In　this　paper,　in　order　to　describe　complex　network　systems,　we　firstly　propose　a　general　modeling　framework　by　combining　a　dynamic　graph　with　hybrid　automata　and　thus　name　it　Dynamic　Graph　Hybrid　Automata　(DGHA).　Then　we　apply　this　framework　to　model　traffic　flow　over　an　urban　freeway　network　by　embedding　the　Cell　Transmission　Model　(CTM)　into　the　DGHA.　With　a　modeling　procedure,　we　adopt　a　dual　digraph　of　road　network　structure　to　describe　the　road　topology,　use　linear　hybrid　automata　to　describe　multi-modes　of　dynamic　densities　in　road　segments　and　transform　the　nonlinear　expressions　of　the　transmitted　traffic　flow　between　two　road　segments　into　piecewise　linear　functions　in　terms　of　multi-mode　switchings.　This　modeling　procedure　is　modularized　and　rule-based,　and　thus　is　easily-extensible　with　the　help　of　a　combination　algorithm　for　the　dynamics　of　traffic　flow.　It　can　describe　the　dynamics　of　traffic　flow　over　an　urban　freeway　network　with　arbitrary　topology　structures　and　sizes.　Next　we　analyze　mode　types　and　number　in　the　model　of　the　whole　freeway　network,　and　deduce　a　Piecewise　Affine　Linear　System　(PWALS)　model.　Furthermore,　based　on　the　PWALS　model,　a　multi-mode　switched　state　observer　is　designed　to　estimate　the　traffic　densities　of　the　freeway　network,　where　a　set　of　observer　gain　matrices　are　computed　by　using　the　Lyapunov　function　approach.　As　an　example,　we　utilize　the　PWALS　model　and　the　corresponding　switched　state　observer　to　traffic　flow　over　Beijing　third　ring　road.　In　order　to　clearly　interpret　the　principle　of　the　proposed　method　and　avoid　computational　complexity,　we　adopt　a　simplified　version　of　Beijing　third　ring　road.　Practical　application　for　a　large-scale　road　network　will　be　implemented　by　decentralized　modeling　approach　and　distributed　observer　designing　in　the　future　research.