Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles
Author:
Seva Rosemary1, del Rosario Imanuel Luir1, Peñafiel Lorenzo Miguel1, Young John Michael1, Sybingco Edwin2ORCID
Affiliation:
1. Department of Industrial and Systems Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, Philippines 2. Department of Electronics and Computer Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, Philippines
Abstract
The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road.
Funder
De La Salle University through its University Research and Coordination Office De La Salle University and the Engineering Research and Development for Technology
Subject
Public Health, Environmental and Occupational Health,Safety Research,Safety, Risk, Reliability and Quality
Reference32 articles.
1. Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data;Yang;J. Saf. Res.,2021 2. Lin, H.A., Chan, C.W., Wiratama, B.S., Chen, P.L., Wang, M.H., Chao, C.J., Saleh, W., Huang, H.C., and Pai, C.W. (2022). Evaluating the effect of drunk driving on fatal injuries among vulnerable road users in Taiwan: A population-based study. BMC Public Health, 22. 3. Should we throw the book at ‘em? Charge combinations and conviction rates among alcohol-influenced drivers involved in motorcycle crashes;Hamann;J. Saf. Res.,2022 4. Lin, H.Y., Li, J.S., Pai, C.W., Chien, W.C., Huang, W.C., Hsu, C.W., Wu, C.C., Yu, S.H., Chiu, W.T., and Lam, C. (2022). Environmental Factors Associated with Severe Motorcycle Crash Injury in University Neighborhoods: A Multicenter Study in Taiwan. Int. J. Environ. Res. Public Health, 19. 5. Lam, C., Wiratama, B.S., Chang, W.-H., Chen, P.-L., Chiu, W.-T., Saleh, W., and Pai, C.-W. (2020). Effect of motorcycle helmet types on head injuries: Evidence from eight level-I trauma centres in Taiwan. BMC Public Health, 20.
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