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.