Abstract
This study focuses on scheduling electric connected and autonomous vehicles (CAVs) in platoons on highways, using a tree-like network that includes charging stations with limited capacity. The aim is to reduce overall energy consumption and travel time while meeting vehicle deadlines and charging capacities. The problem can be formulated by an MILP, however, this is only feasible for small instances. To reduce the size of the MILP, we propose to select possible platoon members and leaders based on a heuristic that takes into account the specific characteristics of the vehicles. Our numerical experiments indicate that this heuristic is 36 times faster than the original MILP.
| Original language | English |
|---|---|
| Pages (from-to) | 1347-1356 |
| Number of pages | 10 |
| Journal | Proceedings of International Conference on Computers and Industrial Engineering, CIE |
| Volume | 2024-December |
| Publication status | Published - 2024 |
| Event | 51st International Conference on Computers and Industrial Engineering, CIE 2024 - Sydney, Australia Duration: Dec 9 2024 → Dec 11 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- charging capacity
- coordinated vehicles
- heuristic
- platooning
- scheduling
- scoring
ASJC Scopus subject areas
- General Computer Science
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering
- Safety, Risk, Reliability and Quality
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