Remote driving testbed with force feedback based on slip angle estimation

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


While automotive research plays a significant role nowadays, most of the experimental activity demands costly platforms and involves safety issues. Plenty of driving simulators were proposed to reduce the costs and guarantee safety. However, they still cannot reflect the physical world, resulting in subjective assessments in any aspect of the study. This paper introduces an affordable remote driving testbed based on small-scale car-like mobile platforms and a physical road. The driver in the remote driving station observes a real-time video taken from a front-facing camera installed in the car. For a realistic driving experience, we have developed a torque feedback mechanism based on the small-scale car motion to mimic the influence of the physical linkage between the front wheels and the steering wheel of a standard car. This mechanism demands knowledge of the car's side-slip angle that is not directly measured. Here, we introduce a supervised learning-based combined regression model (RidgeCV and Bootstrap aggregating decision tree) that estimates the side-slip angle for highly non-linear behavior.

Original languageEnglish
Title of host publication10th European Conference on Mobile Robots, ECMR 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781665412131
StatePublished - 1 Aug 2021
Event10th European Conference on Mobile Robots, ECMR 2021 - Virtual, Bonn, Germany
Duration: 31 Aug 20213 Sep 2021


Conference10th European Conference on Mobile Robots, ECMR 2021
CityVirtual, Bonn


  • Bagging decision tree (Bootstrap aggregating)
  • Remote driving testbed
  • Ridge cross validation
  • Side-slip angle
  • Torque feedback
  • regression

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Optimization
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Mechanical Engineering


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