Infrastructure development for alternative fuel vehicles on a transportation network
- Hwang, Seong wook
- [University Park, Pennsylvania] : Pennsylvania State University, 2016.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Ventura, Jose A.
- etda.libraries.psu.edu , Connect to this object online.
- Restrictions on Access:
- Open Access.
- Due to global concerns regarding environmental and economic sustainability in ground logistics, recent research has paid considerable attention to the commercialization of alternative fuel (AF) vehicles that help reduce greenhouse gas emissions. Nevertheless, logistics companies are reluctant to replace their long-distance trucks with AF trucks because their supply chain routes have an insufficient level of AF infrastructure coverage. Employing AF vehicles in the transportation sector requires an initial AF infrastructure, which would involve constructing refueling stations in optimal locations to cover the maximum traffic flows on a given road network. To achieve the goal, this research proposes rigorous mathematical models and algorithms for optimal positioning of AF refueling stations on directed transportation networks such as highways, toll roads, and expressways. In the first problem, we propose a new mathematical model that locates AF refueling stations on a directed transportation network that has two types of candidate sites for AF refueling stations: (1) single-access sites which are accessible from only one driving direction, and (2) dual-access sites which are accessible from both driving directions. The existing literature on path-based demand models to locate AF refueling stations does not consider these directional candidate sites on a transportation network. Note that highway systems, which play an important role in the exchange of goods, have directed candidate sites for AF refueling stations. In this respect, we present a 0-1 linear programming model that locates AF refueling stations on a directed transportation network with the objective of maximizing the coverage of traffic flows. Then, we apply the proposed model to the Pennsylvania Turnpike considering the 2011 medium- and heavy-duty truck traffic data with different vehicle driving ranges. Two greedy algorithms are also provided and implemented to find the best sequence to set up the AF refueling stations for the selected sites. In the second problem, we design a new mathematical model for locating AF refueling stations when vehicles have different driving ranges and fuel remaining in a tank at their origins and destinations (ODs). The existing literature generally assumes that vehicles are capable of traveling the same driving range and have similar fuel tank levels at their ODs. We relax these assumptions and introduce a multi-class vehicle transportation network which is defined as a transportation network with the variations of vehicles driving ranges and different fuel tank levels at their ODs. A 0-1 linear programming model is proposed to locate a given number of refueling stations that maximize the total traffic flow covered (in round trips per time unit) by the stations on the network. Through numerical experiments with the 2011 medium- and heavy-duty truck traffic data in the Pennsylvania Turnpike, we identify the optimal sets of refueling stations for AF trucks on a multi-class vehicle transportation network. In the third problem, we consider that vehicles are able to make detours from pre-planned paths if there are no available AF refueling stations on the paths. This problem is essential to be considered for AF trucks on highway systems when an AF refueling infrastructure is not fully developed yet in their supply chain routes. That is, alternative paths with the AF refueling availability can be considered to include drivers routes even though AF truck drivers need to deviate from pre-planned paths. In this respect, we first propose an algorithm to generate alternative paths that drivers are willing to select for their routes between ODs. Then, a 0-1 linear programming model is presented to locate AF refueling stations at candidate sites on a network by maximizing the coverage of traffic flows along multiple paths. We test our model with the algorithm on a classical 25-node network with 25 candidate sites through various scenarios that include different numbers of paths, deviation factors, and limited driving ranges.
- Other Subject(s):
- Dissertation Note:
- Ph.D. Pennsylvania State University 2016.
- Reproduction Note:
- Microfilm (positive). 1 reel ; 35 mm. (University Microfilms 13819206)
- Technical Details:
- The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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