Purpose GDL systems restrict newly-licensed (“intermediate”) young drivers from carrying multiple passengers and nighttime driving. We know little about the extent to which teens’ comply with GDL restrictions. Further, Methods used to measure compliance are unable to provide population-level estimates. We aimed to estimate compliance with GDL one-passenger and nighttime (11:01 pm–4:59 am) restrictions among New Jersey’s 17- to 20-year-old intermediate driver population.

Methods We used a novel application of the quasi-induced exposure (QIE) Method, a validated Method used in traffic safety research. Specifically, we borrow QIE’s primary assumption – that non-responsible drivers in “clean” (i.e., only one responsible driver) multi-vehicle crashes are randomly selected by the responsible driver and thus are reasonably representative of the general driving population. We identified all 9,250 non-responsible intermediate drivers involved in clean multi-vehicle crashes between 7/1/10–6/31/12 from NJ’s linked licensing-crash database and ascertained information on driver- and crash-level characteristics – including the presence of passengers and time of crash.

Results We estimated that 8.3% and 3.1% of intermediate driver trips were not in compliance with passenger and nighttime restrictions, respectively. Generally, non-compliance was more common among drivers residing in low-income areas, in summer months, and among older drivers; males and females had similar non-compliance rates. With NJ’s ≈170,000 young intermediate drivers taking an average of three trips per day (estimated from a separate data source), we estimate that over 40,000 intermediate driver trips in NJ each day are not in compliance with passenger restrictions.

Conclusions Results suggest there is progress to be made in encouraging teens and families to comply with GDL restrictions. Subgroups with higher noncompliance rates should be targeted for prevention efforts.

Significance/contributions This Method produces estimates very similar to those made via substantially more resource-intensive Methods such as in-vehicle technology, thus providing a more feasible and cost-effective Method to estimate population-level compliance.