Summary of Optimal Design and Implementation Of An Open-source Emulation Platform For User-centric Shared E-mobility Services, by Maqsood Hussain Shah et al.
Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services
by Maqsood Hussain Shah, Yue Ding, Shaoshu Zhu, Yingqi Gu, Mingming Liu
First submitted to arxiv on: 12 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a comprehensive open-source platform for shared electric mobility services, aiming to address the existing design deficiencies in this field. The proposed platform is tailored to diverse user preferences and offers enhanced customization through an agent-in-the-loop approach and modular architecture. To demonstrate its viability, the authors provide a comprehensive analysis of integrated multi-modal route-optimization in various scenarios using modified Ant Colony Optimization (ACO) and Q-Learning algorithms. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The proposed platform can help reduce transportation emissions and pollution by providing users with optimized routes that consider energy availability, user preferences, and E-mobility tools placement. The authors demonstrate the effectiveness of their approach through experiments, showing that Q-learning achieves better performance in terms of travel time cost compared to MMEC-ACO for different scenarios. |
Keywords
» Artificial intelligence » Multi modal » Optimization
