There have been significant research and developments in recent years for intersection-safety solutions that are intended to alert drivers of hazardous situations by utilizing sensing, computing, and communication technologies. Since the effectiveness of intersection-safety systems depends strongly on driver perception and acceptance of the provided warning signal, the understanding of driver actions under the targeted scenario is a central research topic. One significant safety concern at intersections is the left-turn crossing-path scenarios, where a left-turning vehicle is confronted by oncoming traffic. This paper describes the analysis and synthesis of real-world data for such scenarios observed in field observations. Specifically, traffic interactions in left-turn across-path situations are evaluated to compare data from various intersections with different operation and traffic attributes. The analyzed data were characterized to gain insight into a time gap acceptance exhibited by a population of drivers. The knowledge of driving behaviors can provide the guidelines for future investigation as well as a knowledge basis for the selection of warning criteria to allow timely alerts to drivers in the intended safety applications.