To　reveal　the　key　influencing　factors　and　rules　of　intercity　travel　decisions　under　abnormal　circumstances,　16　kinds　of　travel　scenarios　were　designed　for　stated　preference　(SP)　survey　according　to　the　level　of　blocking　events,　the　amount　of　time　of　bypassing　the　route,　and　the　type　of　travel　(elasticity　trip　and　rigidity　trip).　The　questionnaire　included　11　factors　affecting　residents＇　travel　decisions　and　4　decision　options.　Based　on　the　multinomial　logistic　regression,　travel　decision　models　were　built　by　using　the　SP　Data　of　16　abnormal　scenes　in　intercity　travel.　Results　show　that　the　significant　factors　affecting　residents＇　decision-making　are　different　from　the　extent　of　the　interruption　of　the　events,　the　distance　of　the　bypass,　and　different　purposes　of　the　trip.　Moreover,　there　is　a　difference　in　the　degree　of　influence　for　the　same　factor　in　different　scenes.　Among　them,　the　travel　time　consumption　and　residents＇　preference　for　a　certain　travel　mode　are　the　most　significant　factors　followed　by　the　trip　frequency　and　occupation　under　different　travel　scenarios.　Nevertheless,　driving　age,　age　and　gender　have　significant　effects　under　individual　scenarios.　These　results　can　be　used　to　predict　the　travel　behavior　of　the　residents　under　the　road　blocking　event　in　the　integrated　transportation　network.　It　can　also　provide　support　for　personalized　and　refined　travel　information　service　to　different　travel　individuals　in　abnormal　circumstances.　©　2019,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.