Car-following　model　has　important　applications　in　traffic　and　safety　engineering.　To　enhance　the　accuracy　of　model　in　predicting　behavior　of　individual　driver,　considerable　studies　strive　to　improve　the　model　calibration　technologies.　However,　microscopic　car-following　models　are　generally　calibrated　by　using　macroscopic　traffic　data　ignoring　measurement　errors-in-variables　that　leads　to　unreliable　and　erroneous　conclusions.　This　paper　aims　to　develop　a　technology　to　calibrate　the　well-known　Van　Aerde　model.　Particularly,　the　effect　of　measurement　errors-in-variables　on　the　accuracy　of　estimate　is　considered.　In　order　to　complete　calibration　of　the　model　using　microscopic　data,　a　new　parameter　estimate　method　named　two-step　approach　is　proposed.　The　result　shows　that　the　modified　Van　Aerde　model　to　a　certain　extent　is　more　reliable　than　the　generic　model.