论文总字数：31416字

摘 要

在互联网高速发展的现代信息化社会，共享单车产业的发展也是与时俱进，共享单车走进了城市大大小小的街道之中，走进了人们的日常生活，对于人们生活水平的提高有了显著的帮助。共享单车又分为无桩共享单车和有桩共享单车，无桩共享单车最出名的诸如小黄车、小蓝车、摩拜单车等等^[2]，它的特点是使用者可以随时随地的停车，用户不会再因为停车问题而烦恼；有桩共享单车一般就是城市公共自行车，它的特点正如它的名字一样，它是有停车桩的，使用者在需要使用的时候都需要到停车节点去借车，停车也是需要到附近的停车节点停车^[6]。随着共享单车产业的不断发展，社会和大众也渐渐的发现了它们带来的问题，有桩共享单车车辆使用完后乱停乱放，并且车辆丢失严重，而无桩共享单车主要就是用户停车难的问题^[1]。本文主要针对无桩共享单车停车难的问题进行了详细的分析最终提供了解决的方案，有桩共享单车在停车的时候需要通过软件来寻找附近的停车节点，软件能够显示附近停车节点的位置，停车节点的数量等信息。但是用户需要的是能够实时了解当前停车节点空停车位的数量，同时在用户骑行到停车节点的时间里，需要软件对这个时间段内空停车桩数量出现的变化进行一个实时的预测。传统的软件并没有针对这一关键问题给出一个有效的解决方案，本人通过详细的数据分析最终完成了有桩共享单车停车算法的设计与实现。这个系统能够实时的预测出停车节点空车桩的数量，用户骑行到这个停车节点的所需时间以及在这个时间段里空停车桩数量出现的变化，分析出用户在骑行到停车节点后是否还有空的停车桩用来停车，通过算法给用户规划出一条最优的停车路线。

本论文主要完成有桩共享单车停车算法的设计与实现。系统主要采用了线性回归算法，实现了在特定时间里，对停车节点空车桩数量的变化进行实时预测。因为本人无法取得实际环境中城市的街道以及人流量等大数据，所以本系统采用人为初始化一些基本数据对空车桩数量的变化来进行预测。最终通过一系列的数据，预测出停车节点空车桩数量的变化，规划出最优的停车路线。当系统对需要停车的用户进行最优路径的预测时，需要考虑到一些因素，例如，停车节点的初始停车桩数量、初始空车桩数量、骑行到停车节点的时间、骑行到停车节点所花时间里的进车量、出车量，考虑到这些外界因素的影响，本系统选用了最符合条件的算法来进行设计与实现。在完成了有桩共享单车停车算法的设计后，软件性能最终得到了很大的提高，能够实时有效的给人们规划出一条可以停车的最优路线。这个功能在传统的有桩共享单车软件中是不曾具备的，它的完善满足了社会与大众对于有桩共享单车软件的期望。

在适用于有桩共享单车停车的算法中，线性回归算法无疑是最合适的算法。为什么说它是最适合的呢？有桩共享单车停车在实际情况中受到很多关键因素的影响^[4]，比如，停车节点周围的区域人流量变化、骑行到目的地时间里有桩共享单车进车量和出车量的变化、初始化停车桩数量以及初始化空车桩数量等。结合这些因素我们发现线性回归算法是高效率的解决此类问题的，系统采用了线性回归算法对有桩共享单车停车拟出了一个方案，该方法有着易于编程的实现，算法效率高^[18]，复杂度低等优点。所以这次毕业设计的主要功能就是对有桩共享单车实际中的特性进行分析，将关键因素考虑进来进行综合预测，最终规划出一条最优的停车路线，将信息反馈给用户。

关键词：有桩共享单车；停车；线性回归算法；预测

Design and Implementation of a Shared Bicycle Parking Algorithm

Abstract

In the modern information-based society where the Internet is developing rapidly, the development of the shared bicycle industry is also advancing with the times. The shared bicycles have entered the streets of cities, large and small, and have entered people’s daily lives, and have improved people’s living standards. Significant help. Sharing bikes are divided into non-pronged shared bicycles and piled shared bicycles. There are no piles of shared bicycles such as the small yellow car, small blue car, Mobike bicycles, etc. It is characterized by users can park anytime, anywhere. Will not worry because of parking problems; a pile of shared bicycles is generally a city public bicycle, its characteristics, just as its name, it is a parking pile, the user needs to use the parking node to borrow when you need to use Parking is also needed to park near the parking nodes. With the continuous development of the shared bicycle industry, the society and the public have gradually discovered the problems they have caused. There are piles of shared bicycles that have been parked indiscriminately after use, and the vehicles are severely lost. The sharing of bicycles without a pile is mainly a result of user parking. Difficult question. This article mainly analyzes the problem of parking without a pile of shared bicycles. It finally provides a solution to the problem. When a piled shared bicycle is parked, it needs to use the software to find nearby parking nodes. The software can display the location of nearby parking nodes. , the number of parking nodes and other information. However, what the user needs is to be able to know in real time the number of empty parking spaces at the current parking node, and at the same time that the user is riding to the parking node, software is required to make a real-time prediction of the change in the number of empty parking piles during this time period. The traditional software does not provide an effective solution to this key problem. I have completed the design and implementation of the algorithm for parking a pile of shared bicycles through detailed data analysis. This system can predict the number of parking spaces in real time, the time required for the user to ride to this parking node, and the change in the number of empty parking piles during this period, and analyze whether the user is riding to the parking node. There are also empty parking piles for parking and an algorithm to give the user an optimal parking route.

This dissertation mainly completes the design and implementation of the algorithm for parking a pile of shared bicycles. The system mainly adopts the linear regression algorithm, realizing the real-time prediction of the change of the number of empty vehicle-piston piles at a specific time. Because I cannot obtain big data such as streets and people flow in cities in the actual environment, this system uses artificially initialized some basic data to predict changes in the number of empty vehicle piles. Finally, through a series of data, predict the change of the number of empty vehicle piles in the parking node and plan the optimal parking route. When the system predicts the optimal path for users who need to stop, some factors need to be taken into account, for example, the number of initial vehicle stops for the parking node, the number of initial empty parking spaces, the time for riding to the parking node, and the time for riding to the parking node. Taking into account the influence of these external factors, the system takes the most qualified algorithm to design and implement. After completing the design of the pile sharing bicycle parking algorithm, the software performance has been greatly improved, and it can effectively and efficiently plan an optimal route for people to stop. This function is not available in conventional piled bicycle sharing software. Its perfection satisfies the social and public expectations for sharing bicycle software.

The linear regression algorithm is undoubtedly the most suitable algorithm in the algorithm that is suitable for sharing bicycles with piles. Why is it the most suitable? There are many key factors affecting the sharing of bicycles in the actual situation. For example, changes in traffic flow around the parking nodes, changes in the number of shared-vehicle-entry vehicles and vehicles entering the destination, and initial parking. The number of piles and the number of initial empty truck piles. Combining these factors, we find that the linear regression algorithm is highly efficient to solve such problems. The system uses a linear regression algorithm to develop a plan for parking a pile of shared bicycles. The method is easy to program, and the algorithm is efficient and low-complex. Degrees and other advantages. Therefore, the main function of this set-up is to analyze the actual characteristics of the piled shared bicycles, take the key factors into consideration, and finally make an optimal parking route to feedback the information to the users.

Keywords: piled shared bicycle; parking; linear regression algorithm;prediction

目 录

摘要 I

Abstract II

第一章 引言 1

1.1 开发背景和意义 1

1.2 研究现状 1

1.3 研究的方法 2

1.4 本章小结 2

第二章 可行性分析与需求分析 4

2.1可行性分析 4

2.1.1 技术可行性 4

2.1.2 经济可行性 4

2.1.3 社会可行性 5

2.1.4 操作可行性 5

2.2需求分析 5

2.2.1系统开发的目的 5

2.2.2 系统的开发要求 5

2.2.3系统的主要功能 5

2.2.4系统ER图设计 7

2.2.5系统角色分析 10

2.2.6用例说明 10

2.3本章小结 11

第三章 系统概要设计 12

3.1系统开发环境 12

3.1.2系统开发语言 12

3.1.3 Microsoft Visual Studio 2015 12

3.1.4 Microsoft SQL Server 2012 13

3.2总体结构设计 13

3.3功能模块设计 13

3.4 数据流程分析 14

3.5系统数据库设计 16

3.5.1 数据库概念设计 16

3.5.2 数据库逻辑设计 16

3.5.3 数据表详细设计 16

3.6本章小结 18

第四章 系统详细设计与实现 19

4.1 系统功能模块说明 19

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