Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors

The access to the information on the vehicle motion state is of great significance for the vehicle stability control and the development of active safety products. However, the vehicle state parameter extraction is primarily accessed by attaching special sensors to the vehicles, which usually requir...

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Main Authors: Jie MA, Chaozhong WU, Shuiqing YAN
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2013-12-01
Series:Sensors & Transducers
Subjects:
GPS
Online Access:http://www.sensorsportal.com/HTML/DIGEST/december_2013/PDF_vol_160/P_1587.pdf
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spelling doaj-c69f6e931c654bf995f0390adcd26b5b2020-11-24T21:48:19ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792013-12-0116012111117Vehicle Dynamic State Estimation Using Smartphone Embedded SensorsJie MA0Chaozhong WU1Shuiqing YAN2ITS Research Center, Wuhan University of Technology & Engineering Research Center for Transportation Safety, Ministry of Education, Heping Avenue #1040, Wuhan, 430063, China ITS Research Center, Wuhan University of Technology & Engineering Research Center for Transportation Safety, Ministry of Education, Heping Avenue #1040, Wuhan, 430063, China ITS Research Center, Wuhan University of Technology & Engineering Research Center for Transportation Safety, Ministry of Education, Heping Avenue #1040, Wuhan, 430063, China The access to the information on the vehicle motion state is of great significance for the vehicle stability control and the development of active safety products. However, the vehicle state parameter extraction is primarily accessed by attaching special sensors to the vehicles, which usually requires modification of redesign of the vehicle with high cost. Smartphone integrate gyro, orientation sensor, GPS and some other sensors thus providing a new way for vehicle dynamic parameter estimation. Therefore, we choose smartphone as our working platform, and data acquisition is fulfilled on a variety of mobile sensors embedded in an Android platform phone. Combining the features of these sensors and the properties of vehicle kinematics, a Kalman filter based sensor fusion approach is proposed to perform the vehicle state estimation. The parameters of vehicle heading angle and sideslip angle are extracted using fusion of data from the gyro, GPS and orientation sensor. Experiments carried on real vehicle show that the estimation results generated by fusing the gyro and orientation sensor are better than that of the gyro and GPS, but the two fusion approaches can complement each other in different contexts used. The main contribution of our work is that we provide a new attempt for accessing the vehicle dynamic parameters using off-the-shelf sensors. http://www.sensorsportal.com/HTML/DIGEST/december_2013/PDF_vol_160/P_1587.pdfVehicle dynamic state estimationSmartphoneKalman filterGyroGPSOrientation sensor.
collection DOAJ
language English
format Article
sources DOAJ
author Jie MA
Chaozhong WU
Shuiqing YAN
spellingShingle Jie MA
Chaozhong WU
Shuiqing YAN
Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
Sensors & Transducers
Vehicle dynamic state estimation
Smartphone
Kalman filter
Gyro
GPS
Orientation sensor.
author_facet Jie MA
Chaozhong WU
Shuiqing YAN
author_sort Jie MA
title Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
title_short Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
title_full Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
title_fullStr Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
title_full_unstemmed Vehicle Dynamic State Estimation Using Smartphone Embedded Sensors
title_sort vehicle dynamic state estimation using smartphone embedded sensors
publisher IFSA Publishing, S.L.
series Sensors & Transducers
issn 2306-8515
1726-5479
publishDate 2013-12-01
description The access to the information on the vehicle motion state is of great significance for the vehicle stability control and the development of active safety products. However, the vehicle state parameter extraction is primarily accessed by attaching special sensors to the vehicles, which usually requires modification of redesign of the vehicle with high cost. Smartphone integrate gyro, orientation sensor, GPS and some other sensors thus providing a new way for vehicle dynamic parameter estimation. Therefore, we choose smartphone as our working platform, and data acquisition is fulfilled on a variety of mobile sensors embedded in an Android platform phone. Combining the features of these sensors and the properties of vehicle kinematics, a Kalman filter based sensor fusion approach is proposed to perform the vehicle state estimation. The parameters of vehicle heading angle and sideslip angle are extracted using fusion of data from the gyro, GPS and orientation sensor. Experiments carried on real vehicle show that the estimation results generated by fusing the gyro and orientation sensor are better than that of the gyro and GPS, but the two fusion approaches can complement each other in different contexts used. The main contribution of our work is that we provide a new attempt for accessing the vehicle dynamic parameters using off-the-shelf sensors.
topic Vehicle dynamic state estimation
Smartphone
Kalman filter
Gyro
GPS
Orientation sensor.
url http://www.sensorsportal.com/HTML/DIGEST/december_2013/PDF_vol_160/P_1587.pdf
work_keys_str_mv AT jiema vehicledynamicstateestimationusingsmartphoneembeddedsensors
AT chaozhongwu vehicledynamicstateestimationusingsmartphoneembeddedsensors
AT shuiqingyan vehicledynamicstateestimationusingsmartphoneembeddedsensors
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