Computing and Analyzing Mixed Equilibrium Network Flows with Gasoline and Electric Vehicles

This article formulates, solves and evaluates a special network equilibrium problem with mode and route choices. The two transportation modes (or vehicle types) included in this problem are gasoline vehicles (GVs) and battery electric vehicles (BEVs) which are distinguished from each other in terms of driving distance limit and travel cost composition. In view of the advantages (e.g., low fuel expenses and vehicle emissions) and disadvantages (e.g., limited driving range and long charging time) pertaining to driving electric vehicles, it is anticipated that a large number of households/motorists may prefer to own both gasoline and electric vehicles. The purpose of this article is to offer a traffic equilibrium modeling tool for networks that serve households/motorists who can choose between gasoline and electric vehicles. A convex optimization model is proposed for characterizing such mixed equilibrium traffic networks with both gasoline and electric vehicles. The authors implemented and evaluated two competing solution algorithms, a linear approximation algorithm of the Jacobi type and a quadratic approximation algorithm that takes the form of the Gauss–Seidel decomposition. Experimental results clearly show that, from the model behavior perspective, the produced network flow patterns replicate the anticipated combined mode-route choice results and this means that the higher the distance limit or the gasoline price is, the more travelers choose BEVs when both BEVs and GVs are available to them.


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  • Accession Number: 01539033
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 14 2014 4:32PM