An　improved　cellular　automata　model　based　on　car-truck　combination　effect　oriented　to　faithfully　reproducing　the　characteristics　of　heterogeneous　traffic　flow　is　presented　in　this　paper.　The　model　focuses　on　reflecting　complex　car-following　and　lane-changing　behavior　of　cars　and　trucks　by　incorporating　the　difference　of　physical　performance　and　driving　behavior　between　cars　and　trucks　and　the　behavioral　change　caused　by　car-truck　interaction.　The　update　rules　of　cars　and　trucks　were　constructed　separately　based　on　the　analysis　results　of　NGSIM　and　SP　survey.　The　impact　of　the　truck　in　front　was　introduced　into　the　model,　which　can　affect　the　lane-changing　probability,　safety　expectation　and　randomization　probability.　As　revealed　by　the　simulation　results,　the　driving　of　vehicles　in　the　heterogeneous　traffic　(i.e.　car-truck,　truck-car,　car-car　and　truck-truck)　is　reproduced　properly　through　the　model.　In　addition,　the　model　is　capable　of　reproducing　the　hysteresis　phenomenon　and　identifying　three　typical　traffic　states,　namely　free　flow,　synchronized　flow　and　jam.　Under　certain　conditions,　trucks　can　help　to　eliminate　the　propagation　of　congestion　waves.　Moreover,　the　percentage　of　trucks　and　truck　impact　have　a　significant　influence　on　the　fundamental　diagram,　congestion　rate,　lane-changing　rate　and　traffic　stability.　The　findings　of　this　study　can　provide　a　basis　for　further　research　on　the　heterogeneous　traffic.　(C)　2020　Elsevier　B.V.　All　rights　reserved.