5 research outputs found

    The Implementation of Smart Mobility for Smart Cities: A Case Study in Qatar

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    This paper contributes to building a systematic view of the mobility characteristics of smart cities by reviewing the lessons learned from the best practices implemented around the world. The main features of smart cities, such as smart homes, smart infrastructure, smart operations, smart services, smart utilities, smart energy, smart governance, smart lifestyle, smart business, and smart mobility in North America, Asia, and Europe are briefly reviewed. The study predominantly focuses on smart mobility features and their implications in newly built smart cities. As a case study, the modern city of Lusail located in the north of Doha, Qatar is considered. The provision of car park management and guidance, real-time traffic signal control, traffic information system, active-modes arrangement in promenade and busy urban avenues, LRT, buses, taxis, and water taxis information system, and multimodal journey planning facilities in the Lusail smart city is discussed in this study. Consequently, the implications of smart mobility features on adopting Intelligent Transportation Systems (ITS) will be studied. The study demonstrates that the implementation of Information and Communication Technologies (ICT) when supported by Intelligent Transportation Systems (ITS), could result in making the most efficient use of existing transportation infrastructure and consequently improve the safety and security, mobility, and the environment in urban areas. The findings of this study could be considered an initial step in the implementation of Mobility-as-a-Service (MaaS) in cities with advanced public transportation such as Doha, the capital of Qatar. Doi: 10.28991/CEJ-2022-08-10-09 Full Text: PD

    Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

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    The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments

    Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

    No full text
    The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments

    Three essays on urban freight transport: models and tools for effective city logistics projects

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    The main purpose of these three years of research, summarized in this thesis, was to investigate the obstacles to the development of the city logistics initiatives by seeking solutions to overcome them through model and framework coming from management and transportation engineering. In particular, following a first analysis of a collection of European projects and a systematic analysis of scientific literature, three main gaps in city logistics have been identified: the lack of the stakeholders’ involvement, the need for data sharing platforms to overcome the current lack of data and the need to define city logistics solutions within the urban ecosystem, making consistent design choices coherently with what is already existing in terms of infrastructures, rules and stakeholders in the context. From these three gaps, three main research questions have arisen: (RQ1) Is it possible to support stakeholders in analysing CL solutions fitting their necessities applying some already existing and consolidate decision-making methods? (RQ2) Is it possible to define a database platform in which it is possible to collect, consult and update as many existing data as possible regarding urban freight transport? (RQ3) How is it possible to optimize city logistics infrastructures in a harmonious and coherent way with respect to the entire city logistics ecosystem? To answers to the research questions, a collection of articles is illustrated in this thesis work. From time to time different methodologies are used and illustrated, derived from the field of management and transport engineering, these different methodologies, such as the Systematic Literature Review, the House of Quality, a framework for building a data sharing platform, the city logistics Ecosystem and a decision-making support model (based on both a covering model and a Monte Carlo simulation) are described in detail in the various chapters of the thesis. In this dissertation work for the first time, the main obstacles to the development of city logistics initiatives, that are the lack of involvement of stakeholders, the lack of data, and the lack of an ecosystem vision of urban transport, have been identified and addressed at the same time. Even if literature sometimes offers some possible solutions to these gaps, few are simple to understand for those who work in the urban freight transport industry, easy to apply and replicable. Both in identifying the gap and in seeking solutions, the solutions showed in this thesis sought to address to those who work in the industry, mainly carriers, retailers, shop owners and public administration representatives, trying to combine scientific research with the search for solutions that can be implemented in practice as requested by such a practical research topic. For this reason, each proposed solution and methodology in this thesis has been implemented and experimented using as a case study the city of Bergamo (and testing its replicability in other European cities such as Saint-Etienne, Luxemburg and Amsterdam). In particular, the initial experience in the “Bergamo Logistica” project, part of the Bergamo 2.035 smart city research program, gave me the opportunity to understand the main critical issues found by the main actors who work in this field (i.e., carriers, couriers, retailers and institutions), to confirm some evidences that I found in the theory (i.e., main research gaps which originates the research questions) and to search for solutions that could both solve research gaps and optimize the daily logistics activities of the operators.The main purpose of these three years of research, summarized in this thesis, was to investigate the obstacles to the development of the city logistics initiatives by seeking solutions to overcome them through model and framework coming from management and transportation engineering. In particular, following a first analysis of a collection of European projects and a systematic analysis of scientific literature, three main gaps in city logistics have been identified: the lack of the stakeholders’ involvement, the need for data sharing platforms to overcome the current lack of data and the need to define city logistics solutions within the urban ecosystem, making consistent design choices coherently with what is already existing in terms of infrastructures, rules and stakeholders in the context. From these three gaps, three main research questions have arisen: (RQ1) Is it possible to support stakeholders in analysing CL solutions fitting their necessities applying some already existing and consolidate decision-making methods? (RQ2) Is it possible to define a database platform in which it is possible to collect, consult and update as many existing data as possible regarding urban freight transport? (RQ3) How is it possible to optimize city logistics infrastructures in a harmonious and coherent way with respect to the entire city logistics ecosystem? To answers to the research questions, a collection of articles is illustrated in this thesis work. From time to time different methodologies are used and illustrated, derived from the field of management and transport engineering, these different methodologies, such as the Systematic Literature Review, the House of Quality, a framework for building a data sharing platform, the city logistics Ecosystem and a decision-making support model (based on both a covering model and a Monte Carlo simulation) are described in detail in the various chapters of the thesis. In this dissertation work for the first time, the main obstacles to the development of city logistics initiatives, that are the lack of involvement of stakeholders, the lack of data, and the lack of an ecosystem vision of urban transport, have been identified and addressed at the same time. Even if literature sometimes offers some possible solutions to these gaps, few are simple to understand for those who work in the urban freight transport industry, easy to apply and replicable. Both in identifying the gap and in seeking solutions, the solutions showed in this thesis sought to address to those who work in the industry, mainly carriers, retailers, shop owners and public administration representatives, trying to combine scientific research with the search for solutions that can be implemented in practice as requested by such a practical research topic. For this reason, each proposed solution and methodology in this thesis has been implemented and experimented using as a case study the city of Bergamo (and testing its replicability in other European cities such as Saint-Etienne, Luxemburg and Amsterdam). In particular, the initial experience in the “Bergamo Logistica” project, part of the Bergamo 2.035 smart city research program, gave me the opportunity to understand the main critical issues found by the main actors who work in this field (i.e., carriers, couriers, retailers and institutions), to confirm some evidences that I found in the theory (i.e., main research gaps which originates the research questions) and to search for solutions that could both solve research gaps and optimize the daily logistics activities of the operators

    Smart Sensor Technologies for IoT

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    The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed. Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications. This Special Issue, “Smart Sensor Technologies for IoT” aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT
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