Identifying Feasible Locations for Rail Transit Stations

Samanta, Sutapa; Jha, M. K.

doi:10.3141/2063-10

Cited by 24 publications

(11 citation statements)

References 13 publications

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“…For urban planners, promoting the local housing market is usually a major target, and building a subway system is thought to be one efficient option [72,73]. However, our findings display a contrary picture.…”

Section: Policy Implicationscontrasting

confidence: 65%

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

et al. 2019

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Using housing market data of Beijing and Hangzhou, China, we conduct a case study to detect how the difference of urban structure can affect the relationship between the subway system and housing prices. To quantify the characteristics of urban structure, we propose a constrained clustering method, which can not only reveal the spatial heterogeneity of the housing market, but also provides a link between heterogeneity and the underlying urban structure. Applying constrained clustering to Beijing and Hangzhou, we find that the relationship between accessibility to metro stations and housing prices is weak and vulnerable, while the improvement of commuting efficiency, measured by a key variable, the metro index, does have a robust connection to metro premium on housing units. In particular, only a large metro index can be associated with a positive metro premium. Structural features, such as the size of urban core and the existence of multiple sub-centers, influence the metro premium by affecting the value and spatial distribution of the metro index. The evidence from Beijing and Hangzhou supports that in a mono-centric city, the size of the urban core is positively associated with the metro index and the metro premium, while in a poly-centric city with a small urban core, the metro index tends to be lower in the core region and higher in the satellite regions, which enforces the metro premium to be negative in the core while positive outside of the core.

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Section: Policy Implicationscontrasting

confidence: 65%

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

et al. 2019

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“…The construction of a metro network entails extraordinary costs; therefore, the design phase is of great importance. Since a metro network should serve the inhabitants living in a given area, their transportation demands should be the main criterion while designing such a system [2]. Obviously, there are always some budget constraints that could significantly limit the range of the investment.…”

Section: Introductionmentioning

confidence: 99%

The Design of a Metro Network Using a Genetic Algorithm

Król

2019

Applied Sciences

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The process of planning the metro system is very complex. This is due to the large amount of required input data originating from many domains. Additionally, the required extraordinary budget makes the design phase difficult and forces some trade-offs to meet most expectations. Designing a metro system requires often a multi-variant analysis to examine possible future ways of urban agglomeration development. In such circumstances there is a need to apply an efficient method, which allows for obtaining a draft design of a metro system. This paper presents an application of a genetic algorithm for two stages of a metro system design. The first stage determines the layout of metro stations, which optimally meets the transportations demands of the inhabitants. The second stage generates the optimal topology of lines connecting the stations, taking into account the minimization of construction costs and the total travel time of all passengers. The parameters, which control the operation of the optimization procedures, were tuned with the use of the Taguchi method.

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“…This study does not attempt to determine the location of rail stations. Samanta & Jha (2008), however, developed an integrated mathematical and GIS model for optimizing station locations. Li, Li, Fan, & Deng (2017) have been discussing the use of a 1 km x 1 km grid in ArcGIS to support their study in locating the effecting carsharing location.…”

Section: Introductionmentioning

confidence: 99%

Agent Based Model in SAS Environment for Rail Transit System Alignment Determination

Brunner

2018

JWL

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Abstr act: Transit system had been proposed for the urban area of Honolulu. One consideration to be determined is the alignment of the transit system. Decision to set the transit alignment will have influences on which areas will be served, who will be benefiting, as well as who will be impacted. Inputs for the decision usually conducted through public meetings, where community members are shown numbers of maps with pre-set routes. That approach could lead to a rather subjective decision by the community members. This paper attempts to discuss the utilization of grid map in determining the best alignment for rail transit system in Honolulu, Hawaii. It tries to use a more objective approach using various data derived from thematic maps. Overlaid maps are aggregated into a uniform 0.1-square mile vector based grid map system in GIS environment. The large dataset in the GIS environment is analyzed and manipulated using SAS software. The SAS procedure is applied to select the location of the alignment using a rational and deterministic approach. Grid cells that are superior compared to the others are selected based on several predefined criteria. Location of the dominant cells indicates possible transit alignment. The SAS procedure is designed to allow a transient vector called the GUIDE (Grid Unit with Intelligent Directional Expertise) agent to analyze several cells at its vicinity and to move towards a cell with the highest value. Each time the agent landed on a cell, it left a mark. The chain of those marks shows location for the transit alignment. This study shows that the combination of ArcGIS and SAS allows a robust analysis of spatial data and manipulation of its datasets, which can be used to run a simulation mimicking the Agent-Based Modelling. This study also opens up further study possibilities by increasing number of factors analyzed by the agent, as well as creating a composite value of multi-factors.

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Identifying Feasible Locations for Rail Transit Stations

Cited by 24 publications

References 13 publications

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

The Design of a Metro Network Using a Genetic Algorithm

Agent Based Model in SAS Environment for Rail Transit System Alignment Determination

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