1. A traffic simulator, comprising: a setting portion that, when a vehicle model, which is a model of a vehicle, is virtually driven on a road and traffic conditions are simulated, sets ability information representing driving abilities of a driver of the vehicle model; a storage portion that stores space arrangement data representing an arrangement of the vehicle model in a virtual road space; a searching portion that searches the road space, which is represented by the space arrangement data stored in the storage portion, for cautionary objects that should be heeded by the driver when driving the vehicle model; a selection portion, using a processor, that selects a plurality of cautionary objects recognized by the driver from the cautionary objects found by the searching portion based on the ability information of the driver set by the setting portion, the selection portion selecting, as the cautionary objects recognized by the driver, the cautionary objects found by the searching portion whose required level of experience for driver recognition, represented by a level of experience information associated with each predetermined cautionary object, is less than or equal to a level of driving experience of the driver included in the ability information of the driver; and a determination portion that calculates a plurality of movement ranges of the vehicle mode, based on the plurality of cautionary objects selected by the selection portion, and determines a movement of the vehicle model based on the plurality of movement ranges, wherein: the ability information further includes at least one of information representing an eyesight ability of the driver or information representing a level of concentration ability of the driver; the storage portion further stores, for each predetermined cautionary object, recognition time information representing a time required for the driver to recognize the cautionary object according to at least one of eyesight ability or level of concentration ability; and the selection portion, based on the recognition time information stored in the storage portion, obtains the time required for the driver to recognize the cautionary object found by the searching portion according to at least one of the eyesight ability or the level of concentration ability of the driver set by the setting portion, adds together the obtained required times in a predetermined order of priority or in a random order, and selects as cautionary objects recognized by a driver those cautionary objects which are added within a movement determination time required for the driver to recognize cautionary objects and for the movement of the vehicle model to be determined.