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基于分布式的停车位分配系统

作者:优质期刊论文发表网  来源:www.yzqkw.com  发布时间:2019/10/10 9:39:11  

摘要:随着智慧城市建设的加快,智能交通的趋势愈加明显,而停车作为现代交通的最后一公里,也被称为速度为零的交通,提供方便可靠的停车服务对于建设智能交通以及智慧城市有着举足轻重的影响力。目前,许多学者研究的停车位分配算法及系统大部分是在特定交通网络下的问题,而且能够实际使用的算法不能够达到停车位资源的合理调配,不能有效解决停车信息不对称等问题。本文选择基于分布式技术的停车位分配算法及其相关支持系统的实现,目的是为了优化城市停车位资源,缓解高峰时段停车位紧张问题,为车主提供停车便利同时优化城市停车资源。本文研究的主要内容包括以下三个方面:

(1)设计并实现了用于数据收集以及存储的手机终端及数据库平台,手机终端通过Android Studio开发平台以及BaiduMap SDK进行开发,手机终端主要包括有GPS位置信息采集、数据交互以及目的地导航等功能.

(2)通过对交通网络及系统场景的分析,建立了合理的停车位分配系统模型,考虑了由车辆以及有限的停车位组成的停车位分配模型,通过设计贪心算法、遗传算法的算法流程对问题进行了解决,并且通过引入了约束优化处理以及精英策略和自适应交叉变异算子对遗传算法进行了改进,加快了算法的收敛速度,并且设计了算法的实现流程。

(3)设计了算法的分布式计算框架,并且给出了Map与Reduce阶段的详细操作,对各算法进行了仿真与实现,在不同供需比下的表现,包括运行时间与迭代次数进行了对比。

该系统通过用户终端收集单个时隙内用户的包含当前位置坐标信息与目的地坐标信息的泊车请求,根据目的地临近泊车位的当前可用状态,以及城市整体停车位资源的饱和状态进行停车位分配,将路径规划返回给用户终端,通过用户终端为用户进行行车导航至分配的停车位,同时服务器端收集用户需求后将不同数据存储至对应的数据库表结构中。而分布式算法与传统算法相比,分布式停车位分配算法具有更高的抗压能力与全局搜索能力,并且能够根据服务器中的车位可用性确保泊车信息的实时性与有效性,也能有效避免线下算法导致的停车位分配冲突的问题,达到合理分配停车位资源以及避免停车信息不对称等状况。算法的仿真与实现结果表明,改进的遗传算法可在高需求量、高需求比场景下更快速更准确的找到占优解集,为车主匹配合适的车位。基于分布式的停车位分配系统能够在实际情况下完成停车位分配目标,并且具有相当的时效性与可靠性,对于优化城市交通建设以及智慧城市的建设具有良好的经济效益与实际意义,具有一定的应用价值。

With the acceleration of smart cityconstruction, the trend of building intelligent transportation is becoming moreand more obvious, and parking as the last kilometer of modern traffic, alsoknown as speed zero traffic, providing convenient and reliable parking servicehas a decisive influence on the construction of intelligent transportation andsmart city. At present, most of the parking space allocation algorithms andsystems studied by many scholars are under the specific traffic network, andthe algorithms that can be actually used cannot achieve the reasonableallocation of parking space resources and effectively solve the problems suchas parking information asymmetry. In this paper, the parking space allocationalgorithm based on distributed technology and the realization of its relatedsupport system are selected to optimize urban parking space resources,alleviate the problem of parking space shortage in rush hours, provide parkingconvenience for car owners and optimize urban parking resources at the sametime. The main content of this paper includes the following three aspects

(1) the mobile terminal and databaseplatform for data collection and storage are designed and implemented. Themobile terminal is developed through the Android Studio development platformand the BaiduMap SDK. The mobile terminal mainly includes GPS locationinformation collection, data interaction, destination navigation and other functions.

(2) in this paper, we analyze trafficnetwork and system, the establishment of a reasonable parking spacedistribution system model, considering the parking space composed of vehicle,and the limited parking space distribution model, with the greedy algorithm,genetic algorithm design of algorithm process to solve the problem, and byintroducing the constraint optimization and elite strategy and adaptivecrossover mutation operator of genetic algorithm is improved, and acceleratethe convergence speed of the algorithm, and design the implement process of thealgorithm.

(3) in this paper, the distributedcomputing framework of the algorithm is designed, the detailed operation of Mapand Reduce phases is given, the simulation and implementation of each algorithmis carried out, and the performance of each algorithm under different supplyand demand ratios, including the running time and the number of iterations arecompared.

The system collects the parking requests ofthe user within a single time slot, this parking requests including the currentposition coordinate information of the users and destination coordinateinformation, the algorithm allocates parking Spaces to users by analyzing thecurrent available state of parking Spaces near the destination and thesaturation state of urban parking Spaces, then return the route planning to theclient and parking route planning and navigation are performed for the users.Compared with the traditional algorithm, the distributed parking algorithm hasa higher ability to withstand pressure and global search capability, and it canensure the real-time and validity of the parking information, so it can reducethe problem of the parking space shortage and unavailable parking space. Thesimulation results show that the NSGA-II algorithm can find the solution setmore quickly and accurately under the circumstance of high demand, and matchthe appropriate parking space for users. In sum, the distributed parkingalgorithm is practical, and has a good economic benefit and the optimization ofurban traffic, and has certain application value.

关键词:城市交通;停车位分配;分布式计算;匹配算法

urban transport;parkingallocation;distributed computing;matching algorithm

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