Traffic congestion and freeway bottlenecks continue to challenge existing transportation networks. This study presents a systematic method to evaluate freeway performance and locate and rank freeway bottlenecks while accounting for both intensity and reliability dimensions of traffic congestion. A data-driven approach is used to determine a local range of the weighting factor. Based on the vehicle probe data collected on four interstate freeways in Mecklenburg County, North Carolina, a case study is conducted to illustrate this new method. Numerical results clearly indicate that although two freeway segments have nearly identical reliability values, their intensity levels can be significantly different, and vice versa. Hence, quantifying both dimensions of traffic congestion in freeway bottleneck studies is necessary. The research results can provide insightful and objective information for decision makers and transportation professionals to systematically assess traffic conditions along freeway segments and objectively locate and rank freeway bottlenecks, competently develop congestion mitigation strategies, and thus allocate limited transportation funding in a more effective and efficient manner.