Road　intersections　are　important　components　of　urban　road　system.　It　is　the　traffic　flow　characteristics　representing　the　current　traffic　situation　that　provide　a　basis　for　the　planning,　designing　and　management　of　intersections.　In　this　paper,　we　constructed　an　automatic　processing　framework　on　traffic　flow　characteristics　analysis　and　understanding　the　traffic　state　at　the　urban　road　intersections,　based　on　the　collected　raw　vehicle　motion　trajectories.　Our　proposed　method　is　basically　attributed　to　identifying　distinct　vehicle　motion　patterns　at　intersections　hierarchically　using　raw　trajectory.　Firstly,　the　fundamental　assumption　in　traditional　approaches　that　the　trajectory　set　of　high　quality　are　readily　available　after　manual　rectification　is　not　taken　for　granted　any　more.　And　by　fully　analyzing　the　local　characteristics　of　trajectories,　we　figure　out　and　explain　various　patterns　behind　traffic　flow　as　well　as　yielded　higher　accuracy　in　motion　trajectory　clustering　under　the　multi-layer　spectral　clustering　method.　At　last,　coupling　the　analyzing　results　with　the　surrounding　characteristics　of　the　intersection,　the　examples　computing　traffic　flow　features　and　predicting　vehicle　activity　illustrates　the　potential　of　applying　vehicle　trajectories　to　traffic　study,　which　are　all　suggested　by　experimental　results.　©　2011　IEEE.