华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (8): 20-28.doi: 10.12141/j.issn.1000-565X.240455

• 智慧交通系统 • 上一篇    下一篇

共享单车与需求响应公交耦合优化

许航   李欣   袁昀   

  1. 大连海事大学 交通运输工程学院,辽宁 大连 116026



  • 出版日期:2025-08-25 发布日期:2025-03-07

Joint Optimization of Demand Responsive Connector Fed by Shared Bikes

XU Hang  LI Xin  YUAN Yun   

  1. Transportation Engineering College, Dalian Maritime University, Dalian 116026, Liaoning, China 

  • Online:2025-08-25 Published:2025-03-07

摘要:

针对需求响应公交系统在运营过程中存在的服务效率与运营成本的博弈难题,以及难以实现“门到门”的服务难题,提出一种共享单车接驳需求响应公交的联合出行模式。基于连续近似方法,将离散的需求点与共享单车投放点连续化,推导计算公交运营成本、共享单车成本以及乘客出行时间成本,以最小化系统总成本为目标,实现共享单车与需求响应公交的耦合优化。最后以重庆市大学城片区为例,验证所提出联合出行系统的适用性。结果表明:联合出行系统可有效解决需求响应公交的运营难题,与无共享单车接驳的传统需求响应公交系统相比,联合出行系统可最高降低14.8%的系统总成本,15.2%的出行时间成本与29%的公交车辆绕行,大幅提升公共交通的服务效率与服务水平。


关键词: 城市交通, 耦合优化, 连续近似, 需求响应公交, 共享单车

Abstract:

Aiming at the problems that appear in the demand response bus system including excessive detours, and difficulty in realizing the "door-to-door" service. A joint travel service combining demand-responsive connectors and shared bikes is proposed to relieve these problems. Utilizing a continuous approximation method, the discrete demand points and shared bicycle distribution points are transformed into continuous variables, and derive the calculation of transit operation costs, shared bicycle costs, and passenger travel time costs. With the goal of minimizing the total system cost, the coupling optimization of shared bicycles and demand-responsive buses is realized. Finally, the applicability of the proposed joint system is verified by taking the university city area in Chongqing as an example. The results show that the bike-fed DRC system can solve the problems that appeared in the operation. Besides that, compared with the DRC-only system, the joint travel mode 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%, which can significantly improve the service efficiency and service level of public transportation.

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