Phased Transit Service Design Based on Mean-Variance Theory

XIA Liang; JIANG Xinguo; FAN Yingfei

doi:10.3969/j.issn.0258-2724.20210874

Volume 58 Issue 6

Dec. 2023

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Abstract

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Journal of Southwest Jiaotong University > 2023 > 58(6): 1294-1302.

XIA Liang, JIANG Xinguo, FAN Yingfei. Phased Transit Service Design Based on Mean-Variance Theory[J]. Journal of Southwest Jiaotong University, 2023, 58(6): 1294-1302. doi: 10.3969/j.issn.0258-2724.20210874

Citation:

XIA Liang, JIANG Xinguo, FAN Yingfei. Phased Transit Service Design Based on Mean-Variance Theory[J]. Journal of Southwest Jiaotong University, 2023, 58(6): 1294-1302. doi: 10.3969/j.issn.0258-2724.20210874

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Phased Transit Service Design Based on Mean-Variance Theory

doi: 10.3969/j.issn.0258-2724.20210874

XIA Liang^{1, 2, 3
,},
JIANG Xinguo^{1, 2
,
,},
FAN Yingfei³

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
2.
Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
3.
School of Transportation and Logistics Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
4.
Wangcheng Transportation Bureau, Changsha 410203, China

Received Date: 08 Nov 2021
Rev Recd Date: 25 Jan 2022

Available Online: 25 Aug 2023

Publish Date: 01 Apr 2022

Abstract

Abstract

Transit travel demand has an important characteristic of being stochastic. The decision-makers with different risk attitudes (i.e., risk-neutral, risk-averse, and risk-seeking) will choose various transit service designs in response to the stochastic demand, which seems to be especially critical in the phased transit design. In order to study the impacts of stochastic travel demand on the transit service design, we firstly propose a mean-variance based decision-making approach for decision-makers with different risk attitudes. Correspondingly, the study proposes a model for phased transit corridor design, which can concurrently optimize the line length, transit station location, and headway in each phase. Then, the local decomposition method and optimization theory are adopted to find the analytical solution. Finally, the study compares the transit corridor designs with different design strategies (i.e., full-covered, once-and-done, and phased designs of the transit line) and risk decision-making attitudes. The results indicate: 1) the phased design has a lower expected system cost than the full-covered and the once-and-done designs, and a more robust scheme than the once-and-done design; and 2) risk decision- making attitudes substantially affect the parameters (i.e., the transit length, station location, and headway) of transit system under different design strategies; for example, the risk-averse decision-makers tend to seek denser station locations in the full-covered design, but relatively lower station density in the once-and-done design in phased design. The issue becomes more complex in the phased transit design. This study serves to provide a risk-based decision-making model of phased transit service under the increasing stochastic demand for the government manager and transit operators.
- transit traffic,
- phased design,
- stochastic demand,
- mean-variance theory

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References(27)

References

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