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Cited by 243Autonomous Vehicle Technology and SafetyVehicle Dynamics and Control SystemsHuman-Automation Interaction and Safety

The DOI matches its Crossref record.

Towards a viable autonomous driving research platform

Wei, Junqing, Snider, Jarrod M., Kim, Junsung, Dolan, John M., Rajkumar, Raj, Litkouhi, Bakhtiar·2013·2013 IEEE Intelligent Vehicles Symposium (IV)
DOI 10.1109/ivs.2013.6629559
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Abstract

We present an autonomous driving research vehicle with minimal appearance modifications that is capable of a wide range of autonomous and intelligent behaviors, including smooth and comfortable trajectory generation and following; lane keeping and lane changing; intersection handling with or without V2I and V2V; and pedestrian, bicyclist, and workzone detection. Safety and reliability features include a fault-tolerant computing system; smooth and intuitive autonomous-manual switching; and the ability to fully disengage and power down the drive-by-wire and computing system upon E-stop. The vehicle has been tested extensively on both a closed test field and public roads.

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Crossref · 10.1109/ivs.2013.6629559

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  • Lidar has difficulties with some weather conditions like fog and snow, and radars lack the necessary resolution for many perception tasks.

    “An easy alternative is to use an alternate sensing modalities for perception, but lidar also has difficulties with some weather conditions like fog and snow [146], and radars lack the necessary resolution for many perception tasks [51].”

    From A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2020) · cites this paper as [51]

  • The lack of precision for estimating shape of objects is a major drawback when radar is used in perception systems; the resolution is simply too low.

    “The lack of precision for estimating shape of objects is a major drawback when it is used in perception systems [51], the resolution is simply too low.”

    From A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2020) · cites this paper as [51]

Citations

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Research works printed but not linked: 16

  1. 10.1109/ROMAN.2009.5326205 · DOI
  2. vijayenthiran, 2011, Volkswagen Shows off Self-Driving Auto Pilot Technology for Cars
  3. 10.1109/IVS.2010.5547988 · DOI
  4. 10.1007/978-3-540-73429-1_1 · DOI
  5. 10.1002/rob.20255 · DOI · Paper page
  6. pomerleau, 1989, Alvinn: An autonomous land vehicle in a neural network, Advances in Neural Information Processing Systems 1
  7. thrun, 2012, What We're Driving at
  8. 10.2514/1.39487 · DOI
  9. pinkow, 2012, Continental Tests Highly-Automated Driving
  10. 10.1109/IVS.2011.5940531 · DOI
  11. 10.4271/2012-01-0292 · DOI
  12. markoff, 2010, Google Cars Drive Themselves in Traffic
  13. grisleri, 2010, The braive autonomous ground vehicle platform, Proc Intelligent Autonomous Vehicle, 7, 497
  14. 10.1109/5254.941364 · DOI
  15. kim, 2012, SAFER: Systemlevel architecture for failure evasion in real-time applications, Proc 19th IEEE Real-Time Systems Symp (RTSS)
  16. 10.1109/JPROC.2011.2132790 · DOI

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Metadata

Authors
Wei, J., Snider, J. M., Kim, J., Dolan, J. M., Rajkumar, R., & Litkouhi, B.
Affiliations
  • Carnegie Mellon University (US)
  • General Motors (United States) (US)
ORCID
Dolan, John M.
Venue
2013 IEEE Intelligent Vehicles Symposium (IV)
Publisher
IEEE
Published
2013-06
Pages
763-770
ISSN
1931-0587 (ISSN-L)
DOI
10.1109/ivs.2013.6629559
OpenAlex
W2107656445
Cited by
243
References
0
Citations by year
2026: 3 · 2025: 4 · 2024: 12 · 2023: 17 · 2022: 11 · 2021: 20 · 2020: 36 · 2019: 34 · 2018: 35 · 2017: 24 · 2016: 16 · 2015: 18 · 2014: 12 · 2013: 1
FWCI
19.97
Type
conference paper
Language
en
Open access
closed
Locations
IEEE Intelligent Vehicles Symposium (publishedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
  • Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
  • Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
Keywords
autonomous driving, research platform, trajectory generation, lane keeping, lane changing, vehicle-to-infrastructure communication, vehicle-to-vehicle communication, pedestrian detection, fault-tolerant computing, drive-by-wire, vehicle safety

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