This paper addresses a partially connected vehicle environment (PCVE), where a only fraction of vehicles are equipped with V2V communication technology, and presents a method of realizing highly anticipative driving in it. More specifically, anticipative driving refers to the predictive control of a host vehicle considering the preceding traffic conditions in an extended view but in an abstract form. For acquiring the traffic conditions of the preceding road section, a road-speed profile is proposed, which is dynamically updated using limited V2V data in a bi-level approximation framework. In the lower level of the framework, the state of the known vehicles within the communication range are predicted in a short horizon using a conditional persistence prediction model. The model parameter is determined by fitting with the experimental driving data. In the upper level, the time, position and speed of the vehicles obtained from the lower level are then mapped onto the road, which is represented by a sequence of connected cells. Finally, the average traffic speed in each road cell is calculated using weighted and moving average techniques. The approximation accuracy of the road-speed profile and its potential benefits in implementing highly anticipative driving of a host vehicle are evaluated.