Pre 1980 advancements in computing technology (late 60s late 70s) - - PowerPoint PPT Presentation

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Pre 1980 advancements in computing technology (late 60s late 70s) - - PowerPoint PPT Presentation

Jul 13, 2023 38 likes •195 views

This term paper explores the impact of autonomous vehicles on safety. In doing so, the paper aims to delve deeper into the aspects of the need for a safety centric technology enhancement. An insight into the most possible causes of

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 This term paper explores the impact of

autonomous vehicles on safety. In doing so, the paper aims to delve deeper into the aspects of the need for a safety – centric technology

  • enhancement. An insight into the most

possible causes of such an excitement in the field of autonomous vehicles has a lot to do with the safety and so, a review of the safety enhancement technologies in these vehicles shall be

  • covered. However, challenges shall still

remain in order to fulfill the longer term goal of seamless adoption and integration of this technology. The last part of this paper shall deal with that aspect in detail.

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 BACKGROUND  AUTONOMOUS VEHICLES  WHY SAFETY?? (IMPACTS)  SAFETY ENHANCEMENT

TECHNOLOGIES (REVIEW)

 MARKET PENETRATION  CHALLENGES

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Pre 1980

  • GM presented a vision for

“driverless cars” (1939)1

  • US DOT initiatives heralded by

advancements in computing technology (late 60s – late 70s)

1990s

  • NAHSRP – main goal: develop

specifications for a fully automated highway system.

  • NAHSC2 – motivation: help build

broad interests required for early development & deployment of fully automated highway systems.

2000s

  • DARPA Grand Challenge3 – 2004,

2005 & 2007.

  • Thrust towards advancement in

related technology –> ACC, self – parking, automatic lane keeping & crash avoidance systems.

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 Lot of excitement since 2012

 Potential benefits:

Additional mobility

  • ption

for elderly.

Better & more productive use of travel time.

Safer alternative- very high crash reduction possibilities

Reduction in emission & fuel consumptions – better driving & braking standards

Increased capacity on highways due to closer spacing of vehicles on the road.

KPMG (2012)

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Fatality rates for year 2007 – 41059 (US)4, ~ 40000 (EU)5.

Automotive industry indulging in active research on crash avoidance technologies due to the massive benefits from the same.

Benefits

Crash reduction – human error plays a dominant role in >90% of the crashes; sole reason for crashes (75% cases)7

Of these 75% crashes, 41% - recognition errors & 34% - driver indecision.

Braking failure – 25% of all crashes; braking

  • ne second earlier reduced all brake related

crashes by half.6

Billions of dollars in crash related losses saved !!!

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Safety enhancement technologies (Control systems) Lateral Control Lane Departure Warning System (LDWS) Lane Keeping Assist Systems (LKA) Parallel Parking Assist Longitudinal Control Adaptive Cruise Control (ACC) Pre Crash Braking Assist

  • Lane Departure Warning Systems

(LDWS)

  • “to avoid run – off road and sideswipe

crashes and to support the driver in lane – keeping.”8

  • Methods:
  • Embedded magnetic markers on the

field (most accurate)9

  • Highly accurate GPS maps.
  • Image processing (most suitable)7
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  • Lane Keeping Assist Systems (LKA)
  • small adjustments to the steering to ensure

that the vehicle stays in the same lane.

  • nly a small amount of torque required to
  • vercome actuation11 –> driver alertness issue

–> rectified by asking for certain driver input

  • ver time.
  • Parallel Parking Assist
  • fitted with a rear view cam assisting the driver

while he controls the braking & acceleration.

Konca M & Forrest A (2007)

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  • Adaptive Cruise Control (ACC)
  • controlling the speed at which the vehicle

moves wrt vehicle immediately ahead.

  • dynamic process, speed shifts occur all

the time.

  • when the vehicle ahead moves into

another lane, speed reset again.11

  • Pre – Crash braking assist
  • use ACC to detect possible collisions.
  • If high rate, pre – arm the brakes;
  • reduces SSD.
  • reduces collisions due to bad braking.11

Konca M & Forrest A (2007)

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Littman (2013) Littman (2013) KPMG (2012)

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 Reliability & Robustness of

Technology

“Since cars will likely travel more closely together than they do currently, fail – safe braking is one essential to avoid a chain

  • collision. Also, it’s hard to see autonomy getting

much traction until sensor technology is widely installed on cars – they have to talk with each

  • ther for it to work.” - Dr. Azim Eskandarian.

Other apprehensions – GPS spoofing, non – performance of LIDAR in inclement weather.

Altera (2010)

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 Consumer Perception & Market

Penetration

Skepticism towards autonomous vehicles is a consequence of trust (mistrust)

“Public

  • pinion

can be gained

  • nly

by demonstration, not by use.” – Prof Clifford Nass.

Consumers willing to cede “control” to the autonomous vehicle only if the vehicle drives more adeptly than human.

Major deterrent – the idea that a machine could kill a human being, despite their very slim chances.

Skill degradation – major issues during possible system failures.

FAA advised pilots to fly more manual than autopilot.

Risk homeostasis – drivers willing to accept more risks as they blindly believe in technology.

Kurzweil (2011)

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 Legislation & Liability

Legislation is cloudy

  • ver

the status

  • f

autonomous vehicles; different states have different rules. (Legal: CA, NV , FL)

Future issues dealt in terms of negative liabilities –> what is not illegal, is legal. (Dr. Ryan Calo)

Universally acceptable legislation lacking –> direct impact on safety in the minds of the consumer.

Major liability issues –> nobody wants to be blamed during the event of a crash.

Directly impacting insurance companies which provide cover for these risks.

Risks?? What kind of risks?? Even they don’t know that.

Morris - BC

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1.

Robert A. Ferlis. (2007). The Dream of an Automated Highway. http://www.fhwa.dot.gov/publications/publicroads/07july/07.cfm

2.

Cheon, S. (2003). An Overview of Automated Highway Systems (AHS) and the social and institutional challenges they face. http://www.uctc.net/papers/624.pdf

3.

Lu, B & Moore, M (2012), Autonomous Vehicles for Personal Transport: A Technology Assessment http://www.pickar.caltech.edu/e103/Final%20Exams/Autonomous%20Vehicles%20for%20Personal%20T ransport.pdf

4.

NHTSA (2008). National Motor Vehicle Crash Causation Survey – Report to the Congress. http://www- nrd.nhtsa.dot.gov/Pubs/811059.PDF

5.

European Commission/ Information Society and Media, i2010:Intelligent Car http://europa.eu.int/information_society/activities/policy_link/brochures_2006/documents/intelligent_ca r.pdf

6.

IVsource.net/(Article)Low Speed Automation Using Multiple Sensors( July 31, 2000) http://www.ivsource.net/archivep/2000/jul/a000731_carsense.html

7.

Lay, R & Saxton, L. Vehicle Highway Automation. http://onlinepubs.trb.org/Onlinepubs/millennium/00144.pdf

8.

Intelligent Vehicle Technology and Trends (e-book) / Richard Bishop http://site.ebrary.com/lib/wpi/Doc?id=10091339

9.

Konca, M & Forrest, A. (2007). Autonomous Car & Society IQP OVP 06B1. Worcester Polytechnic Institute,

  • MA. http://www.wpi.edu/Pubs/E-project/Available/E-project-043007-

205701/unrestricted/IQPOVP06B1.pdf

10.

Littman, Todd (2013). Autonomous Vehicle Implementation Predictions: Implications for Transport

  • Planning. Victoria Transport Policy Institute. http://www.vtpi.org/avip.pdf

11.

KPMG (2012), Self-Driving Cars: The Next Revolution, KPMG and the Center for Automotive Research; at www.kpmg.com/Ca/en/IssuesAndInsights/ArticlesPublications/Documents/self-driving-cars-next- revolution.pdf

12.

Mother Nature Network (2012-09-25). Self-Driving Cars will Take Over By 2040. http://www.forbes.com/sites/eco-nomics/2012/09/25/self-driving-cars-will-take-over-by-2040/

13.

Franceschi-Bicchiera, L. (2012). Drone Hijacking? That’s Just the Start of GPS Troubles. http://www.wired.com/dangerroom/2012/07/drone-hijacking/

14.

Marks, P. (2012). GPS jamming: a clear and present reality. http://www.newscientist.com/blogs/onepercent/2012/02/gps-jamming-a-clear-and-presen.html

15.

Waterman, S. (2012). North Korean jamming of GPS shows system’s weakness. http://www.washingtontimes.com/news/2012/aug/23/north-korean-jamming-gps-shows-systems- weakness/?page=all

16.

Urmson, C. (2012). The self-driving car logs more miles on new wheels. http://googleblog.blogspot.com/2012/08/the-self-driving-car-logs-more-miles-on.html

17.

Human Rights Watch. (2012). Arms: New Campaign to Stop Killer Robots. http://www.hrw.org/news/2013/04/23/arms-new-campaign-stop-killer-robots

18.

Lee, J. and N. Moray (1994). Trust, self-confidence, and operators' adaptation to automation. International Journal of Human-Computer Studies 40: 153-184. www.sciencedirect.com/science/article/pii/S107158198471007X

19.

Federal Aviation Administration (2013). Safety Alert for Operators 13002. F. S. Service. Washington DC, Department of Transportation http://media.nbcbayarea.com/documents/SAFO130021.pdf

20.

WIlde, G. J. S. (1998). "Risk homeostasis theory: an overview." Injury Prevention 4: 89–91. http://injuryprevention.bmj.com/content/4/2/89.full

21.

Smith, W.B (2012), Automated Vehicles are Probably Legal in the United States, The Centre for Internet & Society at Stanford Law School and Center for Automotive Research at Stanford http://cyberlaw.stanford.edu/files/publication/files/2012-Smith- AutomatedVehiclesAreProbablyLegalinTheUS_0.pdf

22.

European Commission (2010), Definition of necessary vehicle and infrastructure systems for Automated Driving (pp. 1–111). Brussels http://ec.europa.eu/information_society/activities/esafety/doc/studies/automated/reportfinal.pdf

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