Computation model of network scale for urban rail transit based on traffic demand overflow

An Xue-wu; Du Dian-hu; Ma Chao-qun; Zhou Wei

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An Xue-wu, Du Dian-hu, Ma Chao-qun, Zhou Wei. Computation model of network scale for urban rail transit based on traffic demand overflow[J]. Journal of Traffic and Transportation Engineering, 2008, 8(3): 82-85.

Citation:

An Xue-wu, Du Dian-hu, Ma Chao-qun, Zhou Wei. Computation model of network scale for urban rail transit based on traffic demand overflow[J]. Journal of Traffic and Transportation Engineering, 2008, 8(3): 82-85.

Citation:

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Computation model of network scale for urban rail transit based on traffic demand overflow

1.
School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China
2.
School of Economics and Management, Chang'an University, Xi'an 710064, Shaanxi, China

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Author Bio:
An Xue-wu(1965-), male, doctoral student, +86-29-87295406, anxuewu@yahoo.com.cn

Zhou Wei(1959-), male, professor, +86-29-87295406, zhw59@hotmail.com
Received Date: 2007-11-26
Publish Date: 2008-06-25

Abstract

Abstract

In order to compute the network scale of urban rail transit based on the development degree of roads, the computation methods were analyzed at present, and a new computation model based on traffic demand overflow was built. With the precondition that road network could afford taffic service at certain service level in the future, the overflow of total traffic demand contrasted with road network capacity was computed, the overflow was transformed to passenger transport demand and was transported by rail transit, the rational scale of rail transit network could be confirmed by using its load intensity, the network scale of Xi'an rail transit in 2020 was computed by using different methods, and the computation results were compared. The result from travel demand model is 103.68 km, the result from financial strength analysis is 66.32~94.74 km, the result from the new model is 95.89 km, the results are basically accordant, so the new model is feasible.
- traffic planning,
- urban rail transit,
- network scale,
- traffic demand overflow

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References(10)

References

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