The　capacity　region　(CR)　is　a　key　index　to　characterize　a　dynamic　processing　system＇s　ability　to　handle　incoming　demands.　It　is　a　multidimensional　space　when　the　system　has　multiple　origin-　destination　pairs　where　their　service　rates　interact.　An　urban　traffic　network　is　such　a　system.　Traffic　congestion　appears　when　its　demand　approaches　or　exceeds　the　upper　frontier　of　its　CR.　Part　I　of　this　study　theoretically　proved　that　(1)　accurate　I-SFR　information　of　additional　conflicting　movements　can　enlarge　the　CR,　and　(2)　improving　the　I-SFR　prediction　accuracy　of　observed　movements　can　expand　the　CR.　However,　such　expansion　has　not　been　validated　through　experiments.　Part　II　of　this　study　thus　focuses　on　validating　the　theoretical　findings　in　Part　I.　We　use　a　real-time　traffic　control　policy,　named　BackPressure　(BP)　control,　to　act　as　a　ruler　to　measure　the　size　of　CR.　We　first　prove　that　BP　policy　with　partial　I-SFR　information　can　stabilize　the　network　within　the　corresponding　CR.　Then　we　design　various　calibrated　simulation　experiments　to　check　the　validity　of　the　two　findings　in　Part　I.　Specifically,　we　use　reserve　demand,　which　represents　the　distance　between　a　given　demand　and　the　frontier　of　CR,　as　a　direct　index　to　reflect　the　size　of　CR,　and　use　delay　as　an　indirect　index　to　reflect　the　changes　in　CR.　Simulation　results　confirm　the　theories　in　Part　I.