Abstract
Our research is developing flexible strategies for forming and routing future platoons of automated urban logistics vehicles. We propose the notion of compensational platooning using automated negotiation between agents representing vehicles. After the vehicles reach the end of a common route, an agent can propose part of its route along with a monetary value to platoon partners for further together-travel. If negotiation is successful, a new platoon is formed and follows the proposed route. If the compensation is too small or the route proposed oversteps the agent's limitations, the offer is rejected and the vehicles continue their travel separately. A contribution of this paper is a negotiation strategy that proposes compensation based on beliefs of what the opponent's payment threshold would be. In doing so, the bid with the highest acceptance likelihood is calculated, keeping negotiations short and effective. Our model is tested on a synthetic network and a real urban example. We show that by using negotiation, vehicles can identify mutually beneficial new routes that a centralised/distributed approach would not find, with utility improvements of up to 8%.
Original language | English |
---|---|
Title of host publication | PRIMA 2020: Principles and Practice of Multi-Agent Systems |
Editors | Takahiro Uchiya, Quan Bai, Iván Marsá Maestre |
Place of Publication | Cham |
Publisher | Springer |
Pages | 317-324 |
Number of pages | 8 |
ISBN (Print) | 978-3-030-69322-0 |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 12568 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Bibliographical note
Publisher Copyright:© 2021, Springer Nature Switzerland AG.
Keywords
- Automated negotiation
- Decentralised agent coordination
- Opponent modelling
- Platoon matching