Leveraging Acoustic Signals for Vehicle Steering Tracking with Smartphones

Xiangyu Xu, Jiadi Yu, Yingying Chen, Yanmin Zhu, Minglu Li

Research output: Contribution to journalArticle

Abstract

Given the increasing popularity, mobile devices are exploited to enhance active driving safety nowadays. Among all safety services provided for vehicles, tracking the rotation angle of steering wheel in real time can monitor the vehicles' dynamics and drivers' behaviors at the same time. In this paper, we propose a steering tracking system, SteerTrack, which tracks the rotation angle of steering wheel in real time leveraging audio devices on smartphones. SteerTrack seeks a device-free approach for steering tracking without requiring installation of specialized sensors on steering wheels nor asking drivers to wear sensors on their wrists. Since the steering wheel is operated by a driver's hands, the rotation angle of steering wheel can be tracked based on movements of the driver's hands. SteerTrack first builds an acoustic signal field inside of a vehicle and then analyzes the echoes reflected from the driver's hands with relative correlation coefficient (RCC) and reference frame to track the movement trajectory of hands under different steering maneuvers. Given the tracked movement trajectory, SteerTrack further develops a geometrical transformation-based method for estimating the rotation angle of steering wheel in 3D driving environments by projecting the steering wheel to a 2D ellipse. Through extensive experiments in real driving environments with 5 volunteers for several weeks, SteerTrack can achieve an average steering wheel estimation error of 1.48 degree during driving, and 4.61 degree for turns.

Original languageEnglish (US)
JournalIEEE Transactions on Mobile Computing
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Smartphones
Acoustics
Wheels
Trajectories
Sensors
Mobile devices
Error analysis
Wear of materials

All Science Journal Classification (ASJC) codes

  • Software
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

Keywords

  • Acoustics
  • Radar tracking
  • Smart phones
  • Tracking
  • Trajectory
  • Vehicles
  • Wheels
  • acoustic signal sensing
  • smartphone sensors
  • steering tracking

Cite this

@article{bd1af538d38f493db81b3d7480ba49b1,
title = "Leveraging Acoustic Signals for Vehicle Steering Tracking with Smartphones",
abstract = "Given the increasing popularity, mobile devices are exploited to enhance active driving safety nowadays. Among all safety services provided for vehicles, tracking the rotation angle of steering wheel in real time can monitor the vehicles' dynamics and drivers' behaviors at the same time. In this paper, we propose a steering tracking system, SteerTrack, which tracks the rotation angle of steering wheel in real time leveraging audio devices on smartphones. SteerTrack seeks a device-free approach for steering tracking without requiring installation of specialized sensors on steering wheels nor asking drivers to wear sensors on their wrists. Since the steering wheel is operated by a driver's hands, the rotation angle of steering wheel can be tracked based on movements of the driver's hands. SteerTrack first builds an acoustic signal field inside of a vehicle and then analyzes the echoes reflected from the driver's hands with relative correlation coefficient (RCC) and reference frame to track the movement trajectory of hands under different steering maneuvers. Given the tracked movement trajectory, SteerTrack further develops a geometrical transformation-based method for estimating the rotation angle of steering wheel in 3D driving environments by projecting the steering wheel to a 2D ellipse. Through extensive experiments in real driving environments with 5 volunteers for several weeks, SteerTrack can achieve an average steering wheel estimation error of 1.48 degree during driving, and 4.61 degree for turns.",
keywords = "Acoustics, Radar tracking, Smart phones, Tracking, Trajectory, Vehicles, Wheels, acoustic signal sensing, smartphone sensors, steering tracking",
author = "Xiangyu Xu and Jiadi Yu and Yingying Chen and Yanmin Zhu and Minglu Li",
year = "2019",
month = "1",
day = "1",
doi = "https://doi.org/10.1109/TMC.2019.2900011",
language = "English (US)",
journal = "IEEE Transactions on Mobile Computing",
issn = "1536-1233",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Leveraging Acoustic Signals for Vehicle Steering Tracking with Smartphones. / Xu, Xiangyu; Yu, Jiadi; Chen, Yingying; Zhu, Yanmin; Li, Minglu.

In: IEEE Transactions on Mobile Computing, 01.01.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Leveraging Acoustic Signals for Vehicle Steering Tracking with Smartphones

AU - Xu, Xiangyu

AU - Yu, Jiadi

AU - Chen, Yingying

AU - Zhu, Yanmin

AU - Li, Minglu

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Given the increasing popularity, mobile devices are exploited to enhance active driving safety nowadays. Among all safety services provided for vehicles, tracking the rotation angle of steering wheel in real time can monitor the vehicles' dynamics and drivers' behaviors at the same time. In this paper, we propose a steering tracking system, SteerTrack, which tracks the rotation angle of steering wheel in real time leveraging audio devices on smartphones. SteerTrack seeks a device-free approach for steering tracking without requiring installation of specialized sensors on steering wheels nor asking drivers to wear sensors on their wrists. Since the steering wheel is operated by a driver's hands, the rotation angle of steering wheel can be tracked based on movements of the driver's hands. SteerTrack first builds an acoustic signal field inside of a vehicle and then analyzes the echoes reflected from the driver's hands with relative correlation coefficient (RCC) and reference frame to track the movement trajectory of hands under different steering maneuvers. Given the tracked movement trajectory, SteerTrack further develops a geometrical transformation-based method for estimating the rotation angle of steering wheel in 3D driving environments by projecting the steering wheel to a 2D ellipse. Through extensive experiments in real driving environments with 5 volunteers for several weeks, SteerTrack can achieve an average steering wheel estimation error of 1.48 degree during driving, and 4.61 degree for turns.

AB - Given the increasing popularity, mobile devices are exploited to enhance active driving safety nowadays. Among all safety services provided for vehicles, tracking the rotation angle of steering wheel in real time can monitor the vehicles' dynamics and drivers' behaviors at the same time. In this paper, we propose a steering tracking system, SteerTrack, which tracks the rotation angle of steering wheel in real time leveraging audio devices on smartphones. SteerTrack seeks a device-free approach for steering tracking without requiring installation of specialized sensors on steering wheels nor asking drivers to wear sensors on their wrists. Since the steering wheel is operated by a driver's hands, the rotation angle of steering wheel can be tracked based on movements of the driver's hands. SteerTrack first builds an acoustic signal field inside of a vehicle and then analyzes the echoes reflected from the driver's hands with relative correlation coefficient (RCC) and reference frame to track the movement trajectory of hands under different steering maneuvers. Given the tracked movement trajectory, SteerTrack further develops a geometrical transformation-based method for estimating the rotation angle of steering wheel in 3D driving environments by projecting the steering wheel to a 2D ellipse. Through extensive experiments in real driving environments with 5 volunteers for several weeks, SteerTrack can achieve an average steering wheel estimation error of 1.48 degree during driving, and 4.61 degree for turns.

KW - Acoustics

KW - Radar tracking

KW - Smart phones

KW - Tracking

KW - Trajectory

KW - Vehicles

KW - Wheels

KW - acoustic signal sensing

KW - smartphone sensors

KW - steering tracking

UR - http://www.scopus.com/inward/record.url?scp=85061969467&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061969467&partnerID=8YFLogxK

U2 - https://doi.org/10.1109/TMC.2019.2900011

DO - https://doi.org/10.1109/TMC.2019.2900011

M3 - Article

JO - IEEE Transactions on Mobile Computing

JF - IEEE Transactions on Mobile Computing

SN - 1536-1233

ER -