Based　on　uncertainty　theory,　this　paper　proposed　a　vehicle　scheduling　method　considering　the　dynamic　departure　interval　and　vehicle　configuration　of　electric　buses　(EBs).　An　uncertain　bi-level　programming　model　(UBPM)　is　established,　which　takes　the　total　cost　of　passenger　travel　(CP)　as　the　upper　and　total　cost　of　EBs　(CB)　as　the　lower.　A　chance　constrained　programming　model　(CCPM)　based　on　the　randomness　of　passenger　waiting　time　and　the　uncertainty　of　interstation　running　time　is　proposed　as　the　upper　model.　With　a　certain　confidence　level　of　service　level　as　constraints,　the　goal　is　to　minimize　the　total　cost　of　passenger　travel.　Then,　an　expected　value　model　(EVM)　based　on　the　fluctuation　of　energy　consumption　is　proposed　as　the　lower　model.　Taking　the　number　of　EBs　as　the　constraint　condition,　the　goal　was　to　minimize　the　energy　consumption　of　EBs.　Finally,　a　practical　bus　route　is　taken　as　an　example　to　verify　the　effectiveness　of　the　proposed　method.　The　results　demonstrated　that　the　optimal　scheduling　plan　considering　the　uncertain　variables　can　reduce　the　passenger　travel　cost.　Collaborative　optimization　of　EBs　vehicle　configuration　can　reduce　energy　consumption,　delay,　and　the　number　of　EBs.