基于居住区共享停车的双层规划诱导模型
发布时间：2018-07-18 10:43
【摘要】：为了缓解因城市停车资源有限造成的停车难问题,根据共享停车理论和智能交通诱导策略,提出了居住区泊位参与的共享停车诱导服务流程,探讨了实现居住区共享停车的基本条件,建立了诱导服务的泊位协调控制双层规划模型.该模型上层以高峰泊位空闲指数差异均值最小为目标,作为衡量该诱导服务能否实现区域范围停车资源均衡利用的指标;下层以驾驶员停车后平均步行距离最小为目标,作为衡量共享停车是否可行的依据.根据双层规划模型的求解原理和粒子群算法优化思想,设计了该模型的粒子群嵌套优化算法,并进行仿真实验.结果表明:鹤祥园小区最低泊位空闲指数为0.301,最大高峰泊位对外共享率为0.093,即只利用了不足1/3的闲置泊位就缓解了远洋城的停车问题;平均步行距离为160.59m,说明共享方案可行.
[Abstract]:In order to alleviate the parking difficulties caused by the limited parking resources in the city, according to the shared parking theory and the intelligent traffic guidance strategy, the paper puts forward the shared parking guidance service flow in the residential area. This paper discusses the basic conditions of realizing shared parking in residential area, and establishes a bilevel programming model of berth coordination control for induction service. In the upper layer of the model, the minimum average value of peak berth idle index is taken as the target to evaluate whether the inductive service can realize the balanced utilization of parking resources in the region, and the minimum average walking distance after the driver stops is the goal of the lower layer. As a measure of the feasibility of shared parking. According to the solving principle of the bilevel programming model and the idea of particle swarm optimization, the particle swarm nested optimization algorithm of the model is designed, and the simulation experiment is carried out. The results show that the lowest berth idle index is 0.301, the maximum peak berth sharing rate is 0.093, that is, the parking problem of ocean city is alleviated only by using less than 1 / 3 idle berth, and the average walking distance is 160.59 m, which shows that the sharing scheme is feasible.
【作者单位】： 吉林大学交通学院;华北理工大学建筑工程学院;
【基金】：国家973计划资助项目(2014BAG03B03) 国家自然科学基金资助项目(51378171,61374157)
【分类号】：U491.7
，
本文编号：2131656
[Abstract]:In order to alleviate the parking difficulties caused by the limited parking resources in the city, according to the shared parking theory and the intelligent traffic guidance strategy, the paper puts forward the shared parking guidance service flow in the residential area. This paper discusses the basic conditions of realizing shared parking in residential area, and establishes a bilevel programming model of berth coordination control for induction service. In the upper layer of the model, the minimum average value of peak berth idle index is taken as the target to evaluate whether the inductive service can realize the balanced utilization of parking resources in the region, and the minimum average walking distance after the driver stops is the goal of the lower layer. As a measure of the feasibility of shared parking. According to the solving principle of the bilevel programming model and the idea of particle swarm optimization, the particle swarm nested optimization algorithm of the model is designed, and the simulation experiment is carried out. The results show that the lowest berth idle index is 0.301, the maximum peak berth sharing rate is 0.093, that is, the parking problem of ocean city is alleviated only by using less than 1 / 3 idle berth, and the average walking distance is 160.59 m, which shows that the sharing scheme is feasible.
【作者单位】： 吉林大学交通学院;华北理工大学建筑工程学院;
【基金】：国家973计划资助项目(2014BAG03B03) 国家自然科学基金资助项目(51378171,61374157)
【分类号】：U491.7
，
本文编号：2131656
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