Coordination Group Formation for OnLine Coordinated Routing Mechanisms
Wang Peng, Lili Du

TL;DR
This paper introduces a mathematical and clustering-based approach to form coordination groups for online routing mechanisms, improving computational efficiency and traffic management in urban networks.
Contribution
It develops the ACCA algorithm for effective group formation and proposes the CB-CRM for coordinated routing, addressing computational challenges in large networks.
Findings
ACCA efficiently forms proper coordination groups.
CB-CRM significantly improves computation efficiency.
Parallel computation enhances algorithm performance.
Abstract
This study considers that the collective route choices of travelers en route represent a resolution of their competition on network routes. Well understanding this competition and coordinating their route choices help mitigate urban traffic congestion. Even though existing studies have developed such mechanisms (e.g., the CRM [1]), we still lack the quantitative method to evaluate the coordination penitential and identify proper coordination groups (CG) to implement the CRM. Thus, they hit prohibitive computing difficulty when implemented with many opt-in travelers. Motived by this view, this study develops mathematical approaches to quantify the coordination potential between two and among multiple travelers. Next, we develop the adaptive centroid-based clustering algorithm (ACCA), which splits travelers en route in a local network into CGs, each with proper size and strong…
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Taxonomy
TopicsComplex Network Analysis Techniques · Transportation Planning and Optimization · Plant and animal studies
