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Completed

NCT Number: NCT07401628

In-Vehicle Real-Time Cannabis Influenced Driving Detection

The goal of this clinical trial is to evaluate whether in-vehicle sensor data can be used to detect cannabis-impaired driving in healthy adult recreational cannabis users.

The study aims to assess whether changes in vehicle, driver, and physiological sensor data can distinguish sober driving from cannabis-impaired driving, and how driving performance changes from baseline to approximately 1 to 6 hours after controlled cannabis consumption.

Researchers will compare driving behavior and in-vehicle sensor data from participants who receive controlled cannabis administration with data from a randomized reference group without cannabis exposure, to determine whether cannabis-related impairment driving can be identified on the basis of machine learning.

Participants will complete screening and baseline assessments and drive an instrumented vehicle on a closed test track under sober conditions. Participants assigned to the experimental arm will receive controlled cannabis administration, while participants in the reference arm will receive no intervention. All participants will perform repeated standardized driving sessions over several hours and complete traffic-medical, traffic-psychological, and in-vehicle pre-driving tests. Biological samples and in-vehicle sensor data will be collected throughout the study.

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Key information

Conditions

Driving Under the Influence Behavior Cannabis-impaired Driving Criminal Behavior Dangerous Behavior

Age range

21 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Institute for Forensic Medicine, Forensic Chemistry and Toxicology University of Bern

Bern, 3008, Switzerland

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Informed consent as documented by signature
  • Recreational cannabis-consumption (more than once per month)
  • In possession of a definite Swiss or European Union (EU) driving license
  • At least 21 years old
  • Active, regular driving a car in the last 6 months
  • Must be in good health condition
  • No special equipment needed when driving (special seats, levers, etc.)
  • Fluent in (Swiss) German and no speech impairment

Exclusion criteria

  • Health concerns where cannabis consumption is contra-indicated (such as: high blood pressure, psychiatric problems (e.g. psychosis, depression, attention-deficit conditions, etc.)
  • Cannabis-abstinence or excessive consumption, , assessed using the Cannabis Use Disorders Identification Test-Revised (CUDIT-R)
  • For women: pregnancy or breastfeeding or if intention to become pregnant during study period (time between telephone screening and study day (visit 2)
  • Alcohol misuse or excessive alcohol consumption habits/risky drinking behaviour, assessed using the Alcohol Use Disorders Identification Test (AUDIT) and/or phosphatidylethanol (PEth) in capillary blood > 200 ng/mL at first visit
  • If breath alcohol test is positive at Visit 1 or Visit 2 (study day)
  • Consumption of drugs of abuse (others than cannabis) within 4 weeks before the study
  • Consumption of medications / pharmaceutical drugs which interfere with driving ability
  • Inability to follow the procedures of the study, e.g., due to language

Treatment and study plan

Cannabis (THC)

Drug

Participants assigned to the experimental arm receive a single, controlled inhalative administration of cannabis by smoking a THC-containing joint (target dose 0.67 mg THC per kg body weight; cannabis flowers with 15-18% THC).

Primary outcomes

  1. Diagnostic accuracy (AUROC) of a multimodal machine-learning model for detection of cannabis-impaired driving

    Time frame: Baseline (sober driving) and up to 6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Area under the receiver operating characteristic curve (AUROC) of a single machine-learning classifier that integrates multimodal in-vehicle data (including vehicle controller area network [CAN] data, driver monitoring camera [DMC] features, and physiological signals). All modalities are combined into one predictive model, and performance is reported as one aggregated AUROC value distinguishing non-impaired (sober) driving from cannabis-impaired driving.

Secondary outcomes

  1. Diagnostic accuracy (AUROC) using CAN data

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    AUROC for detecting cannabis-impaired driving using vehicle controller area network (CAN) data only.

  2. Diagnostic accuracy (AUROC) using DMC data

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    AUROC for detecting cannabis-impaired driving using driver monitoring camera (DMC) data only.

  3. Diagnostic accuracy (AUROC) of a physiology-based machine-learning model for detection of cannabis-impaired driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    AUROC of a single machine-learning classifier trained and evaluated using aggregated physiological features only, derived from signals including heart rate, heart-rate variability, oxygen saturation, electrodermal activity, skin temperature, and respiration-related measures. All physiological signals are combined into one predictive model, and performance is reported as a single AUROC value distinguishing non-impaired (sober) driving from cannabis-impaired driving.

  4. Change in driving behavior derived from vehicle CAN data

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in driving behavior between sober driving and post-cannabis driving, derived from vehicle controller area network (CAN) signals, including steering, braking, acceleration, and velocity-related measures.

  5. Change in driver gaze behavior derived from DMC data

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in gaze behavior between sober and post-cannabis driving, derived from driver monitoring camera (DMC) data, including gaze direction and gaze dynamics during driving.

  6. Change in head movement behavior derived from DMC data

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in head movement behavior between sober and post-cannabis driving, derived from driver monitoring camera (DMC) data.

  7. Driving instructor assessment of driving performance

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Assessment of driving performance conducted by a certified driving instructor, quantified as the number of safety interventions required during each standardized driving session.

  8. Diagnostic accuracy (AUROC) of an in-vehicle pre-driving readiness test for detection of cannabis-impaired driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    AUROC of a machine-learning (ML) classification model implementing a study-specific in-vehicle pre-driving readiness test. The test produces an ML-derived readiness score, computed from features derived from the pre-driving test (e.g., attention-related, reaction-time-related, and psychomotor-related features), and is used to classify driving sessions as sober versus post-cannabis.

  9. Performance in the standardized Psytest assessment

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Performance in the standardized Psytest assessment (mobility version of the Test of Attentional Performance), administered under sober conditions and after cannabis consumption. Test performance is summarized using a standardized test score reflecting overall attentional and psychomotor performance relevant for driving.

  10. Self-reported subjective effects

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Self-reported subjective effects assessed using study questionnaires, including subjective feeling of "high" and degree of sleepiness. Responses are recorded using a Likert scale ranging from 0 to 10, where 0 indicates "not at all" and 10 indicates "extremely." Higher scores indicate a worse outcome, reflecting stronger subjective drug effects and greater sleepiness.

  11. Cannabinoid biomarker concentrations in biological samples

    Time frame: Baseline in all participants, and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm.

    Concentrations of Δ9-tetrahydrocannabinol (THC) measured in capillary blood, oral fluid, and breath samples.

  12. Incidence of adverse events

    Time frame: From the first study procedure (i.e. baseline assessment) to the end of the main study day (i.e. driving assessment) expected to be on average up to 6 hours.

    Incidence of adverse events and serious adverse events recorded during all study visits.

  13. Change in heart rate during driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in heart rate measured during driving between sober conditions and post-cannabis conditions.

  14. Change in oxygen saturation during driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in oxygen saturation measured during driving between sober conditions and post-cannabis conditions.

  15. Change in electrodermal activity during driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in electrodermal activity measured during driving between sober conditions and post-cannabis conditions.

  16. Change in skin temperature during driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in skin temperature measured during driving between sober conditions and post-cannabis conditions.

  17. Change in respiration during driving

    Time frame: Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.

    Change in respiration measured during driving between sober conditions and post-cannabis conditions.

Sponsors and collaborators

Lead sponsor

University of Bern

Other

Collaborators

  • ETH Zurich
  • University of St.Gallen

Registry information

Official study title

Randomised, Controlled, Interventional Single-center Study for the Design and Evaluation of an In-vehicle Real-time System for Detecting Cannabis-impaired Driving (CID)

Acronym: REVELIO

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Feb 10, 2026
Registry last updated
Jul 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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