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In China, F-type-5 m intersections are not uncommon. One approach of these intersections usually includes a driveway closely followed by an intersecting street, and the driveway and the intersecting street are parallel and approximately 5 m apart. Nowadays, drivers often rely on the navigation systems for directions. However, it is found that the navigation systems sometimes mislead or confuse drivers to make wrong turns or miss their turns at such F-type-5 m intersections. This study proposed to employ driving simulation to identify the appropriate prompt message delivered at the right prompt timing to help drivers navigate through such F-type-5 m intersections. First, a within-subjects two-factor experiment was designed. One factor was the Prompt Timing Mode (PTM), representing a set of three sequential messages broadcast by the navigation system at varying distances to the intended intersection; the other factor was the Prompt Message Type (PMT), representing various sets of three sequential messages broadcast by the navigation system. Three Prompt Timing Modes were used: PTM1 = {− 400 m, -200 m, − 30 m}, PTM2 = {− 300 m, − 150 m, − 30 m}, and PTM3 = {− 200 m, − 100 m, − 30 m}. Three Prompt Message Types were defined: PMT-A = {Turn right at the traffic light XXm ahead; Turn right at the traffic light XXm ahead; Turn right}, PMT-B = {Turn right at the traffic light XXm ahead, enter YY street; Turn right at the traffic light XXm ahead, enter YY street; Turn right}, PMT-C = {Turn right at the traffic light XXm ahead, enter YY street, and please use the second right turn lane; Turn right at the traffic light XXm ahead, enter YY street, and please use the second right turn lane; Turn right}. The combinations of the two factors generated nine experimental intersections which were randomly assigned to three experimental routes. Then, a total of 37 drivers were recruited, and participated in the driving simulation experiment from which vehicle operation data were collected under different prompt timing modes and message types. Next, the repeated Analysis of Variance (rANOVA) was performed to examine the effects of different prompt timing modes and prompt message types on vehicle operation indicators, such as Driving Time, Standard Deviation of Speed, Absolute Value of Acceleration, and Standard Deviation of Acceleration. Finally, the grey near-optimal method was adopted to evaluate the effectiveness of three prompt message types under each prompt timing mode. The rANOVA results showed the vehicle operation in the F-type-5 m intersection was affected by prompt timing modes and prompt message types; the evaluation results indicated that PMT-C made drivers perform better in PTM1 and PTM3, while PMT-B made drivers perform better inPTM2. However, the effectiveness of PMT-A was the lowest in each prompt timing mode. The research results provide valuable guidance to design the human machine interface of navigation systems, which can help drivers safely navigate through F-type-5 m intersections. This research also has laid solid foundations for establishing navigation messaging design guidelines.