Based　on　microscopic　simulation,　drivers＇　day-to-day　route　choice　behavior　and　evolution　of　network　flow　under　forecast　information　are　investigated.　First,　current　reports　hardly　research　drivers＇　day-to-day　route　choice　under　forecast　information.　A　feasible　travel　time　prediction　method　is　designed.　A　model　updating　the　drivers＇　perceived　travel　time　and　a　route　choice　model　are　developed　according　to　the　drivers＇　day-to-day　route　choice　process.　Then,　by　establishing　a　simple　road　network　with　two　parallel　routes,　the　drivers＇　day-to-day　route　choice　is　simulated　under　forecast　information.　The　fluctuation　of　route　flow　and　efficiency　of　the　system　are　analyzed　when　the　parameters　take　different　values.　Results　show　that　the　fluctuation　of　network　flow　and　efficiency　of　network　are　both　related　to　drivers＇　reliance　on　the　information　and　forecast　model＇s　parameters.　Moreover,　their　changes　are　similar.　Finally,　the　parameter＇s　optimal　range　is　obtained.