Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Arslan, Okan; Yıldız, Barış; Karaşan, Oya Ekin

doi:10.1016/j.enpol.2014.08.015

Cited by 29 publications

(15 citation statements)

References 39 publications

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“…Characteristics of network topologies considered in this study are detailed in Table 2. CA is a real-world representation of the California road network with 339 nodes and 1,234 arcs, as shown in Figure 2 (Arslan et al 2014). The nodes of the network represent road intersections or urban population centers.…”

Section: Computational Studymentioning

confidence: 99%

A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing

Arslan

Karaşan

Mahjoub

et al. 2019

Transportation Science

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Because of the limited range of alternative fuel vehicles (AFVs) and the sparsity of the available alternative refueling stations (AFSs), AFV drivers cooperatively deviate from their paths to refuel. This deviation is bounded by the drivers' tolerance. Taking this behavior into account, the refueling station location problem with routing (RSLP-R) is defined as maximizing the AFV flow that can be accommodated in a road network by locating a given number of AFSs while respecting the range limitation of the vehicles and the deviation tolerance of the drivers. In this study, we develop a natural model for the RSLP-R based on the notion of length-bounded cuts, analyze the polyhedral properties of this model, and develop a branch-and-cut algorithm as an exact solution approach. Extensive computational experiments show that the algorithm significantly improves the solution times with respect to previously developed exact solution methods and extends the size of the instances solved to optimality. Using our methodology, we investigate the tradeoffs between covered vehicle flow and deviation tolerance of the drivers and present insights on deviation characteristics of drivers in a case study in California.

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Section: Computational Studymentioning

confidence: 99%

A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing

Arslan

Karaşan

Mahjoub

et al. 2019

Transportation Science

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“…2 (Simchi- Levi & Berman, 1988) and California (CA) road network in Fig. 3 (Arslan et al, 2014a). We implemented all the algorithms using Java under Linux and CPLEX 12.5 and all experiments are done on the same machine: AMD Opteron(tm) Processor 6282 SE with 2GB RAM.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…However, there are very few studies in the refueling station location literature that incorporate the driver preferences into the location decisions. The effects of driver preferences such as deviating from the shortest paths is a significant factor on travel costs (Arslan, Yıldız, & Kara¸san, 2014a). In this context, Kim and Kuby (2012) study simple-path deviations (i.e.…”

Section: Introductionmentioning

confidence: 99%

A branch and price approach for routing and refueling station location model

Yıldız

Arslan

Karaşan

2016

European Journal of Operational Research

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a b s t r a c tThe deviation flow refueling location problem is to locate p refueling stations in order to maximize the flow volume that can be refueled respecting the range limitations of the alternative fuel vehicles and the shortest path deviation tolerances of the drivers. We first provide an enhanced compact model based on a combination of existing models in the literature for this relatively new operations research problem. We then extend this problem and introduce the refueling station location problem which adds the routing aspect of the individual drivers. Our proposed branch and price algorithm relaxes the simple path assumption generally adopted in the existing studies and implicitly takes into account deviation tolerances without the pregeneration of the routes. Therefore, the decrease in solution times with respect to existing models is significant and our algorithm scales very efficiently to more realistic network dimensions.

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“…Arslan et al (2014) found that 2.5% of AFV drivers prefer to refuel on travel paths that were not the shortest travel path, and that deviation tolerance is higher when refueling networks are sparser. Lines et al (2008) also finds stated evidence for this willingness to deviate, noting that early adopters would go a mile out of their way in order to access a hydrogen refueling station.…”

Section: Introductionmentioning

confidence: 96%

AFV refueling stations and the complexity of freeway intersections: the scale dependency of network representation

Kelley

2016

International Journal of Geographical Information Science

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As interest for alternative fuel vehicles (AFVs) in urban areas continues to build, there has been a corresponding focus on the development of methods that can locate initial refueling stations on regional transportation networks in an optimal manner. Recent studies suggest that the behavior of early adopters of AFVs is consistent with the objectives of flow-capturing station location models. One outstanding issue with the further use of these models to locate AFV stations is the relationship between the relatively coarse geographic representation of regional transportation networks used in flow-capturing models and the complexity of the sites they recommend, which are often nodes that represent freeway intersections. Since AFV refueling stations cannot be built directly at freeway intersections, a network GIS method entitled the freeway traffic capture metric (FTCM) is developed to identify locations on proximate local street networks that can effectively capture all traffic passing through a freeway intersection. The FTCM considers deviation from a shortest travel path specifically through a freeway intersection as its metric of convenience for all possible travel routes that pass through it, computing a score for each candidate site on the nearby local street network. The FTCM is tested on nearly 45,000 candidate sites within one mile of 72 freeway intersections in greater Los Angeles, California. Locations that can capture all traffic passing through the nearby freeway intersection are shown to generally be near the intersection's center, but not necessarily next to freeway entrances or exits. In total, 6.7% of possible station locations near these 72 freeway intersections are convenient for all traffic passing through them, and 22 out of the 72 freeway intersections lack such a site altogether. This indicates that there is high likelihood of inconsistency between regional modeling results and station location effectiveness if this scale dependency between coarse representations of transportation networks and the complexity of local street networks near freeway intersections is not considered when building initial AFV stations near these locations. ARTICLE HISTORY

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Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Cited by 29 publications

References 39 publications

A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing

A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing

A branch and price approach for routing and refueling station location model

AFV refueling stations and the complexity of freeway intersections: the scale dependency of network representation

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