基于累积前景理论的共享停车泊位匹配模型
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U491

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国家自然科学基金(51878349).江苏省研究生科研与实践创新计划项目(SJCX22_0479);南京市科协“软科学研究”项目-南京面向治理的停车共享技术与对策研究(2023-28).


Shared Parking Space Matching Model Based on Cumulative Prospect Theory
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    摘要:

    为缓解停车资源紧缺问题,合理利用现有泊位资源,在充分考虑商业区停车用户的出行目的和个体异质性的基础上构建了基于累积前景理论的共享停车泊位匹配(CPT)模型。通过累积前景理论分析商业区用户的停车选择行为,在考虑停车资源利用情况和用户对泊位满意程度的基础上,以泊位利用率和综合前景价值综合最大为目标函数,采用遗传算法对模型进行求解。算例结果表明:相较泊位利用率最大分配(MPUR)方案,CPT方案能在保证泊位利用率的基础上进一步考虑到用户的实际停车选择行为。根据用户出行目的和个体情况的不同,匹配到该场景下更合适的泊位;为进一步验证模型的有效性和适用性,分别在不同供需情况和不同停车规模下对模型进行仿真实验,结果表明:在供大于求、供需平衡和供不应求三种情况下,CPT模型能在保证泊位利用率的基础上,使用户平均满意度分别提升了10.72%、8.64%和24.62%,通过模型权重的调整可在不同停车供需场景下为泊位管理者提供更加合理的泊位匹配方案参考。

    Abstract:

    In order to alleviate the shortage of parking resources and rationally utilize existing parking resources, a shared parking space matching model based on cumulative prospect theory (CPT) is constructed on the basis of fully considering the travel purpose and individual heterogeneity of parking users in commercial areas. Through the cumulative prospect theory, the parking selection behavior of users in commercial areas was analyzed, and on the basis of considering the utilization of parking resources and the satisfaction of users, the model was solved by genetic algorithm based on the objective function of the comprehensive maximum of parking utilization rate and comprehensive prospect value. the example results show that compared with the maximum allocation of parking utilization rate (MPUR) scheme, the CPT scheme can further consider the actual parking selection behavior of users on the basis of ensuring parking space utilization. According to the user"s travel purpose and individual situation, match to a more suitable parking space in this scenario. To further validate the effectiveness and applicability of the model, simulation experiments were conducted on the model under different supply and demand scenarios and different parking scales. The results show that the CPT model can improve average user satisfaction by 10.72%, 8.64%, and 24.62%, while ensuring the utilization rate of parking spaces, under three scenarios: supply exceeding demand, supply balancing, and supply exceeding demand, by adjust the weight of the model, more reasonable parking matching schemes can be provided for parking managers in different parking supply and demand scenarios.

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郭缙烨,胡军红,傅文陵,等. 基于累积前景理论的共享停车泊位匹配模型[J]. 科学技术与工程, 2024, 24(28): 12357-12365.
Guo Jinye, Hu Junhong, Fu Wenling, et al. Shared Parking Space Matching Model Based on Cumulative Prospect Theory[J]. Science Technology and Engineering,2024,24(28):12357-12365.

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  • 收稿日期:2023-09-10
  • 最后修改日期:2024-07-14
  • 录用日期:2024-04-17
  • 在线发布日期: 2024-11-05
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