Two Network Structure Indicators for Conventional Public Transit

来源 :Journal of Harbin Institute of Technology | 被引量 : 0次 | 上传用户:zap2050zap
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The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,two network structure indicators are proposed.Firstly,according to the obvious defects lying in the traditional no-linear coefficient,the realistic no-linear coefficient γRNL,a modified no-linear coefficient indicator,is put forward,which takes into account the effects of barriers in a city.Secondly,to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network,the length dimension LDis proposed on the basis of Fractal Theory.Finally,a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis.The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines,and LDcan represent the rate of change of the network density,adding a new member to the scheme of network structure indicators for public transit. The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged. In order to improve and enrich the conventional public transit assessment system, two network structure indicators are proposed. Firstly, according to the obvious defects lying in the traditional no-linear coefficient, the realistic no-linear coefficient γRNL, a modified no-linear coefficient indicator, which takes into account the effects of barriers in a city. Secondarily, to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network, the length dimension LDis proposed on the basis of Fractal Theory. Finally, a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis. The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines, and LDca n represent the rate of change of the network density, adding a new member to the scheme of network structure indicators for public transit.
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