Mult-Objective F,volutionary Traffic Assignment

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Chira, C (Author) Other; Bazzan, ALC (Author) Other; Rosaldo J. F. Rossetti (Author) FEUP

Conference proceedings International

Title: 2015 IEEE 18th International Conference on Intelligent Transportation Systems

Pages: 1177-1182

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 8 Citations

Other information

Authenticus ID: P-00K-160

DOI: 10.1109/itsc.2015.194

Abstract (EN): Existing approaches to traffic assignment focus mainly on approximating the user equilibrium. However, nowadays, with the increasing number of traffic information reaching drivers, traffic authorities have a unique opportunity to try to recommend route choices that arc as much as possible aligned with the system optimum. In this paper, we formulate traffic assignment as a multi-objective optimization problem and engage an evolutionary approach to find route solutions for all users in the network. The aim is to discover a good approximation of an optimal distribution of vehicles to alternative routes between their origin and destination, from the perspective of the overall system, while still considering individual needs. Several multi-objective models are defined for this purpose and integrated in a non dominated sorting genetic algorithm. Computational experiments performed support the ability of the proposed approach to detect efficient route assignments in terms of network performance, while also considering the user perspective.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6