This　paper　studies　the　problem　of　the　adaptive　boundary　observer　design　for　the　Aw-Rascle-Zhang　(ARZ)　traffic　flow　model,　which　is　subject　to　both　relaxation　time　uncertainty　in　the　domain　and　boundary　input　disturbance.　The　boundary　input　disturbance　comes　from　merging　vehicles＇　velocities　at　the　downstream　on-ramp,　and　we　scale　the　disturbance　by　a　low-pass　filter　based　on　the　ordinary　differential　equation　(ODE).　Then,　the　ARZ　model　with　the　domain　uncertainty　and　boundary　input　disturbance　can　be　linearized　to　a　coupled　ODEPDE　system.　Based　on　the　swapping　transformation,　an　adaptive　boundary　observer　with　least-squares　type　parameter　estimation　is　designed　to　estimate　the　traffic　states,　the　domain　uncertainty,　and　the　boundary　input　disturbance,　simultaneously.　The　exponential　convergence　conditions　w.r.t.　observer　feedback　gains　are　given　by　employing　the　Lyapunov　technique.　Finally,　the　simulation　results　are　presented　to　illustrate　the　effectiveness　of　the　designed　adaptive　boundary　observer.