scholarly journals Transport Inequalities and the Adoption of Intelligent Transportation Systems in Africa: A Research Landscape

2021 ◽  
Vol 13 (22) ◽  
pp. 12891
Author(s):  
Olasupo O. Ajayi ◽  
Antoine B. Bagula ◽  
Hloniphani C. Maluleke ◽  
Isaac A. Odun-Ayo
Keyword(s):  
Systematic Review ◽  
Information And Communication Technologies ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Western World ◽  
Smart Transportation ◽  
African Cities ◽  
The Impact

Intelligent Transportation Systems (ITS), also known as Smart Transportation, is an infusion of information and communication technologies into transportation. ITS are a key component of smart cities, which have seen rapid global development in the last few decades. This has in turn translated to an increase in the deployment and adoption of ITS, particularly in countries in the Western world. Unfortunately, this is not the case with the developing countries of Africa and Asia, where dilapidated road infrastructure, poorly maintained public/mass transit vehicles and poverty are major concerns. However, the impact of Westernization and “imported technologies” cannot be overlooked; thus, despite the aforementioned challenges, ITS have found their way into African cities. In this paper, a systematic review was performed to determine the state of the art of ITS in Africa. The output of this systematic review was then fed into a hybrid multi-criteria model to analyse the research landscape, identify connections between published works and reveal research gaps and inequalities in African ITS. African peculiarities inhibiting the widespread implementation of ITS were then discussed, followed by the development of a conceptual architecture for an integrated ITS for African cities.

scholarly journals Special Issue “New Perspectives in Intelligent Transportation Systems and Mobile Communications towards a Smart Cities Context”

2019 ◽  
Vol 11 (11) ◽  
pp. 228 ◽  
Author(s):  
Giovanni Pau ◽  
Alessandro Severino ◽  
Antonino Canale
Keyword(s):  
Information And Communication Technologies ◽  
Mobile Communications ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Autonomous Driving ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Special Issue ◽  
Technical Problems ◽  
Information And Communication

Intelligent transportation solutions and smart information and communication technologies will be the core of future smart cities. For this purpose, these topics have captivated noteworthy interest in the investigation and construction of cleverer communication protocols or the application of artificial intelligence in the connection of in-vehicle devices by wireless networks, and in in-vehicle services for autonomous driving using high-precision positioning and sensing systems. This special issue has focused on the collection of high-quality papers aimed at solving open technical problems and challenges typical of mobile communications for Intelligent Transportation Systems.

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

scholarly journals Blockchain-based Reputation for Intelligent Transportation Systems

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 791 ◽  
Author(s):  
Liviu-Adrian Hîrţan ◽  
Ciprian Dobre ◽  
Horacio González-Vélez
Keyword(s):  
Internet Of Things ◽  
San Francisco ◽  
Intelligent Transportation Systems ◽  
Routing Algorithm ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Information ◽  
Disruptive Technology ◽  
Average Speed ◽  
The Impact

A disruptive technology often used in finance, Internet of Things (IoT) and healthcare, blockchain can reach consensus within a decentralised network—potentially composed of large amounts of unreliable nodes—and to permanently and irreversibly store data in a tamper-proof manner. In this paper, we present a reputation system for Intelligent Transportation Systems (ITS). It considers the users interested in traffic information as the main actors of the architecture. They securely share their data which are collectively validated by other users. Users can choose to employ either such crowd-sourced validated data or data generated by the system to travel between two locations. The data saved is reliable, based on the providers’ reputation and cannot be modified. We present results with a simulation for three cities: San Francisco, Rome and Beijing. We have demonstrated the impact of malicious attacks as the average speed decreased if erroneous information was stored in the blockchain as an implemented routing algorithm guides the honest cars on other free routes, and thus crowds other intersections.

scholarly journals REDUCING THE TIME TO GET EMERGENCY ASSISTANCE FOR ACCIDENT VEHICLES ON THE ROAD THROUGH AN INTELLIGENT TRANSPORTATION SYSTEM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 827-832
Author(s):  
A. H. Nourbakhsh ◽  
M. R. Delavar ◽  
M. Jadidi ◽  
B. Moshiri
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Dijkstra Algorithm ◽  
Notification System ◽  
Smart Transportation ◽  
The Road ◽  
On The Road

Abstract. Intelligent Transportation Systems (ITS) is one of the main components of a smart city. ITS have several purposes including the increase of the safety and comfort of the passengers and the reduction of the road accidents. ITS can enhance safety in three modes before, within and after the collision by preventing accident via assistive system, sensing the collision situation and calculating the time of the collision and providing the emergency response in a timely manner. The main objective of this paper is related to the smart transportation services which can be provided at the time of the collision and after the accident. After the accident, it takes several minutes to hours for the person to contact the emergency department. If an accident takes place for a vehicle in a remote area, this time increases and that may cause the loss of life. In addition, determination of the exact location of the accident is difficult by the emergency centres. That leads to the possibility of erroneous responder act in dispatching the rescue team from the nearest hospital. A new assistive intelligent system is designed in this regard that includes both software and hardware units. Hardware unit is used as an On-Board Unit (OBU), which consists of GPS, GPRS and gyroscope modules. Once OBU detects the accident, a notification system designed and connected to OBU will sent an alarm to the server. The distance to the nearest emergency center is calculated using Dijkstra algorithm. Then the server sends a request for assistance to the nearest emergency centre. The proposed system is developed and tested at local laboratory conditions. The results show that this system can reduce Ambulance Arrival Time (AAT). The preliminary results and architecture of the system have been presented. The inclination angle determined by the proposed system along with the car position identified by the installed GPS sensor assists the crash/accident warning part of the system to send a help request to the nearest road emergency centre. These results verified that the probability of having a remote and smart car crash/accident decision support system using the proposed system has been improved compared to that of the existing systems.

scholarly journals Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6309
Author(s):  
Mohammad Peyman ◽  
Pedro J. Copado ◽  
Rafael D. Tordecilla ◽  
Leandro do C. Martins ◽  
Fatos Xhafa ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Edge Computing ◽  
Analytical Models ◽  
Current Status ◽  
Ride Sharing ◽  
The City

With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing.These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.

scholarly journals Routing and Mobility Management in the Internet of Things

2020 ◽  
Author(s):  
Bruno Pereira Santos ◽  
Luiz Filipe Menezes Vieira ◽  
Antonio Alfredo Ferreira Loureiro
Keyword(s):  
Internet Of Things ◽  
Mobility Management ◽  
Intelligent Transportation Systems ◽  
Computer Network ◽  
Smart Cities ◽  
Transportation Systems ◽  
The Internet ◽  
Research Areas ◽  
New Research ◽  
The Impact

This Ph.D. Thesis proposes new techniques for routing and mobility management for Internet of Things (IoT). In the future IoT, everyday mobile objects will probably be connected to the Internet. Currently, static IoT's devices have already been connected, but handle mobile devices suitably still being an open issue in IoT context. Then, solutions for routing mobility detection, handover, and mobility management are proposed through an algorithm that integrates Machine Learning (ML) and mobility metrics to figure out devices' mobility events, which we named Dribble. Also, an IPv6 hierarchical routing protocol named Mobile Matrix to boost efficient (memory and fault tolerance) end-to-end connectivity over mobility scenarios. The Thesis contributions are supported by numerous peer-reviewed publications in national and international conferences and journals included in ISI-JCR. Also, the applicability of this Thesis is evident by showing that our results overcome state-of-the-art in static and mobile scenarios, as well as, the impact of the proposed solutions is a step forward in at least two new research areas so-called Internet of Mobile Things (IoMT) and Social IoT, where devices move around and do social ties respectively. Moreover, during the Ph.D. degree, the author has contributed to different computer network fields rather than routing by publishing in areas like social networks, smart cities, intelligent transportation systems, software-defined networks, and parallel computing.

scholarly journals Visualization of Urban Mobility Data from Intelligent Transportation Systems

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 332 ◽  
Author(s):  
Thiago Sobral ◽  
Teresa Galvão ◽  
José Borges
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Urban Mobility ◽  
Multiple Perspectives ◽  
Data Types ◽  
Mobility Data ◽  
Extensive Body ◽  
Visualization Techniques

Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings.

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