RETRACTED ARTICLE: Smart city routing using GIS &amp; VANET system

Bhavani, M.; Valarmathi, A.

doi:10.1007/s12652-020-02148-y

Cited by 14 publications

(7 citation statements)

References 26 publications

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“…Multi-hop routing is combined with Huffman and arithmetic coding to compress data packet payloads. The work in [157] addresses communication proficiency and routing in VANETs by using a support vector machine (SVM)-based ML scheme to study and process data Item Contributions [152] Designs a Q-learning-based proactive network link status extraction mechanism using periodic HELLO packets [153] The proposed routing approach resolves the network congestion difficulty in VANETs [154] Proposes a Q-learning-based routing protocol for handling microscopic as well as macroscopic issues while taking a routing decision [155] Proposes a ML-based approach to detect local and global invasions in VANETs [156] Handles data forwarding using location on roadsides with the help of k-shortest course routing [157] Designs a SVM-based study of the analysis and process of using probes to collect car data [158] Learning automata improves multipath routing with the help of leapfrog method with Particle Swarm Optimization [159] Reinforcement learning-based routing mechanism adaptively chooses the optimal path for charging data delivery in large-scale dynamic VANET environments [160] Predicts a routing strategy to control traffic congestion in VANETs using Geographic Information System [161] The proposed clustering-based mechanism reduces traffic congestion and significantly increases throughput [162] The learning-based routing scheme has the ability to select routing strategies dynamically using edge server computational power [50] Detects network loads and timely adjusts the routing decision such that the network congestion can be prevented [53] Predicts the vehicle movement patterns based on past traces such that the transmission performance can be increased [163] Addresses the issue of the inefficient data dissemination in V2X communications, and accordingly designs a cluster-based solution collected from cars.…”

Section: F Network Management and Congestion Handlingmentioning

confidence: 99%

“…The work in [159] proposes an efficient charging details transmission strategy for spatiotemporally coordinated V2V charging services. Spatial systems (areas that are measured as GPS point systems, like malls, market areas, and housing areas), in which traffic density is generally high, are considered in [160]. The system proposed in that work predicts a routing strategy to control traffic congestion using VANETs and a GIS architecture.…”

Section: F Network Management and Congestion Handlingmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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Intelligent transportation systems (ITSs) have become increasingly popular because they support effective coordination in connected vehicles. ITSs present an integrated approach for exchanging relevant information in order to improve the safety, efficiency, and reliability of road transportation systems. A variant of mobile ad-hoc networks (MANETs) called vehicular ad-hoc networks (VANETs) are an integral component of ITSs. VANETs consist of interconnected vehicles with sensing abilities that exchange information related to traffic, positioning, weather, and emergency services. In general, vehicle-to-everything (V2X) refers to communications between any entity and a vehicle, where the entity may be a vehicle, a cloud-based network, a pedestrian, or equipment installed along a road. One of the crucial challenges in V2X is the reliable and timely circulation of information among vehicular nodes to allow drivers to make decisions that increase road safety. In this context, efficient V2X routing protocols play a key role in supporting reliability and safety, and enhancing the overall quality of service (QoS) in VANETs. However, VANETs have distinct characteristics, such as high vehicular node mobility, unsteady connectivity, rapid changes in network topology, and unbounded network size, that can significantly affect routing in the network. Various routing protocols for V2X communication exist in the open technical literature. In this survey, we categorize the routing mechanisms as non-learning-and learning-based approaches, and discuss existing V2X routing protocols and their contributions to and impacts on VANET performance. Here, the learning-based approach implies the use of machine learning algorithms. This survey also summarizes open challenges in designing effective V2X routing protocols and future research directions to consider when developing smart routing mechanisms for next-generation intelligent VANET technologies.INDEX TERMS VANET, V2X, routing protocol, non-learning-based routing, learning-based routing.

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Section: F Network Management and Congestion Handlingmentioning

confidence: 99%

Section: F Network Management and Congestion Handlingmentioning

confidence: 99%

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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“…The frequent topology changes cause network fragmentation [13]. In this kind of architecture, the network fragmentation due to high mobility makes routing of data more challenging [20], [28].…”

Section: Architectural Paradigms Of Vanetsmentioning

confidence: 99%

A Survey on Junction Selection based Routing Protocols for VANETs

Abbasi¹,

Elmubarak²

2021

IJACSA

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To compare significant position-based routing protocols based on their underlying techniques such as junction selection mechanisms that provide vehicle-to-vehicle communications in city scenarios. Background: Vehicular Adhoc Network is the most significant offshoot of Mobile Adhoc Networks which is capable of organizing itself in an infrastructure-less environment. The network builds smart transportation which facilitates deriving in-terms of traffic safety by exchanging timely information in a proficient manner. Findings: The main features of vehicular adhoc networks pertaining to the city environment like high mobility, network segmentation, sporadic interconnections, and impediments are the key challenges for the development of an effective routing protocol. These features of the urban environment have a great impact on the performance of a routing protocol. This study presents a brief survey on the most substantial position-based routing schemes premeditated for urban inter-vehicular communication scenarios. These protocols are provided with their operational techniques for exchanging messages between vehicles. A comparative analysis is also provided, which is based on various important factors such as the mechanisms of intersection selection, forwarding strategies, vehicular traffic density, local maximum conquering methods, mobility of vehicular nodes, and secure message exchange. Application/Improvements: the outcomes observed from this paper motivate us to improve routing protocol in terms of security, accuracy, and reliability in vehicular adhoc networks. Furthermore, it can be employed as a foundation of references in determining literature that are worth mentioning to the routing in vehicular communications.

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“…M.Monica Bhavani presented a solution using GIS for detecting heavy traffic dense areas like shopping malls. Alternate routes can be tracked and displayed using VANET communication methodologies (5) . Pampa Sadhukhan addressed the problem traffic congestion using IoT.…”

Section: Related Workmentioning

confidence: 99%

Intelligent signalling system to control traffic in vehicular ad hoc networks R

Lalitha¹,

Srinivas²,

Kumar³

et al. 2020

IJST

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Traffic congestion problem persists more at junctions and causes inconvenience to public. Owing to this, people may not reach their destinations in time. Although there are alerts in mobile phones regarding arrival times of flight services and other journey related information due to sudden traffic jams at junctions these advanced technology innovations are being becoming fragile. Since long, many researchers have been putting their efforts to find remedies for reducing traffic congestion. Objectives: The key focus is on balancing forwarding time and waiting time at junctions based on the number of vehicles arrived at that junction. Methods: The proposed system uses Internet of Things (IoT) based monitoring to control signaling system. IR sensors are used to count number of vehicles passing over the lane by triggering clock for object detection. The signaling time can be changed dynamically based on the vehicle count, so that more time is allocated to the lanes which have more traffic and the remaining time is adjusted among other lanes. This reduces congestion at dense traffic lanes. Findings: There will be time variant setting of signal lights based on the density of the traffic. The dense traffic lanes will be allotted more time and will be cleared first. Expanding on this point, the time adjustment is done based on the vehicle count not on periodical fixation of intervals. Novelty: The ecosystem developed provides an ultimate solution to vehicle users for comfortable movement on the roads without being delayed.

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RETRACTED ARTICLE: Smart city routing using GIS & VANET system

Cited by 14 publications

References 26 publications

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

A Survey on Junction Selection based Routing Protocols for VANETs

Intelligent signalling system to control traffic in vehicular ad hoc networks R

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