A　flexible　bus　route　optimization　scheduling　model　that　considers　the　dynamic　changes　of　passenger　demand　is　proposed　to　address　the　large　difference　in　demand　for　flexible　bus　passengers　and　real-time　variability.　This　model　uses　the　heuristic　algorithm　based　on　gravity　model　to　determine　the　following:　passenger　booking;　vehicle　passenger　capacity;　team　known　conditions　such　as　size,　according　to　the　dynamic　changes　of　passenger　demand　for　real-time　iterative　update　shuttle　travel　time;　vehicle　operating　costs　(vehicle);　and　time　cost　for　passengers　(passengers　waiting　time　for　the　vehicle,　actual　time　of　arrival,　and　the　difference　between　expected　and　actual　times　of　arrival)　before　minimization　as　the　target.　Finally,　the　practicabilities　of　the　model　and　algorithm　are　verified　by　an　example.　Analysis　results　show　that　for　102　travel　demands　of　15　randomly　generated　demand　points,　completing　all　services　requires　17-21　vehicles　with　average　travel　time　of　24.59　minutes　each.　The　solution　time　of　100　groups　of　data　is　within　25　seconds　and　the　average　calculation　time　is　12.04　seconds.　Under　the　premise　of　real-time　adjustment　of　connection　planning　time,　this　optimization　model　can　thus　better　meet　the　dynamic　demand　of　passengers　compared　with　the　current　scenario.　The　model　effectively　reduces　the　planning　path　error,　shortens　the　travel　distance　and　passenger　travel　time,　and　achieves　better　results　than　the　flexible　bus　scheduling　model　that　ignores　changes　of　connection　travel　time.