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.