Research on the Joint Optimization of Shared Bikes and Demand-Responsive Connector

doi:10.12141/j.issn.1000-565X.240455

Abstract

Abstract:

Demand-Responsive Connector (DRC), as a flexible public transportation mode, can provide personalized bus services according to passengers’ needs and has been widely applied in urban areas both domestically and internationally. However, in actual operation, it faces the dilemma of balancing service efficiency and operational costs, as well as the challenge of achieving “door-to-door” services. To address these issues, a joint travel mode combining shared-bike transfer and DRC was proposed. By integrating the advantages of shared bikes and DRC, the coupling optimization of the two transportation modes can be realized, thereby improving the overall service efficiency and service level of public transportation. To this end, based on the continuous approximation method, discrete demand points and shared bicycle deployment locations were continuousized. The operating costs of the transit system, shared bicycle costs, and passenger travel time costs were derived and calculated. By minimizing the total system cost, the joint mobility system was optimized. With the goal of minimizing the total system cost, the coupling optimization of shared bicycles and demand-responsive buses was realized. To verify the effectiveness of the proposed joint travel system, an empirical study was conducted using the university town area of Chongqing as a case. The operation of the joint travel system under different scenarios was simulated and compared with the traditional DRC system without shared-bikes. The results show that the joint travel system can effectively address the operational problems of DRC. Compared with the traditional DRC system, the joint travel system can reduce the total system cost by up to 14.8%, the travel time saving by 15.2%, and the detouring saving of DRC vehicles by 29%. It is demonstrated that introducing shared bicycles as a first- and last-mile connection tool in demand-responsive transit systems can significantly reduce transit operating costs and passenger travel times. At the same time, it minimizes unnecessary detours by transit vehicles, optimizes transit routes, and greatly improves the efficiency and quality of public transportation services.

Key words: urban traffic, joint optimization, continuous approximation, demand-responsive connector, shared bike

CLC Number:

U121

XU Hang, LI Xin, YUAN Yun. Research on the Joint Optimization of Shared Bikes and Demand-Responsive Connector[J]. Journal of South China University of Technology(Natural Science Edition), 2025, 53(8): 20-28.

Figures/Tables 11

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Table 1

Parameter values"

参数	数值
$v w / (k m · h - 1)$	5
$v d / (k m · h - 1)$	20
$v b / (k m · h - 1)$	15
$p / (人 · h - 1)$	30
$α l [16] / (元 · k m - 1)$	4.13
$α b / (元 · h - 1)$	3
$δ [16] / (元 · h - 1)$	25
$β [16]$	0.5
$α f [16] / (元 · h - 1 · 个 - 1)$	5.57
$α x [16] / (元 · h - 1 · 个 - 1)$	0.46

Table 1

Table 2

Solution results of the case"

系统	$d / m$	$r / m$	成本/元
系统	$d / m$	$r / m$	系统总成本	公交运营成本	共享单车运营成本	出行时间成本
联合出行系统	328.5	497.6	1 328	148	56	1 124
传统DRC系统	—	—	1 446	173	—	1 273
成本节约比例/%	—	—	8.2	14.5	—	11.7

Table 2

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