Abstract
The study proposes a dynamic proactive predictive cruise control eco-driving (eco-PPCC) framework for controlling the speed of an Autonomous Electric Vehicle (AEV) approaching a signalized intersection in the presence of a preceding vehicle. By utilizing the preceding vehicle's data, the framework optimizes the AEV's speed profile, achieving significant reductions in energy consumption. The study compares the proposed eco-PPCC algorithm to the conventional Gipps and eco-PCC models, and real-world measurements are taken to study practical scenarios. The results show that the proposed framework outperforms conventional methods by significantly reducing unnecessary stops at intersections, speed fluctuations, and energy consumption.
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350344455 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 19th IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Milan, Italy Duration: 24 Oct 2023 → 27 Oct 2023 |
Publication series
| Name | 2023 IEEE Vehicle Power and Propulsion Conference, VPPC 2023 - Proceedings |
|---|
Conference
| Conference | 19th IEEE Vehicle Power and Propulsion Conference, VPPC 2023 |
|---|---|
| Country/Territory | Italy |
| City | Milan |
| Period | 24/10/23 → 27/10/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- autonomous electric vehicles
- Eco-driving
- energy management
- proactive predictive cruise control
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