This　paper　aims　to　deeply　analyze　the　regularity　of　residents＇　daily　activity-travel　behaviors　to　help　traffic　management　departments　predict　travel　demand　and　evaluate　transportation　policies.　Taking　time　use　data　in　American　as　empirical　analysis,　the　influencing　factors　such　as　residents＇　activity　pattern,　duration　and　competition　were　discussed　and　analyzed　based　on　the　competing　risk　model.　Results　can　be　concluded　that:　a)　people　feel　happy　and　meaningful　during　most　of　the　activities,　while　they　feel　sad　or　pain　in　relatively　rare　occasions;　b)　there　is　no　significant　difference　between　young　people　and　the　elderly　as　for　the　total　number　of　activities　during　one　day;　c)　estimation　results　show　that　personal,　household　and　activity　characteristics　have　significant　influence　on　activity　duration　and　pattern,　and　the　pattern　of　last　activity　(N)　has　a　great　influence　on　the　occurrence　of　next　activity　(N+1);　d)　the　competition　between　residents＇　daily　activities　is　confirmed　based　on　the　competing　risk　model,　and　travel　is　closely　related　to　various　activities　and　can　be　seen　as　the　derived　demand　of　various　activities.　In　all　combinations　of　activity-travel　chain　schedule,　personal　-　household　(30.0%),　household　-　recreation　(25.9%),　work　-　travel　(45.2%),　purchase　-　travel　(33.7%),　recreation　-　travel　(22.5%),　volunteer　-　travel　(55.3%)　and　travel　-　purchase　(28.4%)　have　the　highest　proportion　respectively.