Potential collisions with oncoming traffic while turning left belong to the most safety-critical situations with ~25% of all intersection crossing path crashes. A Left Turn Assist (LTA) was developed to reduce the number of crashes. Crucial for the effectiveness of the system is the design of the human machine interface, i.e. defining how the system uses the calculated crash probability in the communication with the driver. A driving simulator study was conducted evaluating a warning strategy for two use cases: firstly, the ego-vehicle comes to a stop before turning (STOP), and secondly, the driver moves on without stopping (MOVE). 40 drivers drove through three STOP and two MOVE scenarios. For the STOP scenarios, the study compared the effectiveness of an audio-visual warning with an additional brake intervention and a baseline. For the MOVE scenarios, the study analyzed the effectiveness of the audio-visual warning against a baseline. The results showed that the brake intervention is highly effective resulting in significantly larger minimal distances between ego-vehicle and conflict partner. For the MOVE scenarios, the warning strategy is only effective in one scenario, reflecting the higher complexity of MOVE scenarios with regard to the prediction of crash probabilities due to the variability of driving/turn trajectories. Concluding, the brake intervention in STOP scenarios could be further investigated as a promising HMI strategy. Future studies should figure out the appropriate strength of a brake intervention in a real vehicle. MOVE scenarios face big challenges due to the variance of driver behavior in turning situations.