Offering a Method to Find the Most Proper Parking Space in the City Automobile Expediency Network by Genetic Algorithm

Finding a free space for parking in rush hours and heavy traffic has been always a boring and time-consuming problem for drivers. Recently, VANET networks have found special attention among economists and university researchers. Due to day-by-day expansion of wireless communicative systems, many car manufacturers have been installing such communicative tools as OBU on their products. The RSU tools give drivers the possibility to have better and more convenient means of communication. They can trace the availability of parking spaces using these tools and be guided to there, while the automobiles can be equipped with anti-burglar systems to have a higher security. In this research, a comprehensive method using the genetic algorithm have been offered to find a place for parking in the automobile expediency network, which has considered many parameters such as parking space being located near or far, cost of parking space for drivers, the probability of parking space remaining available until the car arrives and reduced past defects as much as possible.Пошук вільного місця для стоянки в години пік завжди є проблемою для водіїв. Останнім часом суб'єкти економіки та університети приділяють особливу увагу мережам VANET. Зважаючи на постійний розвиток бездротових комунікаційних систем, чимало виробників автомобілів встановлюють на свою продукцію комунікатори, зокрема такі як, бортові пристрої обробки даних (onboard units, OBU), а придорожні пристрої (roadside units, RSU) забезпечують водіям зручний спосіб комунікації між собою. За допомогою цих інструментів водії можуть відстежувати наявність місць для паркування і маршрут до них. Окрім того, з метою підвищення безпеки вони передбачають встановлення захисних систем проти зламу. У роботі запропоновано комплексний метод на основі генетичного алгоритму для пошуку вільного паркувального місця в міській мережі автостоянок. Зазначений метод враховує значну кількість параметрів, зокрема таких як відстань до стоянки, вартість місця для паркування, ймовірність того, що місце залишиться вільним до прибуття на стоянку, а також передбачає вдосконалення роботи завдяки усуненню попередніх недоліків.Поиск свободного места для стоянки в час пик всегда является проблемой для водителей. В последнее время субъекты экономики и университеты уделяют особое внимание сетям VANET. Учитывая постоянное развитие беспроводных коммуникационных систем, значительно количество изготовителей автомобилей устанавливают на свою продукцию коммуникаторы, в частности такие как бортовые устройства обработки данных (onboard units, OBU), а придорожные устройства (roadside units, RSU) обеспечивают водителям удобный способ коммуникации между собой. При помощи этих инструментов водители могут отслеживать наличие места для парковки и маршрут к ним. Кроме того, с целью повышения безопасности они предусматривают установку защитных систем против взлома. В работе предложен комплексный метод для поиска свободного места для парковки в городской сети автостоянок, который использует генетический алгоритм. метод учитывает множество параметров, в частности таких как расстояние до стоянки, стоимость места для парковки, вероятность того, что место останется свободным до прибытия на стоянку, а также предусматривает усовершенствование работы благодаря ликвидации предыдущих недостатков

An App for parking with indoor navigation facility

There are numerous parking supervision and random booking procedures that regulate parking operations. Travel time to the parking slot and walking time inside the terminus can still be dropped if the parker can book a precise parking spot instead of an arbitrary one. This is achieved by our proposal, called sPark which is an app-based parking method that includes indoor navigation facility i.e., an app for parking with indoor navigation facility. sPark’s sharing system will rapidly book the optimal parking slots for parkers and advise them on the best feasible entrances for practice. Also, parkers will find the briefest path to their target using our proposed app’s navigation technique, saving them a lot of time roaming to the building. Different parking methods like sPark (our proposed), non-directed and directed methods (existing) are designed and assessed. The designed and assessed simulation outcomes of sPark indicate an important decrease in the overall driving time by 30% to 60% as compared to the non-directed method which is an existing method. Additionally, the resource sharing module in our scheme i.e., an app for parking with indoor navigation facility called sPark has revealed a 9.99% decrease in driving time in comparison to directed methods (existing) that feature interior cruising and direction only

Sharing with Caution: Managing Parking Spaces in Vehicular Networks

By exchanging events in a vehicular ad hoc network (VANET), drivers can receive interesting information while driving. For example, they can be informed of available parking spaces in their vicinity. A suitable protocol is needed to disseminate the events efficiently within the area where they are relevant. Moreover, in such a competitive context where each vehicle may be interested in a resource, it is crucial not to communicate that resource to each driver in the vicinity. Otherwise, those drivers would waste time trying to reach a parking space and only one of them would be fulfilled, which would lead to a poor satisfaction in the system. To solve this problem, we detail in this paper a reservation protocol that efficiently allocates parking spaces in vehicular ad hoc networks and avoids the competition among the vehicles. We have integrated our protocol within VESPA, a system that we have designed for vehicles to share information in VANETs. An experimental evaluation is provided, which proves the usefulness and benefits of our reservation protocol in both parking lots and urban scenarios. Besides, we present an in-depth study of the state of the art on this topic, that shows the interest and the originality of our approach

A Practical Review to Support the Implementation of Smart Solutions within Neighbourhood Building Stock

The construction industry has witnessed an increase in the use of digital tools and smart solutions, particularly in the realm of building energy automation. While realising the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, which are considered critical urban development units. To support the interplay of smart solutions between buildings and neighbourhoods, this study aimed to collect and review all the smart solutions presented in existing scientific articles, the technical literature, and realised European projects. These solutions were classified into two main sections, buildings and neighbourhoods, which were investigated through five domains: building-energy-related uses, renewable energy sources, water, waste, and open space management. The quantitative outcomes demonstrated the potential benefits of implementing smart solutions in areas ranging from buildings to neighbourhoods. Moreover, this research concluded that the true enhancement of energy conservation goes beyond the building’s energy components and can be genuinely achieved by integrating intelligent neighbourhood elements owing to their strong interdependencies. Future research should assess the effectiveness of these solutions in resource conservation

A Survey of Smart Parking Solutions

International audienceConsidering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000-2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Lastly, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture

Factors influencing urban on-street parking search time using a multilevel modelling approach

Vehicles searching for on-street parking create environmental and economic externalities through increasing network traffic flow and congestion, heightening pollutant emission levels, creating additional noise, giving rise to time delays for through vehicles, and leading to potential safety hazards caused by vehicles manoeuvring into or out of on-street spaces. Despite extensive negative impacts on individual drivers and on society, parking search is an under-researched area, particularly in more recent years and within the UK. Furthermore, current statistical modelling techniques applied to parking search time have not utilised a more comprehensive analysis in which hierarchically structured data on multiple levels could be addressed. The aim of this thesis, therefore, is to investigate and compare the factors that influence drivers urban on-street parking search time and its policy implications. A mixed methods approach was applied that comprised qualitative interviews conducted with local government authority Council Officers and a quantitative revealed preference on-street parking survey (sample size, 1,002 observations) undertaken in four cities in the East Midlands region of the UK in order to obtain individual driver-level socio-economic and other parking related factors that may influence parking search time. Statistically significant variables for each of the cities were identified by employing separate linear regression models. A multilevel mixed-effects model in which drivers (Level 1) are nested within streets (Level 2) was then applied to the pooled dataset. Significant factors in the multilevel (street level) model were identified as: time of arrival at a parking place (for which every time period after the 07:00-07:59 reference case indicated increased search time); parking habit; parking tariff; the number of parking places previously visited (on the same trip); trip time from origin to parking place; area type; trip purpose; weather; vehicle type; and walking time from a parking place to a destination. Comparison of the factors that influence parking search time revealed important differences in statistically significant variables and coefficient values between the single-level and multilevel regression modelling approaches. Policy recommendations based upon the findings of the parking survey, modelling analysis, and further interviews conducted with local authority Council Officers, focus around time of arrival at a parking place, area type, parking charges and the potential technological advances that, if implemented, could have a considerable effect on parking search times within urban areas. Robust data collection and subsequent monitoring of parking search activity within each city should be undertaken in order to provide an evidence base which would support the introduction of future policy measures to reduce parking search activity