Citation

Peng W, Du L. Transp. Res. C Emerg. Technol. 2021; 128: e103113.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trc.2021.103113

PMID

unavailable

Abstract

It has been well known that properly coordinating travelers' route choices will help mitigate urban traffic congestion. Accordingly, coordinated routing mechanisms (CRMs), functioned as coordinated network congestion management schemes, have been developed in recent years. They often employ game theory models to strategically coordinate the route decisions of a group of travelers en route with the aim to reduce network traffic congestion. However, existing studies do not provide the solution about how to form the traveler groups, such as who and how many travelers the CRMs should involve. This issue may jeopardize the efficiency and scalability of the CRMs in practical applications. To make up this gap, this study seeks to develop the clustering aided network modeling approaches to form the coordination groups (CGs), which have the proper members and sizes for supporting the merits of the congestion management schemes. Specifically, we define coordination potential as an index to indicate the potential benefit for coordinating travelers' route decisions on network congestion reduction. Then we develop rigorous approaches to understand the mathematical features and further quantify the coordination potential between two travelers, and among multiple travelers. Built upon that, we form the CGs through a well-designed adaptive centroid-based clustering algorithm (ACCA). It secures a local optimal clustering solution, balancing the intra-cluster and inter-cluster CP, so that we can ensure a small system performance loss as we implement a CRM on each CG. The efficiency of the CG formation approach is evaluated by the CG-CRM scheme, which partitions the travelers into multiple CGs and independently coordinates the travelers' route choices in each CG by a CRM. The numerical experiments built upon both Sioux Falls and Hardee city networks confirm the efficiency and effectiveness of the CG formation approach. Mainly, the CG-CRM outperforms the independent best response routing mechanism in system performance. As compared to the CRM working on a single group involving all travelers, the CG-CRM requires significantly less computation load with a minor compromise on the system performance. This merit becomes more apparent under high penetration and congested traffic condition. Therefore, we claim that the CG formation approach will significantly help the implementation of the coordinated congestion mitigation schemes in practice.

Language: en

Keywords

Clustering; Coordinated online in-vehicle routing; Coordination potential