Emergency　path　planning　technology　is　one　of　the　research　hotspots　of　intelligent　transportation　systems.　Due　to　the　complexity　of　urban　road　networks　and　congested　road　conditions,　emergency　path　planning　is　very　difficult.　Road　congestion　caused　by　urban　emergencies　directly　affects　the　original　road　network　structure.　In　this　way,　the　static　weight　of　the　original　road　network　is　no　longer　suitable　as　the　basis　for　path　recommendation.　To　handle　the　dynamic　situational　road　network,　an　equidistant　grid　emergency　path　planning　framework　will　be　designed.　A　novel　situation　grid　road　network　model,　based　on　situation　information,　is　proposed　and　applied　to　an　equidistant　grid　emergency　path　planning　framework.　A　situational　grid　heuristic　search　will　be　proposed　methodology　based　on　this　model,　which　can　be　used　to　detect　the　vehicles　passing　around　the　congestion　area　grid　and　the　road　to　the　destination　in　the　shortest　time.　In　the　path　planning　methodology,　a　grid　inspired　search　strategy　based　on　quaternion　function　is　included,　which　can　make　the　algorithm　converge　to　the　target　grid　quickly.　Three　graph　acceleration　algorithms　are　proposed　to　improve　the　search　efficiency　of　path　planning　algorithm.　Finally,　this　paper　will　set　up　three　experiments　to　verify　our　proposed　method.