Design and Evaluation of an In-Vehicle Real-Time Drunk Driving Detection System

Summary

To analyze driving behavior of individuals under the influence of alcohol while driving in a real car. Based on the in-vehicle variables, the investigators aim at establishing algorithms capable of discriminating sober and drunk driving using machine learning.

Conditions

• Drunk Driving
• Alcohol Drinking
• Impaired Driving

Interventions

OTHER

Driving under the influence of alcohol

Participants will drive in three different states (sober, drunk above and below the legal limit) on a designated circuit with a real car on a test track accompanied by a driving instructor. After the initial sober driving session, participants are administered pre-mixed alcoholic beverages (e.g., vodka orange). Participants are expected to achieve a target breath alcohol concentration of 0.35 mg/l (legal limit in Switzerland is 0.25 mg/l breath alcohol concentration) before the second driving session starts. Finally, the third driving session starts when the participants' breath alcohol concentration drops to 0.15 mg/l. Participants will be blinded to their alcohol levels during the study. Measurements: Heart rate, respiration rate, blood oxygen saturation, skin conductance, skin temperature, accelerometer, eye movement, radar, facial expression, audio recording, vehicle data, in-cabin gas concentration

OTHER

Driving under the influence of a placebo

Participants will drive three times at the same intervals as the treatment group on a designated circuit with a real car on a test track accompanied by a driving instructor. After the initial driving session, participants receive placebo beverages (e.g., orange juice with vodka flavor). Participants are fully blinded. Measurements: Heart rate, respiration rate, blood oxygen saturation, skin conductance, skin temperature, accelerometer, eye movement, radar, facial expression, audio recording, vehicle data, in-cabin gas concentration

Sponsors & Collaborators

• ETH Zurich

  collaborator OTHER

• University of St.Gallen

  collaborator OTHER

• University of Bern

  lead OTHER

Principal Investigators

• Wolfgang Weinmann, Prof. Dr. · University of Bern

Study Design

Allocation

RANDOMIZED

Purpose

OTHER

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

21 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2023-04-05

Primary Completion

2023-08-01

Completion

2023-08-01

Countries

• Switzerland

Study Locations