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

Energy issues in transportation systems have garnered increasing attention in recent years in both the public and private sectors. This study proposes a systematic methodology for policy-makers to improve energy consumption efficiency 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 that aims to minimize energy consumption subject to transportation suppliers’ operational constraints and the traffic demand distribution to paths resulting from the lower level model. The lower level model is a linear program that seeks to maximize the intercity trip utilities of travelers. The interactions between the multimodal transportation suppliers and intercity traffic demand are considered under the goal of minimizing energy consumption at the system level. The proposed bilevel mixed integer nonlinear model is relaxed and transformed into a mathematical program with complimentarity 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 can significantly reduce energy consumption. More importantly, the proposed methodology is able to provide quantitative analyses for system energy consumption and traffic demand distribution among transportation modes under specific policy instruments. The results also illustrate the need to systematically incorporate the interactions between 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 can provide policy-makers the ability to analyze energy consumption in the transportation sector under different policy instruments. TRB 2014 Annual Meeting Original paper submittal not revised by author Lili Du, Srinivas Peeta, Peng Wei, Dengfeng Sun 3 A Quantitative and Systematic Methodology to Investigate Energy Consumption in Multimodal Transportation Systems BACKGROUND AND MOTIVATION The current transportation system relies heavily on non-renewable fuel energy. It accounts for 71 percent of the nation’s petroleum use and 30 percent of U.S. greenhouse gas emissions (1, 2). These statistics suggest that reducing the energy consumption in the transportation sector can significantly enhance national energy security and help control greenhouse gas emissions. However, the current transportation system is central to the U.S. societal mobility and commerce and cannot be easily or quickly altered. Therefore, improving the transportation system energy consumption efficiency without sacrificing mobility needs disproportionately is a key imperative, and motivates the current study. The total energy consumption of the current transportation system is a function of the fuel efficiency of the transportation modes and the intensity of transportation mode usage. Therefore, a natural solution strategy to consider so as to save energy is to develop fuel-efficient vehicles. However, relevant studies (3) suggest otherwise as the improvements resulting from fuel-efficient vehicles have been offset by the higher usage of larger luxury cars and SUVs by travelers. Instead, this study focuses on the commonlyaddressed demand-side strategy of shifting traffic demand from low fuel efficiency modes to high fuel efficiency modes. Empirical data indicates that cars and light trucks used for personal travel alone account for the majority of fuel consumption in the transportation sector (2). The fuel efficiency of transportation modes (per passenger per gallon) degrades in the order of rail, road, and air modes (4). Hence, to reduce energy consumption in current transporting systems, the primary focus is on shifting the passenger traffic demand in cars, light-duty trucks, and air to high fuel efficiency and/or high occupancy modes such as rail and public transit. This raises the key question of how to foster such a traffic demand shift. Strategic policies which influence transportation supplier actions as well as traffic mode choices represent a promising solution paradigm to realize the demand shift from low fuel efficiency modes to higher efficiency ones. Thereby, the three key players including the travelers (who form the traffic demand), transportation suppliers (who provide the traffic supply options), and policy-makers (who design and implement policy instruments), work independently in the short-term, but interactively in long-term to address energy consumption of transportation sector. For example, transportation suppliers, who provide vehicles, fuel and traffic infrastructure, and operate transportation modes and serve commercial freight and passenger, typically focus on profits. Their decisions and actions are significantly impacted by policy instruments such as tax, subsidy, mandatory policies, etc. By contrast, travelers will choose intermodal/multimodal paths based on their preferences and level of service attributes of the modes (such as frequency, fare, travel time, and waiting time) provided by transportation suppliers. The mode choices of the travelers will eventually impact the operational decisions of transportation suppliers. Therefore, the interactions among the three players as well as their operational/behavior characteristics need to be considered so that a successful policy instrument can be implemented. The conceptual perspectives discussed heretofore are well-recognized. The key gap to successfully implement a policy instrument is the need for a systematic tool to predict the traffic demand shift, the energy consumption reduction, and the actions on transportation suppliers, so that the effects of a designed policy instrument can be holistically captured. However, as identified in the literature review in the next section, most existing studies only provide conceptual suggestions based on historical trends but cannot characterize these effects quantitatively. To address this gap, the proposed study proposes mathematical models to predict the energy consumption effects resulting from traffic demand shift and traffic supply operational actions, which are triggered by the implementation of certain policy instruments. Intercity multimodal transportation networks that include the private car, transit, rail, and air modes are considered in this context. Traveler preferences, transportation supplier operational constraints as well as the interactions among traffic demand, suppliers and policy-makers will be considered in the modeling process. The associated solutions can provide policy-makers in both the transportation and energy TRB 2014 Annual Meeting Original paper submittal not revised by author Lili Du, Srinivas Peeta, Peng Wei, Dengfeng Sun 4 consumption sectors insights so that strategic policy instruments can be designed to realize traffic demand shifts and achieve system energy savings in the long-term. The rest of the paper is organized as the follows. The next section reviews the past literature in this domain. Then, preliminaries including definitions, assumptions, and notations are provided. The mathematical model and its solution methodology are described. Next, numerical experiments and the associated insights are discussed. The paper concludes with some comments and insights related to the problem context.