<p dir="ltr">Aerodynamic interactions arising from the close proximity of race cars significantly influence drag, downforce, and performance during overtaking and defensive maneuvers in racing scenarios during overtaking and high-intensity racing situations. Despite advancements in individual vehicle aerodynamics, there is limited understanding of how these interactions influence performance in dynamic race conditions. This thesis investigates the aerodynamic effects of race traffic interactions using computational fluid dynamics (CFD). Simulations conducted in Siemens STAR-CCM+ focus on straight line and cornering scenarios for the Hyundai Elantra N TCR. Cornering simulation techniques are developed and compared to identify effective methods for capturing the complexities of curved flow dynamics. Results demonstrate the impact of vehicle positioning on aerodynamic performance, with strategies identified for optimizing drag reduction and maintaining downforce during straightaways and corners. This research advances knowledge of race traffic aerodynamics, offering valuable insights into the aerodynamic challenges and opportunities faced in competitive motorsport environments. The findings provide a foundation for future studies aiming to enhance understanding and application of vehicle aerodynamics in race scenarios.</p>