Signalized　intersections　are　critical　for　the　safety　and　efficiency　of　urban　traffic　systems.　With　the　proposal　of　the　new　national　infrastructure　strategy　and　the　continuous　development　of　vehicle-road　coordination　techniques,　the　layout　of　connected　and　automated　vehicle　(CAV)　entrance　lanes　for　intersections　is　beneficial　to　improving　capacity　and　reducing　delay,　and　promoting　the　efficiency　and　safety　of　urban　transportation　systems.　However,　the　use　of　CAVs　influences　the　car-following　characteristics,　which　are　different　from　those　of　traditional　vehicles.　In　this　study,　cooperative　adaptive　cruise　control　and　General　Motor　models　were　established　to　simulate　the　car-following　behavior　of　connected　and　nonconnected　vehicles,　respectively.　The　operational　characteristics　of　a　mixed　traffic　flow　under　different　driving　conditions　at　signalized　intersections　were　then　simulated　using　the　models.　The　dynamic　layout　conditions　for　the　CAV　entrance　lane　under　different　conditions　were　proposed　to　improve　capacity　and　minimize　delay　and　fuel　consumption,　considering　the　ratio　of　CAVs,　number　of　entrance　lanes,　traffic　volume,　and　signal　timing　scheme.　The　numerical　simulation　results　indicate　that　the　proposed　method　improves　traffic　efficiency　and　reduces　delay　and　fuel　consumption　at　signalized　intersections.　A　feasible　approach　for　designing　CAV　entrance　lanes　at　signalized　intersections　in　intelligent　network　environments　was　proposed　in　this　study.　Moreover,　this　study　can　serve　as　a　reference　for　related　research　on　vehicle-road　coordination　systems.　©　2022　Xi＇an　Highway　University.　All　rights　reserved.