Recently,　researches　about　Forward　Collision　Warning　(FCW)　technology　has　become　one　of　the　main　parts　of　the　development　of　Advanced　Driver　Assistance　Systems　(ADAS)　to　increase　the　road　safety　and　develop　autonomous　vehicles.　This　paper　presents　a　research　about　FCW　based　on　monocular　vision,　which　consists　of　two　processes:　vehicle　detection　and　vehicle　tracking.　In　the　vehicle　detection　process,　the　vertical　and　horizontal　edges　and　the　shadows　under　the　vehicles　are　combined　at　first　to　roughly　generate　hypothesis　of　all　the　vehicles＇　positions,　and　then　HOG　transform　and　an　improved　Adaboost　classifier　are　applied　to　these　positions　to　eliminate　non-vehicles.　In　the　vehicle　tracking　process,　frames　are　handled　by　an　innovative　feature　point　matching　method　based　on　Harris　detector　and　normalized　cross　correlation,　and　the　distance　is　measured　by　checking　the　bottom　line　of　newly　tracked　vehicles＇　bounding　box.　The　presented　method　is　verified　by　experiments,　and　is　proved　to　have　good　performance.