Intuitive Maneuver of Autonomous Vehicles without Physical Control Interfaces using Wearable Sensing Devices

Weitian Wang, Rui Li, Z. Max Diekel, Yunyi Jia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Autonomous vehicles are more and more likely to eliminate steering wheels, gas/brake pedals and driving shifts. However, direct controls of such vehicle by human drivers are still necessary, especially when the vehicles fail to drive as well as expected. To this end, we propose an intuitive maneuvering approach for autonomous vehicles by using a wearable device which incorporates Electromyography (EMG) and inertial measurement unit (IMU) signals. Based on goal instructions and motion planning algorithms in this approach, humans can intuitively control the accelerator/brake, steering and driving shift of a vehicle using their hand motions and gestures. This approach was implemented by a series of driving experiments in practical cases on a lab-based research vehicle. Experimental results demonstrated that by taking advantages of intuitive operations in this approach, the human can successfully and effectively control the vehicle to accomplish driving tasks in the human-vehicle intuitive maneuver system.

Original languageEnglish
Title of host publication2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1451-1456
Number of pages6
ISBN (Print)9781538604892
DOIs
StatePublished - 24 Aug 2018
Event7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017 - Honolulu, United States
Duration: 31 Jul 20174 Aug 2017

Publication series

Name2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017

Conference

Conference7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
CountryUnited States
CityHonolulu
Period31/07/174/08/17

Keywords

  • EMG information
  • gesture
  • human-vehicle collaboration
  • intuitive maneuver
  • motions planning

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