Locating　the　bottlenecks　in　cities　where　traffic　congestion　usually　occurs　is　essential　prior　to　solving　congestion　problems.　Therefore,　this　paper　proposes　a　low-frequency　probe　vehicle　data　(PVD)-based　method　to　identify　turn-level　intersection　traffic　congestion　in　an　urban　road　network.　This　method　initially　divides　an　urban　area　into　meter-scale　square　cells　and　maps　PVD　into　those　cells　and　then　identifies　the　cells　that　correspond　to　road　intersections　by　taking　advantage　of　the　fixed-location　stop-and-go　characteristics　of　traffic　passing　through　intersections.　With　those　rasterized　road　intersections,　the　proposed　method　recognizes　probe　vehicles＇　turning　directions　and　provides　preliminary　analysis　of　traffic　conditions　at　all　turning　directions.　The　proposed　method　is　map-independent　(i.e.,　no　digital　map　is　needed)　and　computationally　efficient　and　is　able　to　rapidly　screen　most　of　the　intersections　for　turn-level　congestion　in　a　road　network.　Thereby,　this　method　is　expected　to　greatly　decrease　traffic　engineers＇　workloads　by　providing　information　regarding　where　and　when　to　investigate　and　solve　traffic　congestion　problems.