  Due to the limited driving range, inadequate charging facilities, and
time-consuming recharging, the process of finding an optimal charging route for
electric vehicles (EVs) differs from that of other vehicle types. The time and
location of EV charging during a trip impact not only the individual EV's
travel time but also the travel time of other EVs, due to the queuing that may
arise at the charging station(s). This issue is at large seen as a significant
constraint for uplifting EV sales in many countries. In this study, we present
a novel Electric Vehicle Route Planning problem, which involves finding the
fastest route with recharging for an EV routing request. We model the problem
as a new graph problem and present that the problem is NP-hard. We propose a
novel two-phase algorithm to traverse the graph to find the best possible
charging route for each EV. We also introduce the notion of `influence factor'
to propose heuristics to find the best possible route for an EV with the
minimum travel time that avoids using charging stations and time to recharge at
those stations which can lead to better travel time for other EVs. The results
show that our method can decrease total travel time of the EVs by 50\% in
comparison with the state-of-the-art on a real dataset, where the benefit of
our approach is more significant as the number of EVs on the road increases.
