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Author: Jong-Geun Kim
Publisher:
ISBN: 9781124368726
Category : Alternative fuel vehicles
Languages : en
Pages : 192
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Book Description
Concerns about Peak Oil, political instability in the Middle East, health hazards, and greenhouse gas emissions of fossil fuels have stimulated interests in alternative fuels such as biofuels, natural gas, electricity, and hydrogen. Alternative fuels are expected to play an important role in a transition to a sustainable transportation system. One of the major barriers to the success of alternative-fuel vehicles (AFV) is the lack of infrastructure for producing, distributing, and delivering alternative fuels. Efficient methods that locate alternative-fuel refueling stations are essential in accelerating the advent of a new energy economy. The objectives of this research are to develop a location model and a Spatial Decision Support System (SDSS) that aims to support the decision of developing initial alternative-fuel stations. The main focus of this research is the development of a location model for siting alt-fuel refueling stations considering not only the limited driving range of AFVs but also the necessary deviations that drivers are likely to make from their shortest paths in order to refuel their AFVs when the refueling station network is sparse. To add reality and applicability of the model, the research is extended to include the development of efficient heuristic algorithms, the development of a method to incorporate AFV demand estimates into OD flow volumes, and the development of a prototype SDSS. The model and methods are tested on real-world road network data from state of Florida. The Deviation-Flow Refueling Location Model (DFRLM) locates facilities to maximize the total flows refueled on deviation paths. The flow volume is assumed to be decreasing as the deviation increases. Test results indicate that the specification of the maximum allowable deviation and specific deviation penalty functional form do have a measurable effect on the optimal locations of facilities and objective function values as well. The heuristics (greedy-adding and greedy-adding with substitution) developed here have been identified efficient in solving the DFRLM while AFV demand has a minor effect on the optimal facility locations. The prototype SDSS identifies strategic station locations by providing flexibility in combining various AFV demand scenarios. This research contributes to the literature by enhancing flow-based location models for locating alternative-fuel stations in four dimensions: (1) drivers' deviations from their shortest paths, (2) efficient solution approaches for the deviation problem, (3) incorporation of geographically uneven alt-fuel vehicle demand estimates into path-based origin-destination flow data, and (4) integration into an SDSS to help decision makers by providing solutions and insights into developing alt-fuel stations.
Author: Jong-Geun Kim
Publisher:
ISBN: 9781124368726
Category : Alternative fuel vehicles
Languages : en
Pages : 192
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Book Description
Concerns about Peak Oil, political instability in the Middle East, health hazards, and greenhouse gas emissions of fossil fuels have stimulated interests in alternative fuels such as biofuels, natural gas, electricity, and hydrogen. Alternative fuels are expected to play an important role in a transition to a sustainable transportation system. One of the major barriers to the success of alternative-fuel vehicles (AFV) is the lack of infrastructure for producing, distributing, and delivering alternative fuels. Efficient methods that locate alternative-fuel refueling stations are essential in accelerating the advent of a new energy economy. The objectives of this research are to develop a location model and a Spatial Decision Support System (SDSS) that aims to support the decision of developing initial alternative-fuel stations. The main focus of this research is the development of a location model for siting alt-fuel refueling stations considering not only the limited driving range of AFVs but also the necessary deviations that drivers are likely to make from their shortest paths in order to refuel their AFVs when the refueling station network is sparse. To add reality and applicability of the model, the research is extended to include the development of efficient heuristic algorithms, the development of a method to incorporate AFV demand estimates into OD flow volumes, and the development of a prototype SDSS. The model and methods are tested on real-world road network data from state of Florida. The Deviation-Flow Refueling Location Model (DFRLM) locates facilities to maximize the total flows refueled on deviation paths. The flow volume is assumed to be decreasing as the deviation increases. Test results indicate that the specification of the maximum allowable deviation and specific deviation penalty functional form do have a measurable effect on the optimal locations of facilities and objective function values as well. The heuristics (greedy-adding and greedy-adding with substitution) developed here have been identified efficient in solving the DFRLM while AFV demand has a minor effect on the optimal facility locations. The prototype SDSS identifies strategic station locations by providing flexibility in combining various AFV demand scenarios. This research contributes to the literature by enhancing flow-based location models for locating alternative-fuel stations in four dimensions: (1) drivers' deviations from their shortest paths, (2) efficient solution approaches for the deviation problem, (3) incorporation of geographically uneven alt-fuel vehicle demand estimates into path-based origin-destination flow data, and (4) integration into an SDSS to help decision makers by providing solutions and insights into developing alt-fuel stations.
Author: Sang Kweon
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Burning conventional fossil fuels including gasoline and diesel mainly results in over 90% of greenhouse gas emissions from transportation. To reduce these emissions from the ground transportation sector, the use of alternative-fuel vehicles is being spotlighted. As a result, refueling station location problems for alternative-fuel vehicles have received attention as well. These refueling station location problems can be classified into two types depending on the set of candidate sites: when a preliminary (finite) set of candidate sites is given, this problem is called discrete; when the stations can be located anywhere along the network, the problem is called continuous. This dissertation considers one discrete and two continuous location problems for alternative-fuel refueling stations on transportation networks. First, the discrete location problem is addressed with two conflicting objectives of maximizing the total vehicle-miles traveled per time unit covered by the stations and minimizing the capital cost for constructing the refueling infrastructure. Two versions of bi-criteria binary linear programming models are proposed and validated with an application to the Pennsylvania Turnpike System regarding the location of liquefied natural gas refueling stations on existing service plazas. Next, assuming that a vehicle cannot deviate from the preplanned path, the continuous location problem for a single refueling station is addressed on a tree network with the objective of maximizing the traffic flow (in round trips per time unit) covered by the station. Two reduction properties regarding the problem size and some optimality conditions are derived. Then, an exact polynomial algorithm is developed to determine the set of optimal locations for the refueling station. Lastly, the continuous location problem introduced above is extended to a version where a given portion of drivers are willing to deviate to be able to refuel if the station is not located along their preplanned routes. Optimality properties and exact polynomial algorithms are suggested to determine the deviation options and find the set of optimal station locations that maximizes the traffic flow (in round trips per time unit) covered by the station.
Author: Shuyao Hong
Publisher:
ISBN:
Category : Alternative fuel vehicles
Languages : en
Pages : 66
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Book Description
In order to address concerns about the dominance of petroleum-fueled vehicles, the transition to alternative-fueled counterparts is urgently needed. Top barriers preventing the widespread diffusion of alternative-fuel vehicles (AFV) are the limited range and the scarcity of refueling or recharging infrastructures in convenient locations. Researchers have been developing models for optimally locating refueling facilities for range-limited vehicles, and recently a strategy has emerged to cluster refueling stations to encourage consumers to purchase alternative-fuel vehicles by building a critical mass of stations. However, clustering approaches have not yet been developed based on flow-based demand. This study proposes a Threshold Coverage extension to the original Flow Refueling Location Model (FRLM). The new model optimally locates p refueling stations on a network so as to maximize the weighted number of origin zones whose refuelable outbound round trips exceed a given threshold, thus to build critical mass based on flow-based demand on the network. Unlike other clustering approaches, this model can explicitly ensure that flow demands "covered" in the model are refuelable considering the limited driving range of AFVs. Despite not explicitly including local intra-zonal trips, numerical experiments on a statewide highway network proved the effectiveness of the model in clustering stations based on inter-city flow volumes on the network. The models policy implementation will provide managerial insights for some key concerns of the industry, such as geographic equity vs. critical mass, from a new perspective. This project will serve as a step to support a more successful public transition to alternative-fuel vehicles.
Author: Seong wook Hwang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Scott Kelley
Publisher:
ISBN:
Category : Alternative fuel vehicles
Languages : en
Pages : 142
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Book Description
Alternative fuel vehicles (AFVs) have seen increased attention as a way to reduce reliance on petroleum for transportation, but adoption rates lag behind conventional vehicles. One crucial barrier to their proliferation is the lack of a convenient refueling infrastructure, and there is not a consensus on how to locate initial stations. Some approaches recommend placing stations near where early adopters live. An alternate group of methods places stations along busy travel routes that drivers from across the metropolitan area traverse each day. To assess which theoretical approach is most appropriate, drivers of compressed natural gas (CNG) vehicles in Southern California were surveyed at stations while they refueled. Through GIS analysis, results demonstrate that respondents refueled on the way between their origins and destinations ten times more often than they refueled near their home, when no station satisfied both criteria. Freeway interchanges, which carry high daily passing traffic volumes in metropolitan areas, can be appropriate locations for initial stations based on these results. Stations cannot actually be built directly at these interchange sites, so suitable locations on nearby street networks must be chosen. A network GIS method is developed to assess street network locations' ability to capture all traffic passing through 72 interchanges in greater Los Angeles, using deviation from a driver's shortest path as the metric to assess a candidate site's suitability. There is variation in the ability of these locations to capture passing traffic both within and across interchanges, but only 7% of sites near interchanges can conveniently capture all travel directions passing through the interchange, indicating that an ad hoc station location strategy is unlikely to succeed. Surveys were then conducted at CNG stations near freeway interchanges to assess how drivers perceive and access refueling stations in these environments. Through comparative analysis of drivers' perceptions of stations, consideration of their choice sets, and the observed frequency of the use of a freeway to both access and leave these stations, results indicate that initial AFV stations near freeway interchanges can play an important role in regional AFV infrastructure.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 104
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Book Description
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Author: James M. Anderson
Publisher: Rand Corporation
ISBN: 0833084372
Category : Transportation
Languages : en
Pages : 215
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Book Description
The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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Book Description
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Author:
Publisher:
ISBN:
Category : Automobiles
Languages : en
Pages : 128
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Book Description
