Safety is a critical aspect of transportation design and operations. Practitioners utilize various references to ensure that roadways meet safety, operational, and sustainability requirements. Despite this, human error remains as a contributing factor toward unsafe driving behavior and potential crashes. Connected and autonomous vehicles (CAVs) have the potential to enhance traffic safety and operations. Although sensor perception ranges and capabilities pose challenges, the sharing of information via Vehicle-to-Everything (V2X) communication provides CAVs with a potential solution for overcoming sensor limitations. The objective of this study is to use the Simulation of Urban Mobility software to assess safety impacts when using V2X to share sensor-obtained roadway information with a CAV. To this end, this study proposes a novel method for simulating driver behavior that combines car following with consideration of the roadway’s geometric configuration. Several scenarios are utilized to observe the behavior of simulated drivers on a straight tangent approaching a sharp horizontal curve. This study evaluates driver performance using the measured values for longitudinal jerk, lateral jerk, and speed variance. The results of this study indicate that V2X sensor sharing can provide significant benefits to CAV performance and can reduce the safety risk. CAVs receiving sensor-obtained information behave in a manner more akin to their human-driven counterparts in comparison to those receiving basic safety messages. CAVs using sensor-obtained information maintain braking and lateral jerk values within safety thresholds. In addition, speed variance was at its lowest when CAVs utilized V2X sensor information.