|Statistics reveal that from 2007-2011 an average of 751 people died each year in red-light running (RLR) crashes in the U.S. Past studies showed that red light cameras (RLCs), as an enforcement countermeasure, can lower RLR fatalities at signalized intersections. Currently, approximately 430 individual communities run RLC programs in the U.S. and over 40 intersections in Alabama are equipped with these cameras. As more RLCs are installed at intersections in Alabama, understanding their effects and how to best implement them is of growing importance. While extensive research has investigated the safety effects of the system, very little work has been done to investigate the impacts of RLCs on driver behavior and intersection operation. To date, very few study has evaluated the effects of RLCs in Alabama. The primary objective of this study is to fill the research gap by evaluating the effectiveness of RLC program, in terms of safety, operation, and driver behavior, while also developing a novel fine structure for RLR traffic violations. In the first step, the complete process of extracting RLR crash data from Critical Analysis and Reporting Environment is presented to identify target crashes. More importantly, an extensive field observation is conducted to collect drivers’ responses to clearance intervals at four intersections with RLCs and four intersections without RLCs. The increase in the intersection delays due to the presence of RLCs can be estimated. The results indicate a higher tendency to stop and a longer delay at intersections equipped with RLCs. Furthermore, a comparison among clearance lost time values, collected in the field and estimated using the Highway Capacity Manual method and Alabama Department of Transportation’s Traffic Signal Design Guide and Timing Manual method, demonstrates that both manuals overestimate the intersection's capacity. An adjustment factor is estimated and recommended for improving accuracy of both methods. In the last step of the research, a novel method is developed to determine a basis for RLR fines by considering the cost of a potential RLR crash and its resulting delay, which is the first of its kind reported in the literature. Various statistical tests and simulation models are used to accomplish the objectives of this study.