Near-miss accidents at intersections are still reported globally. This is due to the driver inattention during the scenario. Though many collision warning systems have been introduced, such systems are ineffective in alerting the drivers during the sudden emergence of unknown moving vehicles at intersections. This paper proposes an intersection collision avoidance (CA) architecture, composed of Artificial Potential Field (APF) as the motion planning and Nonlinear Model Predictive Control (NMPC) as the path tracking strategy. To aid the driver inattention, APF considers the risk of intersections and collision with the moving obstacles. NMPC is adopted into the architecture to guide the CA navigation. When the host vehicle approaches the intersection, the desired deceleration value is yielded. Once the occluded moving obstacle appears, APF provides the desired vehicle states for path replanning based on the collision risks. NMPC acts as automated motion guidance for the host vehicle to handle the abrupt increment of vehicle summation forces during the navigation. To evaluate the system efficacy, computational simulation is done and the performance is compared with the Time-to-Collision and Safe-Distance to ensure its reliability in preventing near-miss accidents. Results show that the consideration of intersection risk together with the risk of collision with the moving obstacle aids in preventing near-miss intersection collisions.