The global strategic imperatives of carbon dioxide emission reduction and carbon neutrality, together with the promotion of high-quality sustainable development, have led to a progressive decline in the reliance on fossil fuels across both commercial and passenger vehicle fleets. In response, a growing number of freight carriers are transitioning toward electric trucks as their primary delivery fleet. This study addresses the local container drayage problem with electric vehicles and conventional diesel vehicles, aiming to find out the gap between these two different types of vehicles within and outside the tractor-container separation mode. In this context, an electric tractor can be separated from the container during the process of (un)loading at customer nodes for the other tasks or recharging. This study also focuses on the different energy consumption rates of electric trucks under empty load, laden load, or separation mode to simulate a more realistic transportation scenario. Accordingly, a route planning and charging decision model for electric tractors is formulated with the objective of minimizing the total operation cost, including the fixed cost, energy cost, and labor cost. To efficiently solve this mathematical model, an adapted Clarke and Wright heuristic algorithm suitable for this problem is designed. We introduce the feasibility check functions for battery state and (un)loading time constraints into the adapted heuristic algorithm. Finally, a series of numerical experiments is conducted in real-world highway networks and transportation scenarios to assess the performance of the algorithm compared with Gurobi and to analyze the practicability of electric tractors for the separation mode under the influence of various objective terms.