Bi-level multi-objective traffic network optimisation with sustainability perspective


KOLAK O. İ., FEYZİOĞLU O., NOYAN BÜLBÜL N.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.104, ss.294-306, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 104
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.eswa.2018.03.034
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.294-306
  • Anahtar Kelimeler: Traffic network, Multi-objective programming, Bi-level optimisation, Sustainability, Stochastic User Equilibrium, ROAD PRICING MODEL, DESIGN PROBLEM, EQUILIBRIUM, CONGESTION, EQUITY, ALGORITHMS, EMISSION, ACCESSIBILITY, OBJECTIVES, PRINCIPLES
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Recent technological advancements provide a level of mobility never seen before to modern societies. Sustaining today's economy and societies depend on maintaining this mobility. However, this mobility also causes undesirable effects, especially in high urban population areas. Even though, higher priority is given to public transport in metropolitan areas, road network is still an important part of everyday commute and should be planned and managed with great care. In this study, we propose an optimisation methodology that would help the traffic authorities to better predict the results of strategic management decisions in a realistic traffic model. We formulate a bi-level multi-objective traffic optimisation model with a sustainability perspective. The upper level of the proposed model considers the traffic authority's management strategies while the lower level considers the traffic users' decisions. The lower level is modelled using the Stochastic User Equilibrium since it allows more realistic results than the deterministic one. A case study is provided to illustrate the proposed model. The proposed methodology provides an avenue for understanding the trade-offs among conflicting objectives and for designing an environmentally and socially sustainable transportation system. More importantly, it builds the foundation for an intelligent traffic management decision support system. (C) 2018 Elsevier Ltd. All rights reserved.