Research into the impact of road accidents on drivers is essential to effective post-crash interventions. However, due to limited data and resources, the current research focus is mainly on those who have suffered severe injuries. In this paper, we propose a novel approach to examining the impact that being involved in a crash has on drivers by using traffic surveillance data. In traffic video surveillance systems, the locations of vehicles at different moments in time are captured and their headway, which is an important indicator of driving behavior, can be calculated from this information. It was found that there was a sudden increase in headway when drivers return to the road after being involved in a crash, but that the headway returned to its pre-crash level over time. We further analyzed the duration of the decay using a Cox proportional hazards regression model, which revealed many significant factors (related to the driver, vehicle, and nature of the accident) behind the survival time of the increased headway. Our approach is able to reveal the crash impact on drivers in a convenient and economical way. It can enhance the understanding of the impact of a crash on drivers, and help to devise more effective re-education programs and other interventions to encourage drivers who are involved in crashes to drive more safely in the future.