 6 Leisure Auto Security Optical
DD850 Driver Fatigue Monitor 500 80 5 6 6 Eye Alert Optical
Exmovare Empath WristWatch 1000 90 6 5 6 Exmovare Biometric
Driver Assist Package 3000 90 7 7 7 Mercedes Behavioral
Undeveloped Market. US Consumer Car GPS Market
is 5.1 Billion Market in 2010.
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References

• Y. Lin, H. Leng, G. Yang, and H. Cai, An
  intelligent noninvasive sensor for driver pulse
  wave measurement, IEEE Sensors J., vol. 7, no.
  5, pp. 790799, May 2007.
• X. Yu, Real-time Nonintrusive Detection of
  Driver Drowsiness, May 2009
• US Department of Transportation, An Evaluation
  of Emerging Driver Fatigue Detection Measures and
  Technologies, June 2009
• Y. Jie, Y. DaQuan, W. WeiNa, X. XiaoXia, and W.
  Hui, Real-Time Detecting System
• of the Drivers Fatigue, 2006
• Exmovere Holdings Inc, The New Biotechnological
  Frontier The Empath Watch. Feb. 2011
  http//www.exmovere.com/pdf/Exmovere_Wearable_Sens
  or_Research.pdf
• S. Kar, M. Bhagat, and A. Routray, EEG signal
  analysis for the assessment and quantification of
  drivers fatigue, June 2010
• The 6 Most Common Causes of Automobile
  Crashes(2010). Retrieved February 9th 2011, from
  http//www.sixwise.com/newsletters/05/07/20/the_6_
  most_common_causes_of_automobile_crashes.htm
• What causes Fatigue (2010), Retrieved February
  21st 2011, from http//unsafetrucks.org/driver_fat
  igue.htm
• Kingman P. Strohl, M.D, Jesse Blatt, Ph.D,
  Forrest Council, Ph.D, Kate Georges, James Kiley,
  Ph.D, Roger Kurrus, Anne T. McCartt, Ph.D, Sharon
  L. Merritt, Ed.D., R.N, Allan I. Pack, Ph.D.,
  M.D, Susan Rogus, R.N., M.S., Thomas Roth, Ph.D,
  Jane Stutts, Ph.D, Pat Waller, Ph.D., David
  Willis, Drowsy Driving and Automobile Crashes
  (2010), Retrieved February 21st 2011, from
  http//www.nhtsa.gov/people/injury/drowsy_driving1
  /drowsy.htmlNCSDR/NHTSA

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References Continue

• Toshiyuki Matsuda, Masaaki Makikawa, ECG
  Monitoring of a Car Driver Using
  Capacitively-Coupled Electrodes 30th Annual
  International IEEE EMBS Conference ,Vancouver,
  British Columbia, Canada, August 20-24, 2008
• Luis M. Bergasa, Jesús Nuevo, Miguel A. Sotelo,
  Rafael Barea, and María Elena Lopez Real-Time
  System for Monitoring Driver Vigilance IEEE
  Transactions on Intelligent Transportation
  Systems, vol. 7, no. 1, March, 2006
• The John Hopkins university Applied Physics
  Laboratory Technologies Drowsy Driver Detection
  System http//www.jhuapl.edu/ott/technologies/fea
  turedtech/DDDS/
• George Washington University Center for
  Intelligent Systems Research Driver Assistance
  Drowsy/Fatigued Driver Detection
  http//www.cisr.gwu.edu/research/drowsy_details.ht
  ml
• EURASIP Journal on Advances in Signal Processing
  Volume 2010 (2010), Article ID 438205 Driver
  Drowsiness Warning System Using Visual
  Information for Both Diurnal and Nocturnal
  Illumination Conditions http//www.hindawi.com/jo
  urnals/asp/2010/438205/
• Jennifer F. May, Carryl L. Baldwin
  Transportation, Driver fatigue The importance
  of identifying causal factors of fatigue when
  considering detection and countermeasure
  technologies, Research Part F 12 (2009) 218224
• H.P. Greeley, E. Friets,, J.P. Wilson, S.
  Raghavan and J. Picone J. Berg, Detecting
  Fatigue From Voice Using Speech Recognition,
  2006 IEEE International Symposium on Signal
  Processing and Information Technology