Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services

Author:

Maqsood Hussain Shah, Yue Ding, Shaoshu Zhu, Yingqi Gu, Mingming Liu

Keyword:

Computer Science, Artificial Intelligence, Artificial Intelligence (cs.AI)

journal:

date:

2024-03-12 00:00:00

Abstract

In response to the escalating global challenge of increasing emissions and pollution in transportation, shared electric mobility services, encompassing e-cars, e-bikes, and e-scooters, have emerged as a popular strategy. However, existingshared electric mobility services exhibit critical design deficiencies, including insufficient service integration, imprecise energy consumption forecasting, limited scalability and geographical coverage, and a notable absence of a user-centric perspective, particularly in the context of multi-modal transportation. More importantly, there is no consolidated open-source framework which could benefit the e-mobility research community. This paper aims to bridge this gap by providing a pioneering open-source framework for shared e-mobility. The proposed framework, with an agent-in-the-loop approach and modular architecture, is tailored to diverse user preferences and offers enhanced customization. We demonstrate the viability of this framework by solving an integrated multi-modal route-optimization problem using the modified Ant Colony Optimization (ACO) algorithm. The primary contribution of this work is to provide a collaborative and transparent framework to tackle the dynamic challenges in the field of e-mobility research using a consolidated approach.

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