With the rapid advancement of electric vehicle (EV) technology, EV has been emerging as a promising transportation due to the low carbon emission. However, the frequent and long time charging is indispensable to continue travelling. During peak hours, EVs further spend long time on the path routing because of the traffic congestion and queuing in the charging stations. Therefore, we study the EV charging scheduling problem that minimizes the total elapsed time which includes charging time for EVs through jointly optimizing the charging path routing and charging station selection in this paper. Considering the NP-hardness of this optimization problem, we propose an efficient EV charging scheduling method to obtain the optimal solution based on crowd sensing through considering the remaining energy in the battery, traffic condition, and the queue length of charging stations. Simulation results demonstrate that the proposed backtracking method based on crowd sensing can effectively reduce the total elapsed time, in comparison with the greedy algorithm.