With　the　rapid　urban　expansion　in　China,　there　is　considerable　development　of　road　networks,　mainly　comprising　arterial　roads,　expressways,　and　loop-lines　in　urban　regions.　In　addition　to　typical　short　trips,　certain　number　of　long　trips　are　also　included　in　the　driving　behavior　for　urban　areas.　In　view　of　the　new　characteristics　of　urban　mixed　roads,　a　driving　cycle　construction　methodology　combining　k-means　clustering　and　Markov　model　method　is　proposed　based　on　about　2.4　million　seconds　of　driving　data　collected　from　seven　passenger　cars　without　route　planning.　In　order　to　cluster　micro　trips　into　appropriate　categories　corresponding　to　different　types　of　roads,　the　Silhouette　equation　is　introduced　to　determine　the　appropriate　clustering　strategy　and　the　error　of　artificial　factors　is　restrained.　The　constructed　driving　cycle,　comprising　a　1200　s　speed-time　series,　is　developed　based　on　the　assessment　of　speed-acceleration　frequency　distribution　and　estimation　of　six　characteristic　parameters.　According　to　the　results,　the　average　difference　rate　of　six　characteristic　parameters　is　only　4.31%,　which　demonstrates　the　effectiveness　of　the　proposed　method.