Naturalistic Driving Study: Alcohol Sensor Performance (2015) / Chapter Skim
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11 Findings and Applications Algorithm Considerations and Development Previous research efforts for the alcohol sensor and an examination of trips known to have imbibed and unimbibed alcohol presence created the framework for the development of an alcohol-detection algorithm using alcohol sensor data. These considerations and examples are detailed below along with a description of their translation into the final nonproprietary algorithm used in this research.
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12 vehicle. The readings appeared to indicate a stronger sensor response with a decrease in readings when the individual who consumed alcohol was in the driver or passenger seat rather than in the back seat.
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13 Figure 3.2. Effect of various types of unimbibed alcohol on alcohol sensor.
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14 in the presence of the Boozooka with the controlled trips with intoxicated individuals. As shown in Figure 3.4, values for the first alcohol sensor (top)
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15 Bo o zo o ka O ff Bo o zo o ka O n M illi vo lts (m V) Milliseconds (ms)
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16 shows that alcohol sensor readings dropped for both sensors as BrAC increased. However, although the absolute value of the alcohol sensor readings for AS1 and AS2 were similar under no alcohol presence, AS1 had a steeper decrease in sensor readings with increased BrAC.
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17 done by categorizing trips coded as "imbibed alcohol only" and "both imbibed and unimbibed alcohol present" in an "alcohol present" classification. Similarly, trips that were coded as "unimbibed alcohol only" or "neither imbibed nor unimbibed alcohol present" were categorized as "no alcohol present." The results of the confusion matrix are depicted in Figure 3.9.
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18 The confusion matrix for the impaired data set is shown in Figure 3.10. The sensitivity of the algorithm against this data set was 92% and the specificity was 100%.
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