Adaptive traffic management with VANET in V to I communication using greedy forwarding algorithm

Yugapriya, R.; Dhivya, P.; Dhivya, M. M; Kirubakaran, S.

doi:10.1109/icices.2014.7034067

Cited by 4 publications

(5 citation statements)

References 3 publications

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“…A simulation analysis of geographic location and distance routing on the vehicle area network (VANET) was carried out [32][33][34] using the wireless technology approach (IEEE 802.11p). The work addressed the issue of routing in VANET due to road constraints like over-speeding of vehicles and road barriers.…”

Section: Figure 4 Gps-based Vehicular Technology Classificationmentioning

confidence: 99%

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A Vehicle Tracking System Using Greedy Forwarding Algorithms for Public Transportation in Urban Arterial

et al. 2020

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A vehicle tracking system assists public transportation users in their movements by providing real-time information on the locations of vehicles in transit. Public transportation in parts of developing nations, especially Nigeria is ineffective. The system is chaotic and frustrating, especially at peak traffic periods. In a bid to address the problem, a vehicle tracking system was developed as a component of an Advanced Public Transportation System to improve commuting in an urban arterial. The developed system is based on wireless technologies of the Global Positioning System (GPS) and Global System for Mobile Communication module. It records and displays real-time vehicle location using a GPS-based greedy forwarding algorithm, computes route distance information using distance-time based algorithm and radar range sensor (RRS). A pseudo-range mathematical model using the Haversine formula was adopted in determining the accurate position of an object during signal transmission from GPS satellites to the receiver message module. The minimum inversion matrix method was used for the GPS-based geometric dilution of precision (GDoP) selection of satellite approximation and distance. Atmega328P controller chip was used as the logical control unit for processing activities in the tracking system and programming in Arduino IDE using C-language. The system was deployed to a university transportation system in Nigeria: a journey to and from the Bosso and Gidan Kwano Campuses route in the Federal University of Technology, Minna. The vehicle tracking system was tested with 11 tracked satellite and minor dilution error (PDoP error =1.9, HDoP=0.9, and VDOP=1.7) was recorded. The system is efficient and accurate in distance and time information display with a minor delay. The system would enhance fleet management schemes for urban arterial and can be adopted universally.

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Section: Figure 4 Gps-based Vehicular Technology Classificationmentioning

confidence: 99%

“…A simulated analysis of location and distance-based routing in Vehicular area network (VANET) using WiFi (IEEE802.11p) [33].…”

Section: Figure 4 Gps-based Vehicular Technology Classificationmentioning

confidence: 99%

A Vehicle Tracking System Using Greedy Forwarding Algorithms for Public Transportation in Urban Arterial

et al. 2020

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“…Security and privacy are the significant issues in VANET. Chen et al, 10 Gupte and Younis 11 Yugapriya et al, 12 Djahel et al 13 Lunge and Borkar, 14 Xiao and Lo 15 Predictive Predict congestion using data analytics Proactive Predictive Congestion control Pattern analysis Future forecasting Tak et al 16 Nafi et al, 17 Daniel et al, 18 Alrifaee et al 19 HomChaudhuri et al, 20 Liang and Wakahara 21 Scalability. Another major limitation of TMSs is scalability because of the varied node density types of VANET.…”

Section: V2v and V2i Applications For Road Traffic Managementmentioning

confidence: 99%

“…Security and privacy are the significant issues in VANET. Chen et al, 10 Gupte and Younis 11 Yugapriya et al, 12 Djahel et al 13 Lunge 16 Nafi et al, 17 Daniel et al, 18 Alrifaee et al 19 HomChaudhuri et al, 20 Liang and Wakahara…”

Section: V2v and V2i Applications For Road Traffic Managementmentioning

confidence: 99%

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Characterizing the role of vehicular cloud computing in road traffic management

Ahmad

Noor

Ali

et al. 2017

International Journal of Distributed Sensor Networks

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Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles.

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