With　increasing　demand　for　trip　on　urban　transportation　networks,　optimal　traveler　routing　has　become　a　hot　spot　of　public　concern　in　recent　years.　In　parallel,　traffic　congestion　has　an　effect　on　travel　routing　strategy.　The　fundamental　observation　is　about　the　prediction　of　real-time　traffic　flow,　which　is　focus　on　the　results　based　on　short-term　traffic　volume.　This　paper　presents　a　new　approach　which　provides　a　dynamic　route　planning　model　based　on　the　spatio-temporal　interactions　in　a　road　network.　In　addition,　it　is　necessary　to　consider　the　factors　of　security　threats　(weather,　construction,　etc.)　and　the　road　conditions　of　real-time　while　maintaining　the　accuracy　of　the　model.　Firstly,　it　predicts　the　traffic　congestion　status　upon　the　existing　historical　trajectory　data,　which　defines　congestion　coefficient　for　dynamic　planning.　Secondly,　the　simulation　results　show　that　the　improved　A∗　algorithm　and　introducing　the　congestion　coefficient　and　safety　factor　parameters　greatly　improves　the　real-time　dynamic　route　planning.　©　2019　IEEE.