The　driver＇s　takeover　behavior　is　critical　to　safety　during　automated　driving　in　fog　zones.　This　paper　aims　to　explore　the　influence　mechanism　of　takeover　behavior,　this　paper　analyzes　the　influence　of　various　factors　on　takeover　behavior　from　the　perspective　of　event　duration,　and　the　influence　mechanism　of　takeover　behavior　can　be　promoted.　A　takeover　behavior　test　platform　of　L3　automated　driving　technology　was　developed　based　on　a　driving　simulator,　and　a　high-fidelity　driving　simulation　experiment　was　carried　out　with　the　fog　zone　selected　as　the　takeover　scenario.　The　takeover　request　time　(TOR)　was　set　as　5　s　and　10　s,　and　the　no-driving-related　task　(NDRT)　was　set　as　work　tasks　and　entertainment　tasks.　42　drivers　were　invited　to　participate　in　the　experiment　where　takeover　behavior　data　were　obtained.　Takeover　response　time　and　takeover　correct　time　are　representative　indicators　of　takeover　behavior,　which　are　extracted　from　takeover　response　and　takeover　performance.　The　survival　analysis　(the　Kaplan-Meier　method　and　Cox　proportional-hazards　method)　was　used　to　explore　the　effects　of　factors　(gender,　age,　driving　age,　TOR,　NDRT)　on　survival　time　(takeover　response　time,　takeover　correct　time).　The　KM　model　results　show　that　driver　attribute　factors　(gender,　age,　and　driving　age)　had　significant　difference　on　takeover　response　time.　Females　were　more　cautious　about　the　takeover,　and　their　response　time　is　shorter　than　that　of　males.　The　takeover　response　time　increased　with　age　and　driving　age,　with　statistical　difference.　Only　TOR　had　a　statistical　difference　in　the　takeover　correct　time,　while　other　factors　had　no　statistical　significance.　The　takeover　correct　time　of　TOR-10　s　(median　=　8.50　s)　is　higher　than　the　TOR-5　s　(median　=　3.65　s).　However,　the　mean　value　of　takeover　correct　time　corresponding　to　5　s　is　higher　than　10　s.　The　Cox　model　results　are　consistent　with　the　KM　model,　and　the　model　results　show　that　external　variables　(TOR,　NDRT)　have　significant　influence　on　the　takeover　correct　time.　The　work　task　requires　more　immersion,　and　the　longer　time　it　takes　for　drivers　to　recover　the　situational　awareness　of　driving,　which　leads　to　an　increase　in　the　takeover　correct　time.　Based　on　the　survival　analysis　method,　this　research　studies　the　influence　of　factors　on　takeover　behavior　from　the　perspective　of　the　duration　of　takeover　events,　which　can　lay　a　foundation　for　in-depth　study　on　the　influence　mechanism　about　takeover　behavior.　The　study　can　also　provide　references　for　the　improvement　of　drivers＇　takeover　behavior,　and　the　optimization　design　of　the　takeover　warning　system.