Complex systems modeling for evaluating potential impact of traffic safety policies: a case on drug-involved fatal crashes

Research output: Contribution to journalArticle


Driving under the influence of illicit drugs is a critical road safety and public health concern. The U.S. National Drug Control Strategy has set a goal in 2010 to lower drugged driving significantly. In this study we presented a complex systems approach and developed a system dynamics (SD) model of drugged driving for assessing the impact of drugged driving per se law on the crash fatalities over time. The experimental analyses presented the behavioral change on the trend of number of annual drug-related fatally injured drivers when per se law is implemented with certain effect and investigated on the impact of drugged driving per se law on the number drug-related fatally injured drivers. By considering multiple interrelated factors that may influence drugged driving behaviors, the SD model was helpful in analyzing the potential “real world” impact of policy interventions on improving roadway safety and the behavior of drivers given the road infrastructure. Analyses showed that per se law would have negative exponential effect on the drugged driving fatalities over time and the policy effect would require time to be visible. In addition, combining policies of drugged driving and investing on public transportation would cause a higher change over time on reversing the trend of number of drugged driving-related crashes, however, cost effectiveness of policies still need further investigation.

Original languageEnglish (US)
JournalAnnals of Operations Research
StateAccepted/In press - Jan 1 2018



  • Drugged driving
  • Model calibration
  • Per se law
  • Public transportation
  • Simulation
  • System dynamics
  • Traffic safety

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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