NCT04980846

Design and Implementation of a Drunk Driving Detection System

Non-randomised, Controlled, Interventional Single-centre Study for the Design and Evaluation of an In-vehicle Drunk Driving Detection System

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 30 (actual)
• Sponsor: University of Bern · Academic / Other
• Sex: All
• Age: 17 Years
• Healthy volunteers: Accepted

Summary

To analyse driving behavior of individuals under the influence of alcohol using a validated research driving simulator. Based on the driving variables provided by the simulator the investigators aim at establishing algorithms capable of discriminating sober and drunk driving patterns using machine learning neural networks (deep machine learning classifiers).

Detailed description

Driving under the influence of alcohol (or "drunk driving") is one of the most significant causes of traffic accidents. Alcohol consumption impairs neurocognitive and psychomotor function and has been shown to be associated with an increased risk of driving accidents. Automotive technology is highly dynamic, and fully autonomous driving might, in the end, resolve the issue of alcohol impaired accidents. However, autonomous driving (level 4 or 5) is likely to be broadly available only to a substantially later time point than previously thought due to increasing concerns of safety associated with this technology. Therefore, solutions bridging the upcoming period by more rapidly and directly addressing the problem of drunk driving-associated traffic incidents are urgently needed. On the supposition that driving behaviour differs significantly between sober and drunk states, the investigators assume that different driving patterns in both states can be used to generate drunk driving detection models using machine learning neural networks (deep machine learning classifiers).

Conditions

• Transportation Accidents
• Drunk Driving
• Alcohol Drinking
• Impaired Driving

Interventions

Type	Name	Description
OTHER	Driving under the influence of alcohol with a driving simulator	Participants will drive in three different states (sober, drunk above and below the legal limit) on designated circuits using a driving simulator. After the initial sober driving session, participants are administered pre-mixed alcoholic beverages (e.g., vodka orange). Participants are expected to achieve a target BrAC of 0.35 mg/l (legal limit in Switzerland is 0.25 mg/l BrAC) before the second driving session starts. Finally, the third driving session starts when the participants' BrAC drops to 0.15 mg/l. Heart rate, skin conductance, accelerometer, eye movement, radar, facial expression, and speech will be recorded by a smart-watch, an eye-tracker, microphones and an onboard camera, respectively. Participants will be blinded to their alcohol levels during the study. They will have to rate their symptoms and their performance via questionnaires before and after each driving session. Further, capillary blood and oral fluid samples will be collected.

Timeline

• Start date: 2021-08-15
• Primary completion: 2021-11-14
• Completion: 2021-11-14
• First posted: 2021-07-28
• Last updated: 2022-01-03

Locations

1 site across 1 country: Switzerland