The use of cannabis, prescription drugs, and other drugs are increasingly prominent on roadways in the United States, where 25.1 percent of the nation’s 36,096 fatalities in 2019 were related to drug-involved driving. Driving can be impaired by a variety of legal and illegal drugs, substances, and medications. Several states have legalized the use of medical and/or recreational cannabis, increasing concerns about traffic safety. Aside from alcohol, cannabis is the most frequently detected drug in drivers who are in crashes. The impact of drugs on the brain and behavior varies considerably depending on the type of drug and how it is metabolized. There are also large variations across jurisdictions in the frequency of testing suspected impaired drivers for drugs, the consistency of laboratory drug testing practices, and the capacity of law enforcement. Despite challenges in identifying causality and impairment, there is agreement that many illicit, prescription, and overthe- counter drugs impair driving.
Historically, road safety efforts focused on changing human behaviors to prevent crashes. The Safe System approach reframes efforts to save lives by expecting crashes to happen and focusing attention on reducing the severity of injuries when a crash occurs. By understanding the nuances of drug-involved crashes, transportation professionals can better address every aspect of crash risks and implement multiple layers of protection to ensure that everyone traveling on California roadways will go safely. Analyses from FARS presented in the drug-involved program area include fatalities in crashes that involved a driver who tested positive for a drug that could cause impairment. Analyses from SWITRS presented in this program area refer to drug-involvement and include fatal and serious injuries where law enforcement reported the driver to be under the influence of drugs. Crashes in the program area are defined as where one or more drivers tested positive for a drug that could cause impairment or was reported as driving under the influence of drugs, depending on which data set is used.
