居住区共享停车泊位分配模型
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摘要
为了提高停车泊位利用率,减少停车后步行距离,根据商业区和居住区停车需求时段的错峰特征,建立共享停车泊位利用率最大化和步行距离最小化的双目标泊位分配模型.模型考虑了停车泊位供需空间和时间冲突特征,界定了模型的边界约束条件,采用粒子群多目标搜索算法求解.以聊城市金鼎商圈为例,调研了商业区和居住区的停车泊位数量、高峰时段停车需求和平均步行距离等模型参数.通过算法仿真,实验结果验证了模型的可行性.研究结果表明,建立的停车共享分配模型可用于居住区共享停车泊位分配,有效地提高了泊位利用率,降低了停车后的平均步行距离.
In order to improve the occupancy of parking spaces, reduce the walking distance after parking, a double target model which takes the occupancy and walking distance into account is proposed. According to the peak characteristics of commercial zones and the residential zones, this model considers the temporal and spatial conflicting characteristics, defines the boundary constraint model. Then the particle swarm algorithm is used to solve this model. Base on the data collected from the Jin Ding CBD in Liaocheng, China, the parking space amount, peak hours' park demands and walking distance, et al, the feasibility of this model is verified. The results show that the allocating model is practical to distribute the parking spaces, the parking occupancy is effectively increased and the walking distance after parking is shorter.
In order to improve the occupancy of parking spaces, reduce the walking distance after parking, a double target model which takes the occupancy and walking distance into account is proposed. According to the peak characteristics of commercial zones and the residential zones, this model considers the temporal and spatial conflicting characteristics, defines the boundary constraint model. Then the particle swarm algorithm is used to solve this model. Base on the data collected from the Jin Ding CBD in Liaocheng, China, the parking space amount, peak hours' park demands and walking distance, et al, the feasibility of this model is verified. The results show that the allocating model is practical to distribute the parking spaces, the parking occupancy is effectively increased and the walking distance after parking is shorter.
引文
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[2]INGA MOLENDA,GERNOT SIEG.Residential parking in vibrant city districts[J].Economics of Transportation,2013(2):131-139.
[3]SHAO C,YANG H,ZHANG Y,et al.A simple reservation and allocation model of shared parking lots[J].Transportation Research Part C:Emerging Technologies,2016(71):303-312.
[4]段满珍,杨兆升,张林,等.个性化诱导下的居住区共享停车泊位分配模型[J].东北大学学报(自然科学版),2017,38(2):174-179.[DUAN M Z,YANG Z S,LIN Z,et al.Parking spaces allocation model of residential areas sharing parking based on personalized guidance[J].Journal of Northeastern University,2017,38(2):174-179.]
[5]段满珍.基于博弈论的居住区共享停车理论与方法研究[D].长春:吉林大学,2017.[DUAN M Z.Research on the theory and method of residential shared parking based on game theory[D].Changchun:Jilin Universtiy,2017.
[6]章恩泽,陈庆伟.不确定可靠性优化问题的多目标粒子群优化算法[J].控制与决策,2015,30(9):1701-1705.[ZHANG E Z,CHEN Q W.Multi-objective particle swarm optimization for uncertain reliability optimization problems[J].Control&Decision,2015,30(9):1701-1705.]
[7]冯琳,毛志忠,袁平.基于Maximin的动态种群多目标粒子群算法[J].东北大学学报(自然科学版),2010,31(7):913-916.[FENG L,MAO Z Z,YUAN P.Dynamic swarm multiobjective optimization PSO-based maximin function[J].Journal of Northeastern University,2010,31(7):913-916.]