Modern navigation systems prioritize fuel efficiency and time savings, often overlooking the critical aspect of road safety. This study addresses this gap by developing an advanced safe route guidance approach for Electronic Route Guidance Systems that incorporates personalized safety metrics based on individual driving behaviors and road conditions. Using the Safety Performance Function to evaluate the overall risk of road segments, and a copula model to capture the correlation between driving behaviors and road risk, this research uses conditional probability theory to quantify the safety levels of road segments for drivers with different driving behaviors to tailor safer route recommendations. The proposed approach is validated using the crash data, road geometric data, and driving behavior data collected from Los Angeles, demonstrating its capability to customize navigation based on individual driving behavior and significantly enhance route safety. The findings suggest that the safest route may vary depending on driving behavior. This research not only incorporates individualized traffic safety in navigation but also offers a scalable framework for future navigation systems to incorporate safety as a fundamental component.