THC and driving: The simulator crashes peaked at 4 hours, not right after

In a double-blind crossover trial, driving simulator collisions rose after inhaled THC, with the clearest spike at 4 hours. Chronic users did not show fewer collisions than occasional users.

Cardozo, Bibiana et al.·Journal of safety research·2025·Preliminary EvidenceRandomized Controlled Trial·3 min read
RTHC-06158Randomized Controlled TrialPreliminary Evidence2025RETHINKTHC RESEARCH DATABASErethinkthc.com/research

Quick Facts

Study Type
Randomized Controlled Trial
Evidence
Preliminary Evidence
Sample
N=30
Participants
N=30 male adults aged 18-30, chronic (1-2 joints per day) or occasional (1-2 joints per week) cannabis users, driving simulator study. Country not specified.

What This Study Found

In this double-blind crossover RCT (randomized controlled trial where each person receives each condition), inhaled THC increased driving simulator collisions, with the clearest increase observed 4 hours after 10 mg and 30 mg THC. Higher THC Cmax (peak blood THC level) was strongly linked to more collisions at 4 hours. Higher self-rated sleepiness on the Karolinska Sleepiness Scale (a 1-9 rating of how sleepy someone feels) was also linked to higher collision rates on the simulator.

Key Numbers

  • THC dose effect at 4 hours: Beta = 0.65 (95% CI: 0.45 to 0.86), meaning a higher collision rate at that time point under THC compared with placebo in this model. The size is moderate within a simulator outcome, but it comes from N=30 (small sample).
  • Blood THC Cmax (peak blood THC level) and collisions at 4 hours: Beta = 3.63 (95% CI: 2.56 to 4.70), p<0.001 (very unlikely to be random chance). This is a large association within this dataset.
  • Blood THC Cmax and collision rate: IRR (incidence rate ratio) = 37.7, p<0.001, meaning collision counts were far higher at higher peak THC levels in this model. This is an extremely large estimate that can happen when events are sparse or clustered in small samples.
  • Sleepiness and collisions: Beta = 0.10 (95% CI: 0.05 to 0.15), p<0.001 and IRR = 1.1, p<0.001, meaning each 1-point increase on the Karolinska Sleepiness Scale was linked to about a 10% higher collision rate. That is a modest per-point change.

How They Did This

This was a randomized, double-blind, crossover RCT, meaning the same 30 participants completed three separate sessions under placebo, 10 mg THC, and 30 mg THC, and neither participants nor staff knew the condition at the time. Each session was separated by a 7-day washout period, and participants stayed in the hospital for 24 hours while blood samples were collected. Driving performance was tested on the York driving simulator, and participants also completed VAS (visual analog scale) ratings and the Karolinska Sleepiness Scale to capture how they felt during testing. The most important weakness is that simulator collisions are not the same as real-world crashes, and the sample was small and limited to males aged 18-30.

Why This Research Matters

By 2025, policy and safety debates increasingly focused on whether blood THC can serve as a meaningful marker for driving risk, similar to blood alcohol. This study targeted a practical question for traffic safety science: whether a controlled THC exposure changes crash-like outcomes, and whether subjective ratings (VAS, or visual analog scales) track real performance in the same session. The crossover setup (the same participants under placebo, 10 mg, and 30 mg) reduces between-person differences that often complicate real-world crash research.

The Bigger Picture

A headline might read as if “THC increases crashes,” but the timing detail matters here because the strongest increase was reported at 4 hours after inhalation in this simulator protocol, not immediately after dosing. The study also sits at the messy intersection of two ideas that often get treated as the same thing: THC dose (10 mg vs 30 mg) is something the trial controlled, while THC Cmax (peak blood THC) is a biological measure that varied across people and was linked to collisions (IRR = 37.7) in this small sample. The abstract’s claim of no collision difference between occasional and chronic users runs against the popular assumption that frequent users are protected by tolerance, but the abstract does not report the subgroup effect sizes, so the strength of that null finding cannot be checked here. Because every participant had at least a year of cannabis use, these simulator results do not speak to first-time users or cannabis-naive drivers.

What This Study Doesn't Tell Us

Only 30 people were studied, all male and ages 18-30, which leaves open whether the same pattern holds in other groups. The outcome was crashes in a driving simulator, which can model driving errors but does not capture real-road complexity, risk-taking, or consequences. Chronic versus occasional use was discussed, but the abstract does not provide the underlying subgroup statistics, making the tolerance comparison hard to judge from the abstract alone.

Questions This Raises

  • ?How stable is the 4-hour “delayed” collision peak across different simulator tasks, longer drives, or different traffic complexity, versus being specific to the York driving simulator setup used here?
  • ?Why was THC Cmax linked to such a large incidence rate ratio (IRR = 37.7) in N=30, and how much of that estimate reflects sparse collision counts or a few high-crash sessions?
  • ?Would the same THC dose produce similar collision patterns in a mixed-sex sample or in older adults, given that this trial only included males aged 18-30?
  • ?Do VAS items like “adroitness” predict collisions consistently, or was the positive association (higher self-rated adroitness linked to more collisions) specific to this study’s scale wording and timing?

Trust & Context

Key Stat:
IRR 37.7 collision rate at 4 hours in participants with higher peak blood THC (Cmax) in this N=30 simulator trial
Evidence Grade:
Rated preliminary: a randomized double-blind crossover design, but only 30 participants and a driving simulator outcome.
Study Age:
Published in 2025. It reflects current debates about whether blood THC measures track driving risk, but the evidence here is still limited by a small, male-only sample and a simulator-based crash outcome.
Original Title:
Understanding cannabis use and car crashes: Insights from a randomized trial using a driving simulator on THC blood levels and subjective measures of sleepiness and performance.
Published In:
Journal of safety research, 95, 109-116 (2025)Journal of Safety Research is a long-running, peer-reviewed applied safety journal that publishes traffic injury and prevention research.
Database ID:
RTHC-06158

Evidence Hierarchy

Meta-Analysis / Systematic Review
Randomized Controlled TrialGold standard for testing treatments
This study
Cohort / Case-Control
Cross-Sectional / Observational
Case Report / Animal Study

Participants are randomly assigned to treatment or placebo groups to test cause and effect.

What do these levels mean? →

Frequently Asked Questions

When did crashes increase the most after THC in this driving simulator study?

Crashes increased from 1 hour after inhalation, with the strongest reported increase at 4 hours after 10 mg and 30 mg THC compared with placebo (model estimate Beta = 0.65, 95% CI 0.45 to 0.86).

Did blood THC levels actually line up with who crashed in the simulator?

Yes. Higher THC Cmax (peak blood THC) was strongly associated with more collisions at 4 hours (Beta = 3.63, 95% CI 2.56 to 4.70), and the collision-rate model reported a very large IRR of 37.7 in this small sample.

Were frequent cannabis users less impaired than occasional users in this trial?

The abstract reports no significant difference in simulator collisions between chronic users (1 to 2 joints per day) and occasional users (1 to 2 joints per week), but it does not provide subgroup effect sizes, so the strength of that null finding cannot be checked from the abstract alone.

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Cite This Study

RTHC-06158·https://rethinkthc.com/research/RTHC-06158

APA

Cardozo, Bibiana; Hartley, Sarah; Simon, Nicolas; Alvarez, Jean Claude. (2025). Understanding cannabis use and car crashes: Insights from a randomized trial using a driving simulator on THC blood levels and subjective measures of sleepiness and performance.. Journal of safety research, 95, 109-116. https://doi.org/10.1016/j.jsr.2025.09.005

MLA

Cardozo, Bibiana, et al. "Understanding cannabis use and car crashes: Insights from a randomized trial using a driving simulator on THC blood levels and subjective measures of sleepiness and performance.." Journal of safety research, 2025. https://doi.org/10.1016/j.jsr.2025.09.005

RethinkTHC

RethinkTHC Research Database. "Understanding cannabis use and car crashes: Insights from a ..." RTHC-06158. Retrieved from https://rethinkthc.com/research/cardozo-2025-understanding-cannabis-use-and

Access the Original Study

Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.

This study breakdown was produced by the RethinkTHC research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.