scholarly journals DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)

2021 ◽  
Vol 13 (24) ◽  
pp. 13966
Author(s):  
Muhammad Arif ◽  
Venkatesan Dhilip Kumar ◽  
Loganathan Jayakumar ◽  
Ioan Ungurean ◽  
Diana Izdrui ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Decision Model ◽  
Data Transfer ◽  
Transmission Rate ◽  
Wide Spectrum ◽  
Computing Time ◽  
Research Work ◽  
Spectrum Management ◽  
Transportation Systems ◽  
Test Bed

The Internet of Vehicles (IoV) is an important idea in developing intelligent transportation systems and self-driving cars. Vehicles with various wireless networking options can communicate both inside and outside the vehicles. IoVs with cognitive radio (CR) enable communication between vehicles in a variety of communication scenarios, increasing the rate of data transfer and bandwidth. The use of CR can meet the future need for quicker data transport between vehicles and infrastructure (V2I). Vehicles with CR capabilities on VANET have a different appearance than regular VANET vehicles. This paper aims to develop effective spectrum management for CR-equipped automobiles. An improved channel decision model has been proposed with proven outcomes to boost the pace of transmission, eliminate end-to-end delays, and minimize the number of handoffs. Many high-bandwidth channels will be used in the near future to communicate large-sized multimedia content between vehicles and roadside units (RSU) for both entertainment and safety purposes. Co-operative sensing promotes energy-constrained CR vehicles for sensing a wide spectrum, resulting in high-quality communication channels for requesting vehicles. Our research on the CR-VANET focuses on channel decision instead of spectrum sensing and it differs from previous studies. We used the DAHP–TOPSIS model under multi-criteria decision analysis (MCDA), a sub-domain of operations research, to boost profits, i.e., transmission rate with less computing time. We constructed a test-bed in MATLAB and carried out several analyses to demonstrate that the suggested model performs better than other parallel MCDA models because there has been a limited amount of research work conducted with CR-VANET

scholarly journals Enhancing Traffic Safety with Mobile Applications

2016 ◽  
Vol 9 (3) ◽  
pp. 216
Author(s):  
H Kaartinen ◽  
J Jämsä
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Mobile Applications ◽  
Data Transfer ◽  
Research Work ◽  
Transportation Systems ◽  
Point Of View ◽  
Time Data

Intelligent Transportation Systems (ITS) have great potential and market on modern traffic environment. Technologies of the day enable the real-time data transfer and presentation for the actors in traffic and outside of it. Inter-cognitive communication is a form of communication where an information system gathers data and processes it to a form of which users can benefit on their decision making. In this paper we will present how deploying new cognitive elements on mobile applications can increase traffic safety. The most important point of view in sharing the traffic data is how to present it for the driver and how to make the data transfer reliable and safe. New vehicles have built-in solutions, such as comprehensive infotainment systems, to present the information and warnings, but older vehicles do not have this option. Therefore the modern devices, such as smartphones and tablet computers can be utilized for these purposes. This paper describes Centria’s research work on developing mobile applications for improving the traffic flow and safety by real-time support for the driver’s decision making. Also, the data security has been studied and tested at Centria, and will be reported in this paper.

Simplex-Based Calibration of Traffic Microsimulation Models with Intelligent Transportation Systems Data

2003 ◽  
Vol 1855 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Kyu-Ok Kim ◽  
L. R. Rilett
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
System Modeling ◽  
Intelligent Transportation ◽  
Simplex Algorithm ◽  
Transportation System ◽  
Transportation Systems ◽  
Test Bed ◽  
Morning Peak ◽  
Microsimulation Models

In recent years, microsimulation has become increasingly important in transportation system modeling. A potential issue is whether these models adequately represent reality and whether enough data exist with which to calibrate these models. There has been rapid deployment of intelligent transportation system (ITS) technologies in most urban areas of North America in the last 10 years. While ITSs are developed primarily for real-time traffic operations, the data are typically archived and available for traffic microsimulation calibration. A methodology, based on the sequential simplex algorithm, that uses ITS data to calibrate microsimulation models is presented. The test bed is a 23-km section of Interstate 10 in Houston, Texas. Two microsimulation models, CORSIM and TRANSIMS, were calibrated for two different demand matrices and three periods (morning peak, evening peak, and off-peak). It was found for the morning peak that the simplex algorithm had better results then either the default values or a simple, manual calibration. As the level of congestion decreased, the effectiveness of the simplex approach also decreased, as compared with standard techniques.

A Survey of Approaches for Estimating Meteorological Visibility Distance Under Foggy Weather Conditions

2020 ◽  
pp. 65-92 ◽  
Author(s):  
Faouzi Kamoun ◽  
Hazar Chaabani ◽  
Fatma Outay ◽  
Ansar-Ul-Haque Yasar
Keyword(s):  
Intelligent Transportation Systems ◽  
Situational Awareness ◽  
Wide Spectrum ◽  
Distance Estimation ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Driver Assistance Systems ◽  
Research Issues ◽  
Visibility Distance ◽  
Assistance Systems

The immaturity of fog abatement technologies for highway usage has led to growing interest towards developing intelligent transportation systems that are capable of estimating meteorological visibility distance under foggy weather conditions. This capability is crucial to support next-generation cooperative situational awareness and collision avoidance systems as well as onboard driver assistance systems. This chapter presents a survey and a comprehensive taxonomy of daytime visibility distance estimation approaches based on a review and synthesis of the literature. The proposed taxonomy is both comprehensive (i.e., captures a wide spectrum of earlier contributions) and effective (i.e., enables easy comparison among previously proposed approaches). The authors also highlight some open research issues that warrant further investigation.

scholarly journals 6G- Enabled Smart City Networking Model Using Lightweight Security Module

2021 ◽  
Author(s):  
M. M. Kamruzzaman
Keyword(s):  
Resource Allocation ◽  
Intelligent Transportation Systems ◽  
Smart City ◽  
Smart Cities ◽  
Research Work ◽  
Transportation Systems ◽  
Sixth Generation ◽  
Security Module ◽  
Distributed Networking ◽  
Technological Improvements

Abstract Smart cities use lightweight security module technologies like sixth-generation (6G) and wireless connections to improve people's quality of life. A smart city can use a networking model to power and monitor many geographically distributed networking models to support various applications like energy and resource management, intelligent transportation systems, and e-health. To manage smart city resources efficiently and intelligently, a significant state architecture must service various technologies due to the enormous development in networking models and the amount of data they generate. This research work presents a smart city networking architecture for smart city environments employing the lightweight security module (SCNM-LSM) in this work in progress article. It first offers a new conceptual framework termed the conventional model for activity off-loading and resource allocation. Second, it enhances the standard model by including off-loading and resource allocation awareness. It expands on the specific research topics to create and study the effectiveness of individual components with the previous models to accommodate technological improvements like the use of Artificial Intelligence (AI) in the sixth generation data transmission technology.

scholarly journals Analysis of Mobile Edge Computing for Vehicular Networks

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1303 ◽  
Author(s):  
Zachary Lamb ◽  
Dharma Agrawal
Keyword(s):  
Cellular Networks ◽  
Data Storage ◽  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Vehicular Ad Hoc Networks ◽  
Transportation Systems ◽  
Edge Computing ◽  
Test Bed ◽  
And Storage ◽  
Cloud Resources

Vehicular ad-hoc Networks (VANETs) are an integral part of intelligent transportation systems (ITS) that facilitate communications between vehicles and the internet. More recently, VANET communications research has strayed from the antiquated DSRC standard and favored more modern cellular technologies, such as fifth generation (5G). The ability of cellular networks to serve highly mobile devices combined with the drastically increased capacity of 5G, would enable VANETs to accommodate large numbers of vehicles and support range of applications. The addition of thousands of new connected devices not only stresses the cellular networks, but also the computational and storage requirements supporting the applications and software of these devices. Autonomous vehicles, with numerous on-board sensors, are expected to generate large amounts of data that must be transmitted and processed. Realistically, on-board computing and storage resources of the vehicle cannot be expected to handle all data that will be generated over the vehicles lifetime. Cloud computing will be an essential technology in VANETs and will support the majority of computation and long-term data storage. However, the networking overhead and latency associated with remote cloud resources could prove detrimental to overall network performance. Edge computing seeks to reduce the overhead by placing computational resources nearer to the end users of the network. The geographical diversity and varied hardware configurations of resource in a edge-enabled network would require careful management to ensure efficient resource utilization. In this paper, we introduce an architecture which evaluates available resources in real-time and makes allocations to the most logical and feasible resource. We evaluate our approach mathematically with the use of a multi-criteria decision analysis algorithm and validate our results with experiments using a test-bed of cloud resources. Results demonstrate that an algorithmic ranking of physical resources matches very closely with experimental results and provides a means of delegating tasks to the best available resource.

New Vehicle Data Bus Architecture and In-Vehicle Information System Evaluation Platform for Intelligent Transportation Systems Modules

1998 ◽  
Vol 1651 (1) ◽  
pp. 17-22
Author(s):  
Philip F. Spelt ◽  
Allan M. Kirson ◽  
Susan Scott
Keyword(s):  
Information System ◽  
Intelligent Transportation Systems ◽  
Local Area Network ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Area Network ◽  
Test Bed ◽  
Data Bus ◽  
Vehicle Information ◽  
Bus Architecture

An increasing number of intelligent transportation systems- (ITS-) after-market systems present a set of in-vehicle installation and use problems relatively unique in the history of automobile use. Many automobile manufacturers would like to offer these new state-of-the-art devices to customers, but are hampered by the current design cycle of new cars. While automobile manufacturers are indeed using multiplex buses [the automotive equivalent of a computer local area network (LAN)], problems remain because manufacturers are not converging on a single bus standard. A new dual-bus architecture to address these problems is presented with an in-vehicle information system (IVIS) research platform on which the principles embodied in the ITS data bus architecture can be evaluated. The dual-bus architecture has been embodied in a proposed Society of Automotive Engineers (SAE) standard, with support from both automobile and consumer electronics manufacturers. The architecture and a reference model for the interfaces and protocols of the new bus are presented and described. The goals of the ITS data bus are to be inexpensive and easy to install, and to provide for safe and secure functioning. These high-level goals are embodied in the proposed standard. The IVIS development platform comprises a number of personal computers (PCs) linked via ethernet LAN, with a high-end PC serving as the IVIS computer. In this LAN, actual devices can be inserted in place of the original PC that emulated them. This platform will serve as the development and test bed for an ITS data bus conformity test, the SAE standard for which is also being developed.

Exploring the Relationship between Data Aggregation and Predictability to Provide Better Predictive Traffic Information

2005 ◽  
Vol 1935 (1) ◽  
pp. 28-36 ◽  
Author(s):  
Cheol Oh ◽  
Stephen G. Ritchie ◽  
Jun-Seok Oh
Keyword(s):  
Intelligent Transportation Systems ◽  
Data Aggregation ◽  
Transportation Systems ◽  
Traffic Information ◽  
Surveillance Systems ◽  
Test Bed ◽  
Travel Time Prediction ◽  
Successful Operation ◽  
Prediction Techniques ◽  
The Relationship

Providing reliable predictive traffic information is a crucial element for successful operation of intelligent transportation systems. However, there are difficulties in providing accurate predictions mainly because of limitations in processing data associated with existing traffic surveillance systems and the lack of suitable prediction techniques. This study examines different aggregation intervals to characterize various levels of traffic dynamic representations and to investigate their effects on prediction accuracy. The relationship between data aggregation and predictability is explored by predicting travel times obtained from the inductive signature–based vehicle reidentification system on the I-405 freeway detector test bed in Irvine, California. For travel time prediction, this study employs three techniques: adaptive exponential smoothing, adaptive autoregressive model using Kalman filtering, and recurrent neural network with genetically optimized parameters. Finally, findings are discussed on suggestions for applying prediction techniques effectively.

Assessment of Queue Warning Application on Signalized Intersections for Connected Freight Vehicles

2021 ◽  
pp. 036119812110152
Author(s):  
Sara Bashir ◽  
Milan Zlatkovic
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Signalized Intersections ◽  
Signal Control ◽  
Communication Link ◽  
Connected Vehicle ◽  
Test Bed ◽  
Control Logic ◽  
Time To Collision ◽  
Freight Vehicles

Connected vehicle (CV) systems are at the core of intelligent transportation systems (ITS) for their capability to support a variety of ITS applications and to unite vehicles and infrastructure elements into a well-integrated transportation system. CV refers to vehicles that exchange information with each other and with the infrastructure. The queue warning application (Q-WARN) uses CV technologies to allow vehicles within the queue to broadcast their queued status information automatically to upstream vehicles and to infrastructure. Queue warnings are sent to oncoming vehicles to prevent rear-end or other secondary collisions. This paper focuses on Q-WARN applications for freight vehicles at signalized intersections adjacent to I-80 in Wyoming, which are characterized by heavy truck traffic. The algorithms use the latitude/longitude coordinates of freight CVs and intersections to form a communication link and to share information. Tests were performed in VISSIM microsimulation with Econolite ASC/3 software-in-the-loop controller emulator for different CV market penetration rates. Three locations in Wyoming were used as test-bed cases. The developed Q-WARN algorithms are successful in reducing vehicle delays by an average of 2% to 5%. Time to collision (TTC) significantly increased with an increase in CV rates, by two to five times. The abundance of information obtained from CVs can be used further to enhance signal control algorithms. The developed algorithms can easily be implemented in the field, since they use existing CV communication protocols and signal control logic.

scholarly journals On-demand multi-hop forwarding for sustainable vehicular data transfer network

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110151
Author(s):  
Ayoub el Bendali ◽  
Anis Ur Rahman ◽  
Asad Waqar Malik ◽  
Muazzam Ali Khan ◽  
Sri Devi Ravana
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Vehicular Networks ◽  
Data Transfer ◽  
Smart Cities ◽  
Transportation Systems ◽  
Vital Role ◽  
Vehicle Speed ◽  
Coverage Area ◽  
Smart Hospitals

Smart cities play a vital role to develop a sustainable infrastructure with efficient management of the Internet of things devices. The infrastructure is used to support various applications for smart hospitals, smart factories, and intelligent transportation systems. With the extensive deployment of Internet of things devices, unprecedented growth in data has lead to capacity and transfer issues. In this article, we proposed an efficient data transfer mechanism based on self-sustainable networks over the vehicular environment. Depending on whether the network is connected with vehicles available to support direct connection from the source to destination, we propose end-to-end and hop-by-hop forwarding for vehicular networks that are inherently disconnected. The evaluation results demonstrate that the lifetime of the discovered paths depends on the coverage area, vehicle mobility, and vehicle speed. Therefore, at times redundant disjoint paths are selected for communication. In the proposed work, selected vehicles are used to reach the destination.

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