当前位置:主页 > 科技论文 > 路桥论文 >

基于马尔科夫链的公共自行车租赁点选址规划研究

发布时间:2018-05-04 12:12

  本文选题:公共租赁自行车系统 + 选址规划 ; 参考:《北京建筑大学》2017年硕士论文


【摘要】:为了提倡绿色出行,降低机动车出行比例,推广自行车的使用,公共自行车租赁系统在不同城市建成并投入使用,而国内的建设和运营刚刚起步,无论在理论上还是经验上均存在着一定的不足。在公共自行车借还高峰期间极易出现借还不平衡现象,一般采用人工调度方法进行调整,耗费大量政府财力,而忽略了自行车站点位置和配置规模的不合理也会导致不平衡现象的产生。因此本文将立足于公共自行车租赁站点的选址规划,通过分析影响使用者选择行为的主要因素,权衡需求点至站点间距离,相邻站点间距离、站间借还车辆流动情况以及车辆和车桩配置不足等条件的利弊,在一般选址规划研究的同时,增加使用者骑行选择行为的考虑,力求获得总成本最小的选址建设方案,对站点的位置和规模进行合理化的设计,使得站点的借车和还车需求更加趋近于平衡,减少借还数量差值,降低调度工作量。文章具体研究内容如下:(1)公共自行车租赁系统使用者选择特性研究。论文全面分析了不同性别、年龄、出行目的、出行模式等使用者特性,以及季节、时间、用地属性、距离等影响使用者选择行为的因素,探讨公众选取公共自行车租赁系统出行的影响因素,为进一步的进行出行选择模型构建及参数标定提供基本依据;(2)基于马尔科夫链方法的骑行因素和需求因素分析。简要介绍马尔科夫链方法的原理和使用条件,以及在公共自行车租赁系统中的适用性。选取骑行时耗和借还需求两个因素,构建状态数量转移矩阵和转移概率矩阵,并通过马尔科夫链方法求解得到稳态概率向量,获得系统达到稳定状态时基于骑行时耗的各站点状态转移和使用者在各站点处借还需求的一般概率,为选址规划模型中骑行成本和建设成本的确定提供数据支持;(3)公共自行车租赁点选址规划模型。构建基于步行时耗、骑行时耗、建设规模和不足惩罚四个因素的成本模型,考虑站点之间的联系关系,选择不同的站点集合,将其作为整体进行分析,并通过量化和单位统一,在价格层面考虑选址规划方案的优劣;(4)模型应用示例。以北京市已建成运营的公共自行车租赁系统为背景,构建算例,使用模型确定最终的选址规划方案,并以最终方案为例,呈现详细的计算过程。在计算所得的成果中,分析不同标准下的案例选择方式,并对不同类型案例进行对比。
[Abstract]:In order to promote green travel, reduce the proportion of motor vehicle travel, and promote the use of bicycles, the public bicycle rental system has been built and put into use in different cities, but the domestic construction and operation has just started. Both in theory and experience, there are some shortcomings. During the peak period of public bicycle borrowing and returning, it is easy to appear the phenomenon of imbalance between borrowing and returning, so the manual dispatching method is generally adopted to adjust, which consumes a lot of government financial resources. And neglecting the bicycle station location and configuration scale of unreasonable will also lead to imbalance phenomenon. Therefore, this paper will be based on the public bicycle rental site location planning, through the analysis of the main factors affecting the user's choice behavior, weighing the demand point to the distance between the site, the distance between adjacent sites, Taking advantage of the advantages and disadvantages of the flow situation of vehicles and the insufficient allocation of vehicles and piles between stations, while the general site planning is studied, the consideration of the user's behavior of cycling selection is increased, and the site construction scheme with the lowest total cost is obtained. The rational design of site location and scale makes the demand for car borrowing and returning to the station more balanced, reduces the difference of borrowing and returning quantity, and reduces the workload of dispatching. The specific contents of this paper are as follows: 1) Research on the user selection characteristics of public bicycle rental system. The paper comprehensively analyzes the characteristics of users, such as gender, age, travel purpose, travel mode and so on, as well as factors such as season, time, land use attribute, distance and so on, which affect the user's choice behavior. This paper discusses the influencing factors of public choice of public bicycle rental system, and provides a basic basis for the further construction of travel choice model and parameter calibration. (2) the analysis of riding factors and demand factors based on Markov chain method. This paper briefly introduces the principle and application conditions of Markov chain method and its applicability in public bicycle rental system. By selecting two factors of riding time consumption and demand demand, the state quantity transfer matrix and transition probability matrix are constructed, and the steady-state probability vector is obtained by Markov chain method. To obtain the general probability that the system reaches a stable state based on the state transition of each station consumed by riding and the general probability that the user borrows the demand at each site, This paper provides data support for the determination of riding cost and construction cost in the location planning model) the location planning model of public bicycle rental point. A cost model based on walking time, cycling time consumption, construction scale and insufficient penalty is built. Considering the relationship between sites, different sets of sites are selected, analyzed as a whole, and analyzed by quantification and unity of units. Considering the merits and demerits of the site planning scheme at the price level, an example of application of the model is given. Taking the public bicycle rental system in Beijing as the background, a calculation example is constructed, and the final location planning scheme is determined by using the model, and the detailed calculation process is presented by taking the final scheme as an example. In the calculated results, the case selection methods under different criteria are analyzed, and the different types of cases are compared.
【学位授予单位】:北京建筑大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:U491.225

【参考文献】

相关期刊论文 前10条

1 朱玮;何京洋;王德;;法国公共自行车系统布局方法与实证研究——以巴黎和里昂为例[J];国际城市规划;2015年S1期

2 胡列格;夏云;王佳;唐量;;城市公共自行车高峰期需求不均衡的调度优化研究[J];铁道科学与工程学报;2015年02期

3 刘引涛;刘楠;;公共自行车服务系统站点及锁桩设置评价模型的分析研究[J];电子设计工程;2014年23期

4 曹彦;何东进;洪伟;纪志荣;朱学平;游巍斌;连素兰;;加权马尔科夫链在福建省森林火灾预测中的应用研究[J];西南林业大学学报;2014年03期

5 彭姗姗;陆克斌;罗海星;王丹丹;;自行车租赁网点布局规划及车辆分配研究[J];琼州学院学报;2014年02期

6 茹正亮;杨芝艳;朱文刚;杨红莉;;加权马尔科夫AR-GARCH-GED模型在降水量中的预测[J];系统工程;2013年12期

7 杨军;侯忠生;;一种基于灰色马尔科夫的大客流实时预测模型[J];北京交通大学学报;2013年02期

8 周扬军;;城市公共自行车系统规划研究[J];城市交通;2012年05期

9 何流;陈大伟;李旭宏;卢静;;城市公共自行车租赁点布局优化模型[J];武汉理工大学学报(交通科学与工程版);2012年01期

10 章晨;;基于马尔科夫链的股票价格涨跌幅的预测[J];商业经济;2010年21期

相关硕士学位论文 前10条

1 谭玉龙;基于马尔可夫链模型的公共自行车站点供需研究[D];西南交通大学;2015年

2 陆朕;公共自行车租赁点车辆数的预测方法研究[D];南京师范大学;2015年

3 成先镜;公共自行车两阶段调度策略与模型及求解方法研究[D];南京师范大学;2015年

4 冯媛媛;公共自行车租赁点布局方法研究[D];长安大学;2014年

5 马静;城市公共自行车使用研究[D];西安建筑科技大学;2014年

6 唐岷;城市公共自行车的经营模式与租车点布局优化研究[D];长安大学;2014年

7 刘臻;城市公共自行车运营中的多车场车辆调配优化研究[D];北京交通大学;2014年

8 罗峗;城市公共自行车选择行为研究[D];长安大学;2013年

9 秦茜;公共自行车租赁系统调度问题研究[D];北京交通大学;2013年

10 罗海星;城市公共自行车租赁站点选址方法研究[D];北京交通大学;2013年



本文编号:1843010

资料下载
论文发表

本文链接:https://www.wllwen.com/kejilunwen/daoluqiaoliang/1843010.html


Copyright(c)文论论文网All Rights Reserved | 网站地图 |

版权申明:资料由用户5797d***提供,本站仅收录摘要或目录,作者需要删除请E-mail邮箱bigeng88@qq.com