智能停车管理系统,动态定价

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Ambient Intelligence and Smart Environments Pub Date : 2021-11-09 DOI:10.3233/ais-210615
Md Ashifuddin Mondal, Z. Rehena, M. Janssen
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引用次数: 2

摘要

智能停车正日益成为智慧城市倡议的重要组成部分。利用和管理停车场是一项具有挑战性的任务,因为空间通常有限,很难找到空置的空间,而市民希望将车辆停在他们喜欢的地方附近。在高峰时段,这种情况在大城市的重要/豪华地区变得更糟。由于没有合适的停车管理系统,市民不得不四处游荡,以找到一个合适的停车区域。这导致宝贵时间的浪费,不必要的燃料消耗和环境污染。提出了一种基于多准则车位预约算法(MCPR)的智能停车管理系统(SPMS),该系统允许驾驶员/车主在任何时间、任何地点找到并预约最合适的停车位。该系统还考虑了动态定价策略的概念来计算停车收费,以便政府机构和私人投资者获得更多的收入。该系统利用传感器计算停车场的浓度指数、平均车辆间隔时间,以便更好地管理和规划停车。仿真结果表明,该系统减少了用户寻找停车位所需的平均额外驾驶,从而减少了交通拥堵,从而减少了由于寻找合适的停车位而不必要的驾驶所造成的空气污染。
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Smart parking management system with dynamic pricing
Smart parking is becoming more and more an integral part of smart city initiatives. Utilizing and managing parking areas is a challenging task as space is often limited, finding empty spaces are hard and citizens want to park their vehicles close to their preferred places. This becomes worse in important/posh areas of major metropolitan cities during rush hour. Due to unavailability of proper parking management system, citizens have to roam around a lot in order to find a suitable parking area. This leads to the wastage of valuable time, unnecessary fuel consumption and environmental pollution. This paper proposes a smart parking management system (SPMS) based on multiple criteria based parking space reservation algorithm (MCPR) that allows the driver/owner of vehicles to find and reserve most appropriate parking space from anywhere at any time. The system also considers the concept of dynamic pricing strategy for calculating parking charge in order to gain more revenue by the government agencies as well as private investors. The system employs sensors to calculate concentration index, average inter-arrival time of vehicles of a parking area for better parking management and planning. The simulation results show that proposed system reduces the average extra driving required by the users to find a parking area and hence it will reduce traffic congestion, which in turn reduces air pollution caused by unnecessary driving to find a proper parking area.
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来源期刊
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
4.30
自引率
17.60%
发文量
23
审稿时长
>12 weeks
期刊介绍: The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.
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