A computer-implemented method for operating an autonomous vehicle, the method comprises: defining a plurality of driving scenarios for a plurality of types of autonomous vehicles, each driving scenario corresponding to a specific movement of a particular type of autonomous vehicles; for each of the plurality of driving scenarios of each type of autonomous vehicles, obtaining driving statistics of each autonomous vehicle, including recording one or more driving parameters used to control and drive each autonomous vehicle of the type, capturing a driving condition corresponding the driving scenario, and measuring a sideslip caused by the recorded driving parameters and the captured driving condition; constructing a driving scenario to sideslip (scenario/sideslip) mapping table having a plurality of mapping entries, each mapping entry mapping a particular driving scenario to a sideslip, wherein the scenario/sideslip mapping table is utilized to compensate a calculated route of an autonomous vehicle in view of a sideslip under a similar driving scenario; detecting that a next movement of a first autonomous vehicle involves a turn according to a planned route; determining a first driving scenario corresponding to the next movement according to the planned route; searching in the scenario/sideslip mapping table based on the first driving scenario to locate a mapping entry corresponding to a second driving scenario matching the first driving scenario; modifying driving parameters of the first autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry; generating planning and control data based on the modified driving parameters; and controlling and driving the first autonomous vehicle based on the planning and the control data. defining a plurality of driving scenarios for a plurality of types of autonomous vehicles, each driving scenario corresponding to a specific movement of a particular type of autonomous vehicles; for each of the plurality of driving scenarios of each type of autonomous vehicles, obtaining driving statistics of each autonomous vehicle, including recording one or more driving parameters used to control and drive each autonomous vehicle of the type, capturing a driving condition corresponding the driving scenario, and measuring a sideslip caused by the recorded driving parameters and the captured driving condition; recording one or more driving parameters used to control and drive each autonomous vehicle of the type, capturing a driving condition corresponding the driving scenario, and measuring a sideslip caused by the recorded driving parameters and the captured driving condition; constructing a driving scenario to sideslip (scenario/sideslip) mapping table having a plurality of mapping entries, each mapping entry mapping a particular driving scenario to a sideslip, wherein the scenario/sideslip mapping table is utilized to compensate a calculated route of an autonomous vehicle in view of a sideslip under a similar driving scenario; detecting that a next movement of a first autonomous vehicle involves a turn according to a planned route; determining a first driving scenario corresponding to the next movement according to the planned route; searching in the scenario/sideslip mapping table based on the first driving scenario to locate a mapping entry corresponding to a second driving scenario matching the first driving scenario; modifying driving parameters of the first autonomous vehicle by taking into consideration of a first sideslip obtained from the located mapping entry; generating planning and control data based on the modified driving parameters; and controlling and driving the first autonomous vehicle based on the planning and the control data. <EOS>