A Quantitative and Systematic Methodology to Investigate Energy Consumption Issues in Multimodal Intercity Transportation Systems

Energy issues in transportation systems have garnered increasing attention recently. This study proposes a systematic methodology for policy-makers to minimize energy consumption in multimodal intercity transportation systems considering suppliers’ operational constraints and travelers’ mobility requirements. A bi-level optimization model is developed for this purpose and considers the air, rail, private auto, and transit modes. The upper-level model is a mixed integer nonlinear program aiming to minimize energy consumption subject to transportation suppliers’ operational constraints and traffic demand distribution to paths resulting from the lower-level model. The lower-level model is a linear program seeking to maximize the trip utilities of travelers. The interactions between the multimodal transportation suppliers and intercity traffic demand are considered under the goal of minimizing system energy consumption. The proposed bi-level mixed integer model is relaxed and transformed into a mathematical program with complementarity constraints, and solved using a customized branch-and-bound algorithm. Numerical experiments, conducted using multimodal travel options between Lafayette, Indiana and Washington, D.C. reiterate that shifting traffic demand from private cars to the transit and rail modes significantly reduce energy consumption. Moreover, the proposed methodology provides tools to quantitatively analyze system energy consumption and traffic demand distribution among transportation modes under specific policy instruments. The results illustrate the need to systematically incorporate the interactions among traveler preferences, network structure, and supplier operational schemes to provide policy-makers insights for developing traffic demand shift mechanisms to minimize system energy consumption. Hence, the proposed methodology provide policy-makers the capability to analyze energy consumption in the transportation sector by a holistic approach.

[1]  Anna Nagurney,et al.  A multimodal traffic network equilibrium model with emission pollution permits: compliance vs noncompliance , 1998 .

[2]  Todd Litman,et al.  Introduction to Multi-Modal Transportation Planning , 2014 .

[3]  Board on Energy,et al.  Assessment of Fuel Economy Technologies for Light-Duty Vehicles , 2011 .

[4]  Martin Wachs,et al.  A test of inter-modal performance measures for transit investment decisions , 2000 .

[5]  Patrice Marcotte,et al.  An overview of bilevel optimization , 2007, Ann. Oper. Res..

[6]  P. Poudenx The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation , 2008 .

[7]  EVALUATING TRANSIT SUBSIDIES IN CHICAGO , 1997 .

[8]  W. Y. Szeto,et al.  A Sustainable Road Network Design Problem with Land Use Transportation Interaction over Time , 2015 .

[9]  Christodoulos A. Floudas,et al.  Global optimization of mixed-integer bilevel programming problems , 2005, Comput. Manag. Sci..

[10]  I. Savage The dynamics of fare and frequency choice in urban transit , 2010 .

[11]  J. Kenworthy Energy Use and CO2 Production in the Urban Passenger Transport Systems of 84 International Cities: Findings and Policy Implications , 2008 .

[12]  E. Frankel,et al.  NEW TRB SPECIAL REPORT: Policy Options for Reducing Energy Use and Greenhouse Gas Emissions from U.S. Transportation , 2011 .

[13]  William P. Nowak,et al.  The cross elasticity between gasoline prices and transit use: Evidence from Chicago , 2013 .

[14]  Robert G. Jeroslow,et al.  The polynomial hierarchy and a simple model for competitive analysis , 1985, Math. Program..

[15]  Frank S. Koppelman MULTIDIMENSIONAL MODEL SYSTEM FOR INTERCITY TRAVEL CHOICE BEHAVIOR , 1989 .

[16]  Hjp Harry Timmermans,et al.  Incorporating Variety Seeking and Seasonality in Stated Preference Modeling of Leisure Trip Destination Choice: Test of External Validity , 2002 .

[17]  Christopher R. Knittel,et al.  Reducing Petroleum Consumption from Transportation , 2012 .

[18]  Todd Litman,et al.  Understanding Transport Demands and Elasticities: How Prices and Other Factors Affect Travel Behavior , 2012 .

[19]  Ming Zhong,et al.  Modeling the congestion cost and vehicle emission within multimodal traffic network under the condition of equilibrium , 2012 .

[20]  Donald W. Hearn,et al.  Congestion Pricing for Multi-Modal Transportation Systems , 2007 .

[21]  K. Garbade,et al.  Fare policies for mass transit deficit control: Analysis by optimization , 1976 .

[22]  P. Rickwood,et al.  Urban Structure and Energy—A Review , 2008 .

[23]  Jean-Paul Rodrigue,et al.  Incorporating Energy-Based Metrics in the Analysis of Intermodal Transport Systems in North America , 2011 .

[25]  Alberto Mendoza,et al.  Applications of Economic Value of Freight Flows to Transport Planning , 1996 .

[26]  Jonathan F. Bard,et al.  The Mixed Integer Linear Bilevel Programming Problem , 1990, Oper. Res..

[27]  Georgia Aifadopoulou,et al.  Multiobjective Optimum Path Algorithm for Passenger Pretrip Planning in Multimodal Transportation Networks , 2007 .

[28]  Lizhi Wang,et al.  Renewable Portfolio Standards in the Presence of Green Consumers and Emissions Trading , 2013 .

[29]  L. N. Vicente,et al.  Descent approaches for quadratic bilevel programming , 1994 .