Surrogate safety measures provide information about the safety of traffic facilities without waiting for crashes to occur. Most studies related to surrogate safety measures were performed at intersections. Traffic accident statistics show that sideswipe crashes have a considerable percentage of all crashes. Sideswipe crashes arising from lane-change conflicts are highly probable at weaving segments. This study focuses on lane-change conflicts at weaving segments and proposes a new index.Considering the interactions between the subject vehicle and the surrounding vehicles, two new surrogate safety measures, time- and position-based, are recommended. Then, applying a fault tree analysis, these two measures are converted to a lane change risk index to estimate the crash severity. The proposed index is specific to weaving segments. Data from five weaving segments were extracted using deep learning detection and tracking algorithms.The results based on the relationship between the proposed indexes and speed showed that the probability and severity of a crash increased as the speed increased. The longer weaving length resulted in smaller values in the time-based index.The weaving length is critical because it becomes difficult to perform a lane change if the length is too short. The proposed time and position-based indexes combine the effect of weaving length, stopping distance index, time to collision, and brake time. It is believed that the proposed lane change risk index can be used to detect the safety level of weaving segments.