In　modern　transportation,　pavement　is　one　of　the　most　important　civil　infrastructures　for　the　movement　of　vehicles　and　pedestrians.　Pavement　service　quality　and　service　life　are　of　great　importance　for　civil　engineers　as　they　directly　affect　the　regular　service　for　the　users.　Therefore,　monitoring　the　health　status　of　pavement　before　irreversible　damage　occurs　is　essential　for　timely　maintenance,　which　in　turn　ensures　public　transportation　safety.　Many　pavement　damages　can　be　detected　and　analyzed　by　monitoring　the　structure　dynamic　responses　and　evaluating　road　surface　conditions.　Advanced　technologies　can　be　employed　for　the　collection　and　analysis　of　such　data,　including　various　intrusive　sensing　techniques,　image　processing　techniques,　and　machine　learning　methods.　This　review　summarizes　the　state-of-the-art　of　these　three　technologies　in　pavement　engineering　in　recent　years　and　suggests　possible　developments　for　future　pavement　monitoring　and　analysis　based　on　these　approaches.　(C)　2021　THE　AUTHORS.　Published　by　Elsevier　LTD　on　behalf　of　Chinese　Academy　of　Engineering　and　Higher　Education　Press　Limited　Company.