scholarly journals DEMO - A Simulation Framework for Multi-modal Commuting and Parking Optimization.

10.29007/94j5 ◽  
2019 ◽  
Author(s):  
Lara Codeca ◽  
Jérôme Härri ◽  
Jakob Erdmann
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
State Of The Art ◽  
Smart Cities ◽  
Ease Of Use ◽  
Sustainable Growth ◽  
Simulation Framework ◽  
Smart Mobility

In the last decade, many efforts to solve traffic congestion and sustainable growth issues are going in the direction of research and investments in smart cities and consequently smart mobility.We use the proposed simulation framework is compatible with SUMO 1.1.0. We use it to study multi-modal commuting and parking optimization issues in a state-of-the-art large-scale mobility scenario, and we intend to demonstrate the ease of use and its capabilities.

scholarly journals Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2143
Author(s):  
Sara Paiva ◽  
Mohd Abdul Ahad ◽  
Gautami Tripathi ◽  
Noushaba Feroz ◽  
Gabriella Casalino
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
City Planning ◽  
Smart Cities ◽  
The Sustainable Development ◽  
Current Trends ◽  
Enabling Technologies ◽  
Entry Points ◽  
Development Goals ◽  
Smart Mobility

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

scholarly journals A New Approach of Smart Mobility for Heavy Goods Vehicles in Casablanca

2021 ◽  
Author(s):  
Mohammed Mouhcine Maaroufi ◽  
Laila Stour ◽  
Ali Agoumi
Keyword(s):  
Environmental Sustainability ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Research Work ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Smart Mobility ◽  
Heavy Goods Vehicles

Managing mobility, both of people and goods, in cities is a thorny issue. The travel needs of urban populations are increasing and put pressure on transport infrastructure. The Moroccan cities are no exception and will struggle, in the short term, to respond to the challenges of the acceleration of the phenomenon of urbanization and the increase in demand for mobility. This will inevitably prevent them from turning into smart cities. The term smart certainly alludes to better use of technologies, but smart mobility is also defined as “a set of coordinated actions intended to improve the efficiency, effectiveness and environmental sustainability of cities” [1]. The term mobility highlights the preponderance of humans over infrastructure and vehicles. Faced with traffic congestion, the solutions currently adopted which consist of fitting out and widening the infrastructures, only encourage more trips and report the problem with more critical consequences. It is true that beyond a certain density of traffic, even Intelligent Transport Systems (ITS) are not useful. The concept of dynamic lane management or Advanced Traffic Management (ATM) opens up new perspectives. Its objective is to manage and optimize road traffic in a variable manner, in space and in time. This article is a summary of the development of a road infrastructure dedicated to Heavy Goods Vehicles (HGV), the first of its kind in Morocco. It aims to avoid the discomfort caused by trucks in the urban road network of the city of Casablanca. This research work is an opportunity to reflect on the introduction of ITS and ATM to ensure optimal use of existing infrastructure before embarking on heavy and irreversible infrastructure projects.

scholarly journals Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome

2021 ◽  
Author(s):  
Saghar Kaabinejadian ◽  
Carolina Barra ◽  
Bruno Alvarez ◽  
Hooman Yari ◽  
William Hildebrand ◽  
...  
Keyword(s):  
Large Scale ◽  
Vaccine Development ◽  
State Of The Art ◽  
Hla Class I ◽  
Class Ii ◽  
Ease Of Use ◽  
Hla Dr ◽  
Generation Vaccine ◽  
Major Bottleneck ◽  
Epitope Discovery

Mass spectrometry (MS) based immunopeptidomics is used in several biomedical applications including neo-epitope discovery in oncology and next-generation vaccine development. Immunopeptidome data are highly complex given the expression of multiple HLA alleles on the cell membrane and presence of co-immunoprecipitated contaminants. The absence of tools that accurately deal with these challenges is currently a major bottleneck for the large-scale application of this technique. Here, we present the MHCMotifDecon that benefits from state-of-the-art HLA class-I and class-II predictions to accurately deconvolute immunopeptidome datasets and assign individual ligands to the most likely HLA allele while discarding co-purified contaminants. We have benchmarked the tool against other state-of-the-art methods and illustrated its application on experimental datasets for HLA-DR demonstrating a previously underappreciated role for HLA-DRB3/4/5 molecules in defining HLA class II immune repertoires. With its ease of use MHCMotifDecon can efficiently guide interpretation of immunopeptidome datasets, serving the discovery of novel T cell targets.

scholarly journals Smart Cities of the Future as Cyber Physical Systems: Challenges and Enabling Technologies

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3349
Author(s):  
Antonio Puliafito ◽  
Giuseppe Tricomi ◽  
Anastasios Zafeiropoulos ◽  
Symeon Papavassiliou
Keyword(s):  
Quality Of Life ◽  
Social Services ◽  
Smart City ◽  
Large Scale ◽  
Smart Cities ◽  
Social Systems ◽  
Sustainable Growth ◽  
Information And Communications Technology ◽  
Urban Issues

A smart city represents an improvement of today’s cities, both functionally and structurally, that strategically utilizes several smart factors, capitalizing on Information and Communications Technology (ICT) to increase the city’s sustainable growth and strengthen the city’s functions, while ensuring the citizens’ enhanced quality of life and health. Cities can be viewed as a microcosm of interconnected “objects” with which citizens interact daily, which represents an extremely interesting example of a cyber physical system (CPS), where the continuous monitoring of a city’s status occurs through sensors and processors applied within the real-world infrastructure. Each object in a city can be both the collector and distributor of information regarding mobility, energy consumption, air pollution as well as potentially offering cultural and tourist information. As a consequence, the cyber and real worlds are strongly linked and interdependent in a smart city. New services can be deployed when needed, and evaluation mechanisms can be set up to assess the health and success of a smart city. In particular, the objectives of creating ICT-enabled smart city environments target (but are not limited to) improved city services; optimized decision-making; the creation of smart urban infrastructures; the orchestration of cyber and physical resources; addressing challenging urban issues, such as environmental pollution, transportation management, energy usage and public health; the optimization of the use and benefits of next generation (5G and beyond) communication; the capitalization of social networks and their analysis; support for tactile internet applications; and the inspiration of urban citizens to improve their quality of life. However, the large scale deployment of cyber-physical-social systems faces a series of challenges and issues (e.g., energy efficiency requirements, architecture, protocol stack design, implementation, and security), which requires more smart sensing and computing methods as well as advanced networking and communications technologies to provide more pervasive cyber-physical-social services. In this paper, we discuss the challenges, the state-of-the-art, and the solutions to a set of currently unresolved key questions related to CPSs and smart cities.

scholarly journals Blockchain for Smart Mobility—Literature Review and Future Research Agenda

2021 ◽  
Vol 13 (23) ◽  
pp. 13268
Author(s):  
Erik Karger ◽  
Marvin Jagals ◽  
Frederik Ahlemann
Keyword(s):  
Literature Review ◽  
Traffic Congestion ◽  
Research Agenda ◽  
Current Knowledge ◽  
Smart Cities ◽  
Use Cases ◽  
Future Research ◽  
Future Research Agenda ◽  
Information And Communication ◽  
Smart Mobility

Today’s cities face numerous challenges due to climate change and urbanization. The concept of a smart city aims to help cities to address these challenges by adapting modern information and communication technology. Smart mobility and transportation form one important aspect of smart cities. Inefficient mobility in cities can lead to problems such as traffic congestion, which results in frustration for residents and a decrease in the quality of life. Against the backdrop of global warming, cities also strive to reduce CO2 emissions, an attempt which requires sustainable and novel mobility concepts. Blockchain is a current technology, said to have huge potential, that is being investigated for application in many facets of smart cities. In the context of smart mobility, blockchain can be used for transactions relating to ridesharing and electric charging, handling of interactions of platoon members, or serving as a foundation for communication between vehicles. Although initial research about this topic exists, it is distributed among different use-cases and applications. This article conducts a systematic literature review to analyze blockchain’s role in mobility and transportation in smart cities, and its potential to increase efficiency in these areas. With this review, we aim to consolidate and summarize the current knowledge about this topic. As a first result, we present the findings from our literature review, which can be divided into five categories of use-cases. We also present a platform for further research about this emerging topic by identifying promising future research avenues. For this purpose, we derive a future research agenda based on our findings.

scholarly journals Tendencies of Technologies and Platforms in Smart Cities: A State-of-the-Art Review

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Pablo Chamoso ◽  
Alfonso González-Briones ◽  
Sara Rodríguez ◽  
Juan M. Corchado
Keyword(s):  
Smart City ◽  
Large Scale ◽  
New Technologies ◽  
State Of The Art ◽  
Smart Cities ◽  
Clear Understanding ◽  
Smart Systems ◽  
Definition Of

Technology is starting to play a key role in cities’ urban sustainability plans. This is because new technologies can provide them with robust solutions that are of benefit to citizens. Cities aim to incorporate smart systems in their industrial, infrastructural, educational, and social activities. A Smart City is managed with intelligent technologies which allow improving the quality of the services offered to citizens and make all processes more efficient. However, the Smart City concept is fairly recent. The ideas that it encompasses have not yet been consolidated due to the large number of fields and technologies that fit under this concept. All of this led to confusion about the definition of a Smart City and this is evident in the literature. This article explores the literature that addresses the topic of Smart Cities; a comprehensive analysis of the concept and existing platforms is performed. We gain a clear understanding of the services that a Smart City must provide, the technology it should employ for the development of these services, and the scope that this concept covers. Moreover, the shortcomings and needs of Smart Cities are identified and a model for designing a Smart City architecture is proposed. In addition, three case studies have been proposed: the first is a simulator to study the implementation of various services and technologies, the second case study to manage incidents that occur in a Smart City, and the third case study to monitor the deployment of large-scale sensors in a Smart City.

scholarly journals BIG MOBILITY DATA ANALYTICS FOR TRAFFIC MONITORING AND CONTROL

2020 ◽  
Vol 19 (2) ◽  
pp. 087
Author(s):  
Natalija Stojanović ◽  
Dragan Stojanović
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Smart Cities ◽  
Heavy Traffic ◽  
Traffic Monitoring ◽  
Monitoring And Control ◽  
Dynamic Configuration ◽  
Large Cities ◽  
Traffic Lights ◽  
Mobility Data

With the overpopulation of large cities, the problems with citizens’ mobility, transport inefficiency, traffic congestions and environmental pollution caused by the heavy traffic require advanced ITS solutions to be overcome. Recent advances and wide proliferation of mobile and Internet of Things (IoT) devices, carried by people, built in vehicles and integrated in a road infrastructure, enable collection of large scale data related to mobility and traffic in smart cities, still with a limited use in real world applications. In this paper, we propose the traffic monitoring, control and adaptation platform, named TrafficSense, based on Big Mobility Data processing and analytics. It provides a continuous monitoring of a traffic situation and detection of important traffic parameters, conditions and events, such as travel times along the street segments and traffic congestions in real time. Upon detecting a traffic congestion on an intersection, the TrafficSense application leverages the feedback control loop mechanism to provide a traffic adaptation based on the dynamic configuration of traffic lights duration in order to increase the traffic flows in critical directions at the intersections. We tested and evaluated the developed application on the distributed cloud computing infrastructure. By varying the streaming workload and the cluster parameters we show the feasibility and applicability of our approach and the platform.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Yan Pan ◽  
Shining Li ◽  
Qianwu Chen ◽  
Nan Zhang ◽  
Tao Cheng ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Load Capacity ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Promising Alternative ◽  
Logistics Industry ◽  
Last Mile ◽  
Delivery Scheduling ◽  
Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

scholarly journals Large-Scale Road Network Congestion Pattern Analysis and Prediction Using Deep Convolutional Autoencoder

2021 ◽  
Vol 13 (9) ◽  
pp. 5108
Author(s):  
Navin Ranjan ◽  
Sovit Bhandari ◽  
Pervez Khan ◽  
Youn-Sik Hong ◽  
Hoon Kim
Keyword(s):  
Traffic Congestion ◽  
Network Architecture ◽  
Road Network ◽  
Large Scale ◽  
Pattern Analysis ◽  
Image Data ◽  
Urban Life ◽  
Prediction Algorithm ◽  
Rapid Urbanization ◽  
Convolutional Autoencoder

The transportation system, especially the road network, is the backbone of any modern economy. However, with rapid urbanization, the congestion level has surged drastically, causing a direct effect on the quality of urban life, the environment, and the economy. In this paper, we propose (i) an inexpensive and efficient Traffic Congestion Pattern Analysis algorithm based on Image Processing, which identifies the group of roads in a network that suffers from reoccurring congestion; (ii) deep neural network architecture, formed from Convolutional Autoencoder, which learns both spatial and temporal relationships from the sequence of image data to predict the city-wide grid congestion index. Our experiment shows that both algorithms are efficient because the pattern analysis is based on the basic operations of arithmetic, whereas the prediction algorithm outperforms two other deep neural networks (Convolutional Recurrent Autoencoder and ConvLSTM) in terms of large-scale traffic network prediction performance. A case study was conducted on the dataset from Seoul city.

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