摘要
【背景】现有共享泊位分配信息化平台对动态随机需求难以即时响应,鲜有针对用户需求差异化进行泊位分配,且平台收益具有一定优化空间。【目标】构建并求解考虑供需异质性的共享泊位滚动时域分配模型,优化停车资源配置及社会总效益。【方法】基于经典共享泊位分配模型框架,综合考虑停车供需异质性及低碳效益,制定“按需租用”策略,设计人工鱼群-遗传算法(Artificial Fish Shoal-Genetic Algorithm,AFSA-GA),利用Matlab进行数值仿真实验。【数据】重庆市沙坪坝区龙湖好城时光居民小区停车场总泊位数、空闲泊位数及其时空间特征。【结论】模型可实现泊位周转率近80%,用户接受率、请求时段接受率约90%,低碳收益占比约6.56%;与传统模型相比,可节省一定的车位租用成本,具有更高的系统收益,且泊位周转率与传统泊位分配模型相近;通过灵敏度分析发现,随需求量增加,收益先增后减,泊位周转率从剧增转为平稳,用户接受率、请求时段接受率降低速度逐渐加剧。【应用】该研究结果可为共享平台进行停车分配与管理决策提供理论参考。
[Background]Existing information platforms for shared berth allocation cannot respond to dynamic random demands in real time and rarely allocate berths based on user requirements.Ad‐ditionally,the platform’s income can be further optimized.[Objective]To construct and solve a roll‐ing time-domain allocation model for shared berths while considering the heterogeneity of supply and demand to optimize the allocation of parking resources and maximize total social benefits.[Methods]Based on the classical shared-berth allocation model framework,this study comprehen‐sively considers the heterogeneity of parking supply and demand as well as low-carbon benefits.An“on-demand rental”strategy is devised and an artificial fish shoal-genetic algorithm is developed.Numerical simulation experiments are conducted using Matlab.[Data]The total number of parking spaces,the number of available berths,and the temporal and spatial characteristics of parking lots in the Good City Time residential district of Longhu City,Shapingba District,Chongqing,are investi‐gated on-site.[Conclusions]The model achieves a berth turnover rate of approximately 80%,a user acceptance rate and a request period acceptance rate of approximately 90%,and a low-carbon in‐come ratio of approximately 6.56%.Compared with the classical model,it reduces the parking-space rental cost significantly and offers more system benefits.Moreover,its turnover rate is similar to that of the classical parking-allocation model.Finally,a sensitivity-analysis experiment is performed,and the result shows that as demand increases,the revenue first increases and then decreases,the berth turnover rate changes from abrupt to stable,and the decline in the user acceptance rate and re‐quest-period acceptance rate increases gradually.[Applications]The findings of this study provide a theoretical reference for parking allocation and management decisions on shared platforms.
作者
卓云凤
石超峰
张玺
ZHUO Yunfeng;SHI Chaofeng;ZHANG Xi(College of Traffic and Transportation,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《交通运输工程与信息学报》
2025年第2期57-70,共14页
Journal of Transportation Engineering and Information
基金
国家社会科学基金项目(16BJL121)
重庆交通大学科研启动经费项目(17JDKJC-A002)
重庆市教委科学技术研究项目(KJ1705148)。
关键词
城市交通
动态分配模型
人工鱼群-遗传算法
共享停车
混合预约
urban transportation
dynamic allocation model
artificial fish shoal-genetic algorithm
shared parking
mixed reservation
