Accurately　identifying　the　key　nodes　of　the　road　network　and　focusing　on　its　management　and　control　is　an　important　means　to　improve　the　robustness　and　invulnerability　of　the　road　network.　In　this　paper,　a　classification　and　identification　method　of　key　nodes　in　urban　road　networks　based　on　multi-attribute　evaluation　and　modification　was　proposed.　Firstly,　the　emergency　function　guarantee　grade　of　road　network　nodes　was　divided　by　comprehensively　considering　the　importance　of　road　network　nodes,　the　consequences　of　failure,　and　the　degree　of　difficulty　of　recovery.　The　evaluation　indexes　were　selected　according　to　the　local　attributes,　global　attributes,　and　functional　attributes　of　the　road　network　topology.　The　spatial　distribution　patterns　of　the　evaluation　indexes　of　the　nodes　were　analyzed.　The　dynamic　classification　method　was　used　to　cluster　the　attributes　of　the　road　network　nodes,　and　the　TOPSIS　method　was　used　to　comprehensively　evaluate　the　importance　ranking　of　the　road　network　nodes.　Attribute　clustering　of　road　network　nodes　by　dynamic　classification　method　(DT)　and　the　TOPSIS　method　was　used　to　comprehensively　evaluate　the　ranking　of　the　importance　of　road　network　nodes.　Then,　combined　with　the　modification　of　the　comprehensive　evaluation　and　ranking　of　the　importance　of　the　road　network　nodes,　the　emergency　function　support　classification　results　of　the　road　network　nodes　were　obtained.　Finally,　the　method　was　applied　to　the　road　network　within　the　second　Ring　Road　of　Beijing.　It　was　compared　with　the　clustering　method　of　self-organizing　competitive　neural　networks.　The　results　show　that　this　method　can　identify　the　key　nodes　of　the　road　network　more　accurately.　The　first-grade　key　nodes　are　all　located　at　the　more　important　intersections　on　expressways　and　trunk　roads.　The　spatial　distribution　pattern　shows　a　＂center-edge＂　pattern,　and　the　important　traffic　corridors　of　the　road　network　show　a　＂five　vertical　and　five　horizontal＂　pattern.