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Testing, Analysis and Performance Validation

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An Integrated Solution Based Irregular Driving Detection

Part of the book series: Springer Theses ((Springer Theses))

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Abstract

In this chapter, the defined reference data for weaving, swerving, jerky driving and normal driving, both in straight and curved lanes scenarios are created in the simulation, and the O-indicator and D-indicator from the reference are calculated as the input of the FIS system to calculate the reference risk type indicator values and driving classification indicator values. The sorting rules for the driving classification indicators from the reference are extracted to arrive at the driving style judgement. The simulated GPS and INS data are then generated with the designed filter and motion model combination to calculate the precise positioning and dynamic parameter results used for the different types of driving style identification. By comparing the sorting rules of the driving classification indicator calculated from the filter estimated results and reference results, the different types of driving styles based on the filter estimated results can be detected. Finally, real field data based tests are carried out to validate the simulation results. Because of logistical and safety concerns in respect to undertaking field tests, the approach taken in this chapter is to address simulation in detail with limited but targeted field tests for the overall validation of the simulation results.

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Correspondence to Rui Sun .

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© 2017 Springer International Publishing AG

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Sun, R. (2017). Testing, Analysis and Performance Validation. In: An Integrated Solution Based Irregular Driving Detection. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-44926-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-44926-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44925-8

  • Online ISBN: 978-3-319-44926-5

  • eBook Packages: EngineeringEngineering (R0)

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