In　urban　transportation　network,　generally,　traffic　sensors　are　unable　to　fully　cover　the　freeway　network,　and　only　local　measurement　data　is　available.　To　accurately　and　timely　estimate　traffic　density　in　an　urban　freeway　network,　this　paper　proposes　a　distributed　state　observer　approach　based　on　a　macroscopic　traffic　flow　model.　Firstly,　the　urban　freeway　network　is　modeled　in　the　way　of　distributed　systems　by　using　the　cell　transmission　model　(CTM).　Secondly,　based　on　the　model,　a　distributed　observer　is　designed,　which　gains　are　computed　by　using　LMI　technique　according　to　the　Lyapunov　function　and　S-procedure　theory.　Thus,　the　traffic　densities　of　the　whole　network　can　be　estimated　by　the　distributed　observer.　This　method　was　applied　to　Beijing　third　ring　road　and　experimental　results　demonstrate　the　effectiveness　and　applicability　of　the　proposed　approach.　©　ASCE.