Integrating efficient routes with station monitoring for electric vehicles in urban environments: simulation and analysis

Abstract

The electrification of road transportation requires the devel opment of an extensive infrastructure of public charging stations (CSs). In order to avoid them contributing to increased traffic congestion and air pollution in a city, it is very important to optimize their deployment. To tackle this challenge, we present microscopic traffic simulations with a hybrid cellular automata and agent-based model to study different strate gies to route electric vehicles (EVs) to CSs, when their battery level is low. EVs and CSs are modeled as agents with capability to demonstrate complex behaviors. Our models take into account the complex nature of traffic and decisions about routes and their predicted behavior. We show that a synthetic city is very useful for investigating the routing behavior and traffic patterns. We have found that a smart routing strategy can contribute to balancing the distribution of EVs among the different CSs in a distributed network, which is the CS layout that produces less traffic congestion. Contrary to our initial expectations, ensuring a balanced dis tribution throughout the city did not necessarily result in an increase in overall productivity. This observation led to a deeper exploration of the nuances of urban transport dynamics. Furthermore, our study empha sizes the superiority of time-based routing over its distance-based coun terpart and highlights the inherent limitations of transportation within acity.