Skip to main content
SpringerLink
Log in

Sharing Driving Between a Vehicle Driver and a Sensor System Using Trust-Factors to Set Control Gains

  • Conference paper
  • First Online:
Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 868))

Included in the following conference series:

Abstract

This paper presents a method to share the control of a vehicle between a driver and sensors. The vehicle can be driven by a driver, or the sensors can drive the vehicle, or control can be shared between them. In some circumstances, sharing control can allow a human driver to maneuver more safely and efficiently. The gain settings in the controller can be set automatically to be specific to a particular human driver at a particular time. A trust-factor is calculated in real time for the vehicle driver and sensors help the human driver to drive their vehicle. That can correct for any detected weaknesses and inadequacies. A driver might not see a vehicle ahead or a vehicle driver might be drowsy. In an emergency, proficient collaboration between a vehicle and vehicle driver can be vital. This paper examines that interfacing and collaboration. The proposed methods are validated with initial testing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Sanders, D.A., Ndzi, D., Chester, S., Malik, M.: Adjustment of tele-operator learning when provided with different levels of sensor support while driving mobile robots. In: Bi, Y., Kapoor, S., Bhatia, R. (eds.) SAI Intelligent Systems (IntelliSys), vol. 2. Lecture Notes in Networks and Systems, vol. 16, pp. 548–558. Springer, UK (2017). https://doi.org/10.1007/978-3-319-56991-8_41

    Google Scholar 

  2. Sanders, D.A., Sanders, H., Gegov, A., Ndzi, D.: Rule-based system to assist a tele-operator with driving a mobile robot. In: Bi, Y., Kapoor, S., Bhatia, R. (eds.) SAI Intelligent Systems (IntelliSys), vol. 2, Lecture Notes in Networks and Systems, vol. 16, pp. 599–615. Springer, UK (2017). https://doi.org/10.1007/978-3-319-56991-8_44

    Google Scholar 

  3. Sanders, D.A.: Using self-reliance factors to decide how to share control between human powered wheelchair drivers and ultrasonic sensors. IEEE Trans. Neural Syst. Rehabil. Eng. 25(8), 1221–1229 (2017)

    Article  MathSciNet  Google Scholar 

  4. Sanders, D.A.: Non-model-based control of a wheeled vehicle pulling two trailers to provide early powered mobility and driving experiences. IEEE Trans. Neural Syst. Rehabil. Eng. 26(1), 96–104 (2018)

    Article  Google Scholar 

  5. Sanders, D.A., Gegov, A., Tewkesbury, G., Khusainov, R.: Rule-based system to assist a powered wheelchair driver. In: IEEE Proceedings of the Intelligent Systems Conference (IntelliSys) 2017, 7–8 September 2017. IEEE, London (2017)

    Google Scholar 

  6. Sanders, D.A., Sanders, B., Gegov, A., Ndzi, D.: Results from investigating powered wheelchair users learning to drive with varying levels of sensor support. In: Proceedings of the Intelligent Systems Conference (IntelliSys) 2017, 7–8 September 2017. IEEE, London (2017)

    Google Scholar 

  7. Sanders, D.A., Sanders, B., Ndzi, D., Bausch, N.: Using confidence factors to share control between a mobile robot tele-operator and ultrasonic sensors. In: Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2017, 7–8 September 2017. IEEE, London (2017)

    Google Scholar 

  8. Sanders, D.A., Gegov, A., Ndzi, D.: Knowledge-based expert system using a set of rules to assist a tele-operated mobile robot. In: Bi, Y., Kapoor, S., Bhatia, R. (eds.) Intelligent Systems and Applications. Studies in Computational Intelligence, vol. 751. Springer (2017)

    Google Scholar 

  9. US: Mobileye intros smartphone connected driver assistance (ADAS) technology. Telematics News (2012). http://telematicsnews.info/2012/01/12/us-mobileye-intros-smartphone-connected-driver-assistance-adas-technology_j3122. Accessed 13 Nov 2017

  10. Riches: Strategy Analytics: Automotive Ethernet: Market Growth Outlook | Keynote Speech 2014 IEEE SA: Ethernet & IP @ Automotive Technology Day (PDF). IEEE. http://standards.ieee.org/events/automotive/2014/00_Automotive_Ethernet_Market_Growth_Outlook.pdf. Accessed 13 Nov 2017

  11. Rees, K., Park, J.S.: Vehicle Information Access API. W3C Business Group report, W3C and LG Electronics (2014). https://www.w3.org/2014/automotive/vehicle_spec.html. Accessed 13 Nov 2017

  12. ADAS Definition. Autoconnectedcar.com. Archived from the original on 06/10/2012. https://web.archive.org/web/20120610055853/http://telematicsnews.info/2012/01/12/us-mobileye-intros-smartphone-connected-driver-assistance-adas-technology_j3122. Accessed 13 Nov 2017

  13. Banga, B.: Global ADAS and Autonomous Driving Components Market, Analysis & Forecast. Business Intelligence and Strategy Research (2017). https://bisresearch.com/industry-report/global-adas-autonomous-driving-components-market-2026.html. Accessed 13 Nov 2017

  14. Sanders, D.A.: The modification of pre-planned manipulator paths to improve the gross motions associated with the pick and place task. Robotica 13, 77–85 (1995)

    Article  Google Scholar 

  15. Sheridan, T.B.: Tele-operation, telerobotics and telepresence: a progress report. Control Eng. Pract. 3(2), 205–214 (1995)

    Article  Google Scholar 

  16. Sheridan, T.: Humans and Automation: System Design and Research Issues. Wiley (1995)

    Google Scholar 

  17. Sanders, D.A.: Comparing speed to complete progressively more difficult mobile robot paths between human tele-operators and humans with sensor-systems to assist. Assembly Autom. 29(3), 230–248 (2009)

    Article  Google Scholar 

  18. Sanders, D.A., Langner, M., Tewkesbury, G.E.: Improving wheelchair-driving using a sensor system to control wheelchair-veer and variable-switches as an alternative to digital-switches or joysticks. Ind. Robot 37(2), 157–167 (2010)

    Article  Google Scholar 

  19. Sanders, D.A., Baldwin, A.: X-by-wire technology. In: Total Vehicle Technology Conference, pp. 3–12 (2001)

    Google Scholar 

  20. Sanders, D.A.: Controlling the direction of walkie type forklifts and pallet jacks on sloping ground. Assembly Autom. 28(4), 317–324 (2008)

    Article  Google Scholar 

  21. Fiorini, P., Oboe, R.: Internet-based telerobotics: problems and approaches. In: Proceedings of ICAR 1997, Monterey, CA, pp. 765–770 (1997)

    Google Scholar 

  22. Richard, J.P.: Time-delay systems: an overview of some recent advances and open problems. Automatica 39, 1667–1694 (2003)

    Article  MathSciNet  Google Scholar 

  23. Lawrence, D.A.: Stability and transparency in bilateral tele-operation. IEEE Trans. Robot. Autom. 9(5) (1993)

    Article  Google Scholar 

  24. Kim, W., Hannaford, B., Bejczy, A.: Force reflection and shared compliant control in operating telemanipulators with time delay. IEEE Trans. Robot. Autom. 8(2), 176–185 (1992)

    Article  Google Scholar 

  25. Niemeyer, G., Slotine, J.J.: Stable adaptive tele-operation. IEEE J. Ocean. Eng. 16(1), 152–162 (1991)

    Article  Google Scholar 

  26. Niemeyer, G., Slotine, J.J.: Towards force reflecting tele-operation over the Internet. In: Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium (ICRA 1998), pp. 1909–1915 (1998)

    Google Scholar 

  27. Luk, B.L., Cooke, D.S., Galt, S., Collie, A.A., Chen, S.: Intelligent legged climbing service robot for remote maintenance applications in hazardous environments. J. Robot. Autonom. Syst. 53(2), 142–152 (2005)

    Article  Google Scholar 

  28. Rooks, B.: Plotting future UK robotics research Programmes. Ind. Robot 33(3), 165–169 (2006)

    Article  Google Scholar 

  29. Sanders, D.A., Tewkesbury, G.E., Robinson, D.C.: Simple expert systems to improve an ultrasonic sensor-system for a tele-operated mobile-robot. Sens. Rev. 31(3), 246–260 (2011)

    Article  Google Scholar 

  30. Sanders, D.A., Stott, I.J.: Analysis of failure rates with a tele-operated mobile robot between a human tele-operator and a human with a sensor system to assist. Robotica J. 30(6), 973–988 (2012)

    Google Scholar 

  31. Sanders, D., Tewkesbury, G., Graham-Jones, J.: Simple rules to modify pre-planned paths to improve gross robot motions associated with pick and place assembly tasks. Assembly Autom. 31(1), 69–78 (2011)

    Article  Google Scholar 

  32. Sanders, D.A.: Comparing ability to complete simple tele-operated rescue or maintenance mobile-robot tasks with and without a sensor system. Sens. Rev. 30(1), 40–50 (2010)

    Article  Google Scholar 

  33. Sanders, D.A., Graham-Jones, J., Gegov, A.: Improving ability of tele-operators to complete progressively more difficult mobile robot paths using simple expert systems and ultrasonic sensors. Ind. Robot 37(5), 431–440 (2010)

    Article  Google Scholar 

  34. Stott, Sanders, D.: New powered wheelchair systems for the rehabilitation of some severely disabled users. Int. J. Rehab. Res. 23(3), 149–153 (2000)

    Article  Google Scholar 

  35. Sanders, D., Stott, I.: A new prototype intelligent mobility system to assist powered wheelchair users. Ind. Robot 26(6), 466–475 (1999)

    Article  Google Scholar 

  36. Goodwin, M.J., Sanders, D.A., Poland, G.A., et al.: Navigational assistance for disabled wheelchair-users. In: Proceedings of Euromicro Conference 95, vol. 43, pp. 73–79 (1997)

    Article  Google Scholar 

  37. Sanders, D.: Analysis of the effects of time delays on the teleoperation of a mobile robot in various modes of operation. Ind. Robot 36(6), 570–584 (2009)

    Article  Google Scholar 

  38. Sanders, D., Stott, I., Graham-Jones, J., et al.: Expert system to interpret hand tremor and provide joystick position signals for powered wheelchairs with ultrasonic sensor systems. Ind. Robot 38(6), 585–598 (2011)

    Article  Google Scholar 

  39. Sanders, D.A., Bausch, N., Liu, H., et al.: Improving steering of a powered wheelchair using an expert system to interpret hand tremor. In: Proceedings Intelligent Robotics and Applications, Pt I vol. 9245, pp. 460–471 (2015)

    Chapter  Google Scholar 

  40. Sanders, D., Stott, I.: The use of virtual reality to train powered wheelchair users and test new wheelchair systems. Int. J. Rehabil. Res. 23(4), 321–326 (2000)

    Google Scholar 

  41. Sands, D.: Cost effective robotics in the nuclear industry. Ind. Robot 33(3), 170–173 (2006)

    Article  Google Scholar 

  42. Nakamura, T., Satoh, K.: Development of an omni-directional mobile robot using traveling waves based on snail locomotion. Ind. Robot 35(3), 206–210 (2008)

    Article  Google Scholar 

  43. Luk, B.L., Collie, A.A., Cooke, D.S., Chen, S.: Walking and climbing service robots for safety inspection of nuclear reactor pressure vessels. Measure. Control 39(2), 43–47 (2006)

    Article  Google Scholar 

  44. Luk, B., Liu, K., Collie, A., Cooke, D., Chen, S.: Tele-operated climbing and mobile service robots for remote inspection and maintenance in nuclear industry. Ind. Robot 33(3), 194–204 (2006)

    Article  Google Scholar 

  45. Bakari, M.J., Seward, D.W.: Human arm-like mechanical manipulator - the design and development of a multi-arm mobile robot for nuclear decommissioning. In: Proceedings of 3rd International Conference on Informatics in Control, Automation and Robotics – Robotics and Automation, pp. 168–175 (2006)

    Google Scholar 

  46. DeJong, B.P., Faulring, E.L., Edward Colgate, J., Peshkin, M.A., Kang, H., Park, Y.S., Ewing, T.F.: Lessons learned from a novel tele-operation test-bed. Ind. Robot 33(3), 187–193 (2006)

    Article  Google Scholar 

  47. Sanders, D.A., Stott, I.J., Robinson, D.C., et al.: Analysis of successes and failures with a tele-operated mobile robot in various modes of operation. Robotica 30, 973–988 (2012)

    Article  Google Scholar 

  48. Stott, J., Sanders, D.A.: New powered mobile robot systems for the rehabilitation of some severely disabled users. Int. J. Rehab. Res. 23(3), 149–153 (2000)

    Article  Google Scholar 

  49. Sanders, D.A., Graham-Jones, J., Gegov, A.: Improving ability of tele-operators to complete progressively more difficult mobile robot paths using simple expert systems and ultrasonic sensors. Ind. Robot-an Int. J. 37(5), 431–440 (2010)

    Article  Google Scholar 

  50. Sanders, D.A., Stott, I.J.: A new prototype intelligent mobility system to assist powered mobile robot users. Ind. Robot 26(6), 466–475 (1999)

    Article  Google Scholar 

  51. Hayati, S., Venkataraman, S.T.: Design and implementation of a robot control system with traded and shared control capability. In: Proceedings of IEEE International Conf on Robotics and Automation, Scottsdal, AZ, USA, pp. 1310–1315 (1989)

    Google Scholar 

  52. Abbink, D.M.M., Boer, E.R.: Haptic shared control: smoothly shifting control authority? Cogn. Technol. Work 14(1), 19–28 (2012)

    Article  Google Scholar 

  53. Itoh, M., Inagakia, T., Tanaka, H.: Haptic steering direction guidance for pedestrian-vehicle collision avoidance. In: Proceedings of IEEE International Conference on System, Man, and Cybernetics, Seoul, Korea, pp. 3309–3314 (2012)

    Google Scholar 

  54. Carlson, T., Demiris, Y.: Increasing robotic mobile robot safety with collaborative control: evidence from secondary task experiments. In: Proceedings of IEEE International Conf on Robotics and Automation, Anchorage, Alaska, USA, pp. 5582–5587 (2010)

    Google Scholar 

  55. Satti, R., Coyle, D., Prasad, G.: Self-paced brain-controlled mobile robot methodology with shared and automated assistive control. In: Proceedings of IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, Paris, France, pp. 1–8 (2011)

    Google Scholar 

  56. Franchi, A., Secchi, C., Ryll, M., Bulthoff, H.H., Giordano, P.R.: Shared control: balancing autonomy and human assistance with a group of quadrotor UAVs. IEEE Robot. Autom. Mag. 19(3), 57–68 (2012)

    Article  Google Scholar 

  57. Kim, H.K., Biggs, S.J., Schloerb, D.W., Carmena, J.M., Lebedev, M.A., Nicolelis, M.A.L., Srinivasan, M.A.: Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces. IEEE Trans. Biomed. Eng. 53(6), 1164–1173 (2006)

    Article  Google Scholar 

  58. Sanders, D.A., Urwin-Wright, S.D., Tewkesbury, G.E., et al.: Pointer device for thin-film transistor and cathode ray tube computer screens. Electr. Lett. 41(16), 894–896 (2005)

    Article  Google Scholar 

  59. Sanders, D.A., Bergasa-Suso, J.: Inferring learning style from the way students interact with a computer user interface and the WWW. IEEE Trans. Educ. 53(4), 613–620 (2010)

    Article  Google Scholar 

  60. Sanders, D.A., Tewkesbury, G.E.: A pointer device for TFT display screens that determines position by detecting colours on the display using a colour sensor and an Artificial Neural Network. Displays 30(2), 84–96 (2009)

    Article  Google Scholar 

  61. Sanders, D.A., Baldwin, A.: X-by-wire technology. In: Total Vehicle Technology Conference, pp. 3–12 (2001). ISBN: 1-86058-324-5

    Google Scholar 

  62. Carlson, T., Demiris, Y.: Collaborative control for a robotic mobile robot: evaluation of performance, attention, and workload. IEEE Trans. Syst. Man Cybern. Part B Cybern. 42(3), 876–888 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical and Design Engineering, Portsmouth University, Portsmouth, UK

    David A. Sanders & Giles Eric Tewkesbury

  2. School of Computing, Portsmouth University, Portsmouth, UK

    Alexander Gegov

  3. Department of Electronics and Energy, Portsmouth University, Portsmouth, UK

    Rinat Khusainov

Authors
  1. David A. Sanders
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexander Gegov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giles Eric Tewkesbury
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rinat Khusainov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David A. Sanders .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sanders, D.A., Gegov, A., Tewkesbury, G.E., Khusainov, R. (2019). Sharing Driving Between a Vehicle Driver and a Sensor System Using Trust-Factors to Set Control Gains. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_82

Download citation

Publish with us

Policies and ethics

Search

Navigation