Abstract
In recent times, number of researchers have investigated vehicle tracking applications by fusing the measurements done by accelerometers (as part of Inertial Navigation System-INS) and Global Positioning System (GPS). Since smartphones contain both the set of sensors, there exists a high degree of interest in utilizing personal phones for such tracking applications. However, mobile phone sensors have limitations in measurement accuracy and reliability. Usually, sudden changes in vehicle speed are not always captured well by GPS. Accelerometers, on the other hand, suffer from multiple noise sources. In this chapter, we investigate the noise performance of a few smartphone based accelerometers. Then, we apply the said noise analysis for improving the estimation of the speed of moving vehicle, as captured by GPS. A number of experiments were carried out to capture the vehicle’s position and speed from OBD2 (On Board Diagnosis V2), GPS as well as 3-axes accelerometer. We also demonstrate a method by which the phone’s orientation is compensated for while calculating speed from the measured acceleration. Further, a new method of INS/GPS fusion is proposed which enhances the accuracy of speed estimation. It is envisaged that with increasing estimation accuracy, the application of multi-sensor fusion in autonomous vehicles will be greatly enhanced.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
M.S. Grewal, L.R. Weill, A.P. Andrews, Global positioning Systems, Inertial Navigation, and Integration (Wiley, New Jersey, 2007)
V. Gupta, Vehicle localization using low-accuracy GPS, IMU and map aided vision, Doctoral Thesis, The Pennsylvania State University (2009)
R.D. Martini, GPS/INS sensing coordination for vehicle state identification and road grade positioning, Doctoral thesis. The Pennsylvania State University (2006)
T. Chakravarty, A. Ghose, C. Bhaumik, A. Chowdhury, MobiDriveScore-a system for mobile sensor based driving analyis: A risk assessment model for improving one’s driving, in 7th International Conference on Sensing Technology (ICST), pp. 338–344 (2013)
T. Toledo, O. Musicant, T. Lotan, In-vehicle data recorders for monitoring and feedback on drivers behavior. Trans. Res. Part C: Emerg Technol 16(3), 320–331 (2008)
A. Ghose, P. Biswas, C. Bhaumik, M. Sharma, A. Pal, A. Jha, Road condition monitoring and alert application: using in-vehicle smartphone as internet-connected sensor, in 2012 IEEE International Conference Proceedings of Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 489–491 (2012)
J.H. Hong, B. Margines, A.K. Dey, A smartphone-based sensing platform to model aggressive driving behaviors, in ACM Conference on Human-Computer Interaction (CHI) (Toronto, Canada, 2014)
R. Vaiana, T. Iuele, V. Astarita, M.V. Caruso1, A. Tassitani, C. Zaffino, V.P. Giofrè, Driving behavior and traffic safety: An acceleration-based safety evaluation procedure for smartphones. Mod. Appl. Sci. 8(1), 88–96 (2014)
O.J. Woodman, An introduction to inertial navigation, University of Cambridge, Computer Laboratory, Technical Report UCAMCL-TR-696, 14, 15, 2007, http://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-696.pdf
X. Zhang, Y. Li, P. Mumford, C. Rizos, Allan variance analysis on error characters of MEMS inertial sensors for an FPGA-based GPS/INS System, in Proceedings of the International Symposium on GPS/GNNS (2008)
F. Gustafsson, F. Gunnarsson, N. Bergman, U. Forssell, J. Jansson, R. Karlsson, P.J. Nordlund, Particle filters for positioning, navigation, and tracking. Signal Process. IEEE Trans. 50(2), 425–437 (2002)
M. Roth, F. Gustafsson, U. Orguner, On-road trajectory generation from GPS data: a particle filtering/smoothing application, in IEEE 2012 15th International Conference Information Fusion (FUSION), (2012), pp. 779–786
M.S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. Signal Process. IEEE Trans. 50(2), 174–188 (2002)
Timble Navigation Ltd., Differentiating between recreational and professional grade GPS receivers, (Whitepaper), www.timble.com (2006), http://www.clintoncountyohgis.org/Metadata/Difference%20between%20recreational%20and%20professional%20grade%20gps%20recievers.pdf
A. Chowdhury, T. Chakravarty, P. Balamuralidhar, Estimating true speed of moving vehicle using smartphone-based GPS measurement, in IEEE International Conference on Systems, Man and Cybernetics (SMC) (IEEE, 2014), pp. 3348–3353
Z. Hui, C. Wei, Z. Huan-Tao, L. Qiang, Research on calibration method for the installation error of three-axis acceleration sensor. Int J Mech. Mechatron. Eng. IJMME-IJENS 11(04), 6–11 (2011)
B.T. Sutcliffe, Coordinate systems and transformations, in Handbook of Molecular Physics and Quantum Chemistry, vol. 1 (2003)
H. Hou, Modeling Inertial Sensors Errors Using Allan Variance (Department of Geomatics Engineering, University of Calgary, 2004)
S. Colton, F.R.C. Mentor, The balance filter, Presentation (Massachusetts Institute of Technology, 2007), http://burt.googlecode.com/svn-history/r121/trunk/Hardware/Sensors/filter.pdf
A. Chowdhury, T. Chakravarty, P. Balamuralidhar, A novel approach to improve vehicle speed estimation using smartphone’s INS/GPS sensors, in International Conference on Sensing Technology (ICST) (Liverpool, UK, 2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Chowdhury, A., Ghose, A., Chakravarty, T., Balamuralidhar, P. (2016). An Improved Fusion Algorithm For Estimating Speed From Smartphone’s Ins/Gps Sensors. In: Mukhopadhyay, S. (eds) Next Generation Sensors and Systems. Smart Sensors, Measurement and Instrumentation, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-21671-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-21671-3_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21670-6
Online ISBN: 978-3-319-21671-3
eBook Packages: EngineeringEngineering (R0)