Personalized Driving Behavior Monitoring and Analysis for Emerging Hybrid Vehicles

  • Kun Li
  • Man Lu
  • Fenglong Lu
  • Qin Lv
  • Li Shang
  • Dragan Maksimovic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7319)

Abstract

Emerging electric-drive vehicles, such as hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs), hold the potential for substantial reduction of fuel consumption and greenhouse gas emissions. User driving behavior, which varies from person to person, can significantly affect (P)HEV operation and the corresponding energy and environmental impacts. Although some studies exist that investigate vehicle performance under different driving behaviors, either directed by vehicle manufacturers or via on-board diagnostic (OBD) devices, they are typically vehicle-specific and require extra device/effort. Moreover, there is no or very limited feedback to an individual driver regarding how his/her personalized driving behavior affects (P)HEV performance.

This paper presents a personalized driving behavior monitoring and analysis system for emerging hybrid vehicles. Our design is fully automated and non-intrusive. We propose phone-based multi-modality sensing that captures precise driver–vehicle information through de-noise, calibration, synchronization, and disorientation compensation. We also provide quantitative driver-specific (P)HEV analysis through operation mode classification, energy use and fuel use modeling. The proposed system has been deployed and evaluated with real-world user studies. System evaluation demonstrates highly-accurate (0.88-0.996 correlation and low error) driving behavior sensing, mode classification, energy use and fuel use modeling.

Keywords

Internal Combustion Engine User Study Hybrid Electric Vehicle Internal Combustion Engine Hybrid Vehicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
  2. 2.
  3. 3.
    Development of speed correction cycles. Tech. rep., US EPA Assessment and Modeling Division, NVFEL (1997), EPA report no. M6.5PD.001 (1997)Google Scholar
  4. 4.
    Adornato, B., Patil, R., Filipi, Z., Baraket, Z., Gordon, T.: Characterizing naturalistic driving patterns for plug-in hybrid electric vehicle analysis. In: IEEE VPPC (2009)Google Scholar
  5. 5.
    Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. CRC Press (1984)Google Scholar
  6. 6.
    Davison, A.C., Hinkley, D.: Bootstrap Methods and their Application, Cambridge (2006)Google Scholar
  7. 7.
    Ehsani, M., Gao, Y., Emadi, A.: Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design. CRC Press (2009)Google Scholar
  8. 8.
    Ganji, B., Kouzani, A.Z., Trinh, H.M.: Drive Cycle Analysis of the Performance of Hybrid Electric Vehicles. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds.) LSMS 2010 and ICSEE 2010, Part I . LNCS, vol. 6328, pp. 434–444. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Ganti, R.K., Pham, N., Ahmadi, H., Nangia, S., Abdelzaher, T.F.: GreenGPS: a participatory sensing fuel-efficient maps application. In: MobiSys 2010 (2010)Google Scholar
  10. 10.
    Huang, X., Tan, Y., He, X.: An intelligent multi-feature statistical approach for discrimination of driving conditions of hybrid electric vehicle. In: IJCNN 2009 (2009)Google Scholar
  11. 11.
    Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, A., Shih, E., Balakrishnan, H., Madden, S.: CarTel: a distributed mobile sensor computing system. In: SenSys 2006, pp. 125–138 (2006)Google Scholar
  12. 12.
    Harte, J.: Consider a Spherical Cow. University Science Books (1988)Google Scholar
  13. 13.
    Jonasson, K.: Analysing hybrid drive system topologies. Licentiate thesis (2002)Google Scholar
  14. 14.
    Krumm, J.: Realistic Driving Trips For Location Privacy. In: Tokuda, H., Beigl, M., Friday, A., Brush, A.J.B., Tobe, Y. (eds.) Pervasive 2009. LNCS, vol. 5538, pp. 25–41. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  15. 15.
    Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.: A survey of mobile phone sensing. IEEE Communications Magazine 48(9), 140–150 (2010)CrossRefGoogle Scholar
  16. 16.
    Li, K., Wu, J., Jiang, Y., Hassan, Z., Lv, Q., Shang, L., Maksimovic, D.: Large-scale battery system modeling and analysis for emerging electric-drive vehicles. In: ISLPED 2010, pp. 277–282 (2010)Google Scholar
  17. 17.
    Lin, J., Niemeier, D.A.: Regional driving characteristics, regional driving cycles. Transportation Research Part D 8, 361–381 (2003)CrossRefGoogle Scholar
  18. 18.
    Lu, H., Yang, J., Liu, Z., Lane, N.D., Choudhury, T., Campbell, A.T.: The jigsaw continuous sensing engine for mobile phone applications. In: SenSys 2010 (2010)Google Scholar
  19. 19.
    Miluzzo, E., Papandrea, M., Lane, N., Lu, H., Campbell, A.T.: Pocket, bag, hand, etc. - automatically detecting phone context through discovery. In: PhoneSense 2010 (2010)Google Scholar
  20. 20.
    Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In: SenSys 2008, pp. 323–336 (2008)Google Scholar
  21. 21.
    Mohd-Yasin, F., Nagel, D.J., Ong, D.S., Korman, C.E., Chuah, H.T.: Low frequency noise measurement and analysis of capacitive micro-accelerometers: Temperature effect. Japanese Journal of Applied Physics 47(6), 5270–5273 (2008)CrossRefGoogle Scholar
  22. 22.
    Samaras, C., Meisterling, K.: Life cycle assessment of greenhouse gas emissions from plug-in hybrid vehicles: Implications for policy. Environ. Sci. Technol. 42 (2008)Google Scholar
  23. 23.
    Sardy, S., Tseng, P., Bruce, A.: Robust wavelet denoising. IEEE Transactions on Signal Processing 49(6), 1146–1152 (2001)CrossRefGoogle Scholar
  24. 24.
    Thiagarajan, A., Ravindranath, L., LaCurts, K., Madden, S., Balakrishnan, H., Toledo, S., Eriksson, J.: VTrack: accurate, energy-aware road traffic delay estimation using mobile phones. In: SenSys 2009, pp. 85–98 (2009)Google Scholar
  25. 25.
    Tong, H.Y., Hung, W.T., Chun-shun, C.: On-road motor vehicle emissions and fuel consumption in urban driving conditions. Joural of the Air and Waste Management Association 50, 543–554 (2000)CrossRefGoogle Scholar
  26. 26.
    Torrence, C., Compo, G.P.: A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79, 61–78 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kun Li
    • 1
  • Man Lu
    • 1
  • Fenglong Lu
    • 1
  • Qin Lv
    • 2
  • Li Shang
    • 1
  • Dragan Maksimovic
    • 1
  1. 1.Department of Electrical, Computer, and Energy EngineeringUniversity of ColoradoBoulderUSA
  2. 2.Department of Computer ScienceUniversity of ColoradoBoulderUSA

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