Optimization of carsharing fleet size to maximize the number of clients served

Carsharing services aim at offering short-term car rentals. Those rentals can be offered in different modalities, such as round-trip and one-way. This work simulates the dynamics of possible carsharing clients searching for resources availability and using the carsharing service. Clients can rent a vehicle if there is an available car at the client's origin station and an available parking slot at the client's destination station. If there is no car or parking slot available, the possible clients look for these resources in other stations nearby their origin and destination. Together with this Agent-Based simulation, the fleet of vehicles is optimized to serve as many clients as possible and to avoid wasting resources. This work proposes a Mixed-Integer Linear Programming Model to optimize the fleet size of a carsharing service for the one-way and round-trip modes while simulating the clients interaction. Different scenarios are analyzed using real parameters and spatial data from the city of São Paulo, Brazil. Those scenarios are composed for round-trip and one-way, varying the number of possible clients, the maximum number of available vehicles, different sets of carsharing stations and the corresponding number of parking slots. We also explore the distance walked by clients to find an available vehicle to rent or a parking slot to deliver the rented vehicle. The Agent-Based simulation showed that clients' flexibility to walk was well aligned with a higher allocation of vehicles in the same station, since it increased the possibility of sharing cars among nearby clients. Also, results show that round-trip services can scale-up better than one-way services, and that distances walked by the clients to be served are essential to make the most of the one-way mode's vehicles and parking slots.     

Dynamic parking negotiation and guidance using an agent-based platform

Modern prosperous cities strongly need advanced parking assistant systems, intelligent transportation systems providing drivers with parking information. Existing parking information systems usually ignore the parking price factor and do not automatically provide optimal car parks matching drivers’ demand. Currently, the parking price has no negotiable space; consumers lose their bargaining position to obtain better and cheaper parking. This study uses an intelligent agent system, and considering negotiable parking prices, selects the optimal car park for the driver. The autonomous coordination activities challenge traditional approaches and call for new paradigms and supporting middleware. An agent-based coordination network is proposed to bring true benefit to drivers and car park operators. These modern intelligent agents have capabilities including planning, mobility, execution monitoring and coordination. These properties can be used to construct the integrated parking assistant system.     

一种基于路径规划的自动平行泊车算法

针对城市中停车位狭小、现有自动泊车方法缺乏连贯性的问题,提出一种自动平行泊车算法。对现有的五阶多项式路径规划方法加以改进,并有针对性地设计罚函数,采用遗传算法计算最佳泊车路径和最小泊车空间,实现自动平行泊车。仿真结果表明,该算法能快速有效地完成泊车,车辆损伤小,对空间的要求最低。     

Opportunistically assisted parking service discovery: Now it helps,now it does not

In this paper, we explore the way the discovery of service can be facilitated or not by utilizing service location information that is opportunistically disseminated primarily by the service consumers themselves. We apply our study to the real-world case of parking service in busy city areas. As the vehicles drive around the area, they opportunistically collect and share with each other information on the location and status of each parking spot they encounter. This opportunistically assisted scenario is compared against one that implements a “blind” non-assisted search and a centralized approach, where the allocation of parking spots is managed by a central server with global knowledge about the parking space availability.Results obtained for both uniformly distributed travel destinations and a single hotspot destination reveal that the relative performance of the three solutions can vary significantly and not always inline with intuition. Under the hotspot scenario, the opportunistic system is consistently outperformed by the centralized system, which yields the minimum times and distances at the expense of more distant parking spot assignments; whereas, for uniformly distributed destinations, the relative performance of all three schemes changes with the vehicle volume, with the centralized approach gradually becoming the worst solution and the opportunistic one emerging as the best scheme. We discuss how each approach modulates the information dissemination process in space and time and resolves the competition for the parking resources. We also outline models providing analytical insights to the behaviour of the centralized approach.     

基于改进A*算法的AGV智能泊车算法

随着社会的发展和文明的进步，人类对车辆智能化水平、便捷性和安全性的要求越来越高，针对停车场车位少、停车难的问题，在A*算法的基础上，增加了时间因素，将等待时间加入启发函数，综合路径距离和等待时间两个因素进而规划出入库和出库任务的最佳路径，设计了三维A*智能泊车算法，在结构化环境下，根据给定的停车场地图，预留出最优车位，规划出多辆同时工作的自动导引车（Automated Guided Vehicle，AGV）最优路径，安排AGV运载车辆到指定车位或完成出库过程，尽量减少客户在停车和取车中的等待时间，并使总成本最小，呈现真正"互联网化"的智能停车体验.     

基于多传感器多路径规划自动泊车系统仿真及实车验证

针对无人驾驶汽车比赛进行的研究和设计。根据阿克曼转向几何建立汽车运动学模型,采用多种传感器构建感知系统识别车位,为不同车位设计了平行、垂直和单段三种泊车路径,籍由触角算法控制汽车跟踪规划路径,用Matlab仿真,在VC2005平台上实车测试。比赛中,＂智能先锋号＂车位检测与车身控制准确,避免了其他参赛队漏检错检或碰到障碍物的失误,为拿下最终比赛的胜利垫定了基础。     

Multi Criteria Decision Making System for Parking System

System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques were used. The two modules were compared with other state-of-the-art solutions. We utilized the You Only Look Once (YOLO) architecture to detect and recognize an LP because its performance in the context of Saudi Arabian LP numbers was superior to that of other solutions. Compared with existing state-of-the-art solutions, the performance of the proposed solution was more effective. The solution can be further improved for use in the city and large organizations that have priority parking spaces. A dataset of LP-annotated images of vehicles was used. The results of this study have considerable implications for smart parking, particularly in universities; in addition, they can be utilized for smart cities.     

数据驱动的通勤团体配对共享停车方法研究

随着机动车保有量日益增加,停车难愈发成为城市的通病,但当上班地点停车场大排长龙时,周边居住区车位却大量处于空闲状态,车位资源得不到合理利用,而现有的共享停车方法由于其随机性实施难度较大。为减少其随机性,降低共享停车的实施难度以及减少车位资源的浪费,基于毗邻办公楼与居住区的通勤团体之间出行时间具有的天然互补性,提出数据驱动一对一的配对共享解决方案。通过分析车场车辆进出记录数据对问题进行求解,分析进出口数据,得到关于居住区车位的空闲时长特征与办公楼车辆的使用时长特征,进而根据时长最大化的匹配方法得到配对车位与车辆。针对选取的停车场进行实验,完全匹配的车位占比37.66%,所有匹配车位利用率平均提高15.24%,其中最大提高57.84%。结果表明配对共享方法具有较大可行性。     

光电传感器在停车场车位信息指示系统中的应用

车辆的增加和停车场的停车位的数量缺少,使得北京繁华地区停车难。有空车位信息指示系统的停车场可以提高停车场的使用效率,特别是车位引导指示和空车位数量显示功能。本文从总体设计、传感器设计及其调理电路、地标引导灯、车位显示进行了论述,并在实际应用中得到了验证。     

基于二段多项式的窄空间平行泊车路径规划方法

针对窄空间平行泊车路径规划问题, 提出一种基于二段五阶多项式的方法分别计算车辆前进路线与倒车路线, 其中前进路线用于调整车辆位姿, 实现倒车入库路径曲率最优. 根据常规停车位大小与家庭轿车的尺寸建立仿真环境, 结合车辆运动模型, 搜索自由空间内无碰撞路径. 仿真结果表明, 二段五阶多项式法可以实现在有限空间范围内的智能泊车, 且在由两段路径连接得到的路径上方向盘转向角连续变化.     

城市停车场实时车位获取与分配研究

以实时获取空余车位和智慧分配车位为目标,基于射频识别技术和地理信息技术开发智慧停车系统原型。采用模糊决策矩阵,定量化驾驶员从当前位置到停车场的驾驶时间、停车费用、停车场至目的地的步行距离和停车场的空余车位数这4个车位分配影响因素的权重;在考虑空余车位有限和实时交通状况的前提下,提出带有4个条件矩阵的车位分配模型,并利用某市道路网、交通状况、停车场等数据在ArcGIS中进行模型实验,实验结果表明,该智慧停车系统具有一定的可行性和实际意义。     

基于Ibeacon的室内智能停车导航系统

随着无线技术的发展以及位置读物需求的多样化发展,在大型室内停车场的应用场景中,用户对于基于位置服务的需求更加迫切。同时,私家车数量的渐进式增长,后续所造成的一系列城市停车难现象,比如地下停车场结构环境复杂、车库内车辆交通混乱、停车场管理效率低下以及驾驶员停泊车过程中所用时间过长等问题,使得人们迫切需要一种良好的解决方案。而现如今主流的GPS导航由于穿透性不佳导致在室内无法发挥其正常作用。最近比较流行的Wi-Fi室内定位技术也同样存在因室内环境的多变性和复杂性导致信号传输不稳定的难题。然而,随着Bluetooth-4.0时代的来临,其低功耗、抗干扰和低成本的特点弥补了这一缺口。针对以上问题,文中设计开发了一个基于Ibeacon的室内智能停车导航小程序。该设计与应用将通过Matlab图像处理、Ibeacon定位等技术的应用来帮助用户更方便、更快捷地找到自己的停车位,大大提高了用户的便利性。同时也改善了停车场的管理效率和帮助停车场进行电子数据统计和分析,从而达到双赢的局面。     

基于Web GIS的智能共享汽车系统

近十年伴随着互联网技术和GIS技术的快速发展,以及人们生活水平的显著提高,共享汽车的智能化和人性化是一个趋势。通过研究某App在某块区域的车位,车流量等信息,建立了一个基于Web GIS的智能共享汽车系统,该系统将Python爬虫,HTML,C#等相联系,通过对于获得的共享汽车位置进行时空大数据分析,得出该区域内的热点地段,并给予商家一些关于调整车位,车辆数量等建议。     

Adaptive control system for car parking

In the paper, the first results of the work on the development and implementation of an adaptive control system for car parking are presented. The proposed approach to construction of a car control system differs from the commonly accepted approach [1–3] and is based on the autonomous adaptive control method [4] developed by the research team headed by A.A. Zhdanov. In the framework of this method, car control and training and retraining of the control system are implemented in one process with satisfaction of all necessary conditions and constraints. This allows the control system to adjust to parameters of a particular car and to automatically readjust if these parameters vary in the course of the car usage. In the paper, a program modeling car parking based on the principles developed in this study is described. Examples of parking a car for some particular cases of mutual location of obstacles and the desired slot in the parking place are presented.     

考虑用户偏好和平台收益的共享泊位分配模型

与机动车数量激增类似,泊位短缺也是导致城市交通拥堵主要问题之一,在不增加车位的情况下提高泊车位利用率也是解决交通拥堵的一种方法。针对城市“泊车难”和部分泊车场利用率较低的问题,考虑了用户的偏好特征,研究了一种具有用户偏好的泊车位共享策略。考虑存在三种不同的泊车方式,在中央商务区（CBD）等待泊车、共享私人泊位、共享公共泊位,运用累积前景理论分析用户的泊车成本,发现用户在不同情形下的选择存在差异。平台通过对关键路径法修改,采用了偏好分组法进行分配。算例对偏好分组的结果与采用关键路径法的分配结果进行了比较,结果表明,基于偏好分组法的分配满足了更多的用户需求,平台收益更高,为管理者提供决策参考。     

Autonomous Vehicle Emergency Recovery Tool: A Cooperative Robotic System for Car Extraction

Vehicles have been proven to be an ideal means for terrorists because they can be meticulously prepared well in advance before being deployed in urban and public places. To increase the risk and burden of explosive ordnance disposal teams, third‐party vehicles have also been used to block the access path to the explosive loaded vehicle. In this paper, we present a multirobot system that can remove vehicles from confined spaces with delicate handling, swiftly and in any direction to a safer disposal point. The new lifting robots, capable of omnidirectional movement, autonomously underride the identified vehicle and dock to its wheels for a synchronized lifting and extraction. The validity and efficiency of the novel robotic system is illustrated via experiments in an indoor parking lot, demonstrating successful autonomous navigation, docking, lifting, and extraction of a conventional car for a total covered distance of 20 m.     

无线磁阻传感器网络停车检测技术研究

随着机动车保有量的高速增长,停车混乱问题日益严重,各大中城市对停车实时监控及管理有迫切的建设需求。为了构建基于无线传感器网络的大规模、低成本、低功耗的停车管理系统,本文基于磁场干扰车辆检测原理,提出了一种停车检测算法,实际应用表明该算法车辆检测精度高,达到了设计要求。     

Using computer simulation to determine operations policies for a mechanised car park

Using mechanised car parks to solve increasing parking demands is a relatively new concept. Processing a high number of clients each day ensures profitability, therefore time effective service which depends on efficient equipment and operations is vital for optimum car storage and retrieval. In focusing on a mechanised car park of known design characteristics (in the design phase) we identify factors that affect its operation, and use a discrete-event simulation model to evaluate proposed operations policies for efficiency. Simulation is shown to be a powerful tool for resolving complex, stochastic real-world problems.     

Sitting and sizing of aggregator controlled park for plug-in hybrid electric vehicle based on particle swarm optimization

Environmental constraints, high and unstable fuel prices, limitation on fuel resources have led to emergence of Plug-in Hybrid Electric Vehicles (PHEVs). In order to launch the regulation service for grid-use of electric-drive vehicles, a smart control interface called an aggregator between the grid and the vehicles has been developed. In this paper, a particle swarm optimization (PSO), as well as its modified version (MPSO) based approach is presented for optimal sitting and sizing of aggregator controlled public car park for vehicle fleets in modern power system, which is convenient to the optimal charger control of PHEVs. The optimal location and sizing is calculated by minimizing the power loss and voltage deviations. The proposed approach is tested on IEEE 14 bus system.     

GSM网络在车位管理系统中的应用

针对日益增加的私家车辆所带来的“停车难”问题,设计了一种基于GSM网络的停车场车位管理系统.通过车位控制器的方式实现对车位状态的监控,系统通信主节点采用RS485总线的方式将各个车位节点的状态收集起来,并且通过GSM通信网络传送给管理主机,管理主机接收来自各通信主节点发送的车位信息,从而实现对邻近公共停车场状态的统一调...