Modelling Electrical Car Diffusion Based on Agents

TL;DR

This paper presents an agent-based simulation model to analyze how various government policies and incentives influence the adoption of electric vehicles, demonstrated through a case study at the University of Nottingham.

Contribution

It introduces a novel agent-based model for simulating electric vehicle diffusion and evaluates policy impacts, aiding decision-making for promoting zero-emission transport.

Findings

Higher parking charges reduce electric vehicle adoption.

Incentives like lower prices increase uptake.

Agent-based modeling effectively assesses policy impacts.

Abstract

Replacing traditional fossil fuel vehicles with innovative zero-emission vehicles for the transport in ci ties is one of the major tactics to achieve the UK government 2020 target of cutting emission. We are developing an agent-based simulation model to study the possible impact of different governmental interventions on the diffusion of such vehicles. Options that could be studied with our what-if analysis to include things like car parking charges, price of electrical car, energy awareness and word of mouth. In this paper we present a first case study related to the introduction of a new car park charging scheme at the University of Nottingham. We have developed an agent based model to simulate theimpact of different car parking rates and other incentives on the uptake of electrical cars. The goal of this case study is to demonstrate the usefulness of agent-based modelling and simulation for such investigations.