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 ...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.展开更多
基金funding provided by the U.S.Department of Transportation through the NEXTRANS Center,the USDOT Region 5 University Transportation Center.
文摘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.
