A predictive road traffic management system based on vehicular ad-hoc network

Nafi, Nazmus Shaker; Khan, Reduan H.; Khan, Jamil Y.; Gregory, Mark A

doi:10.1109/atnac.2014.7020887

Cited by 33 publications

(16 citation statements)

References 5 publications

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“…Ren et al [23] proposed a mobility-based and stability-based clustering algorithm for urban scenarios that takes into account the movement of the vehicle, its relative position, the estimation of the useful link life between vehicles, and the traffic flow rate. Similarly, Nafi et al [24] proposed a predictive road traffic management system based on a Vehicular Ad-hoc Network architecture. Their solution relies on a communications scheme to estimate the intensity of future traffic at different intersections based on a linear predictive algorithm that accounts for maximum speed, scenario, and routes.…”

Section: Related Workmentioning

confidence: 99%

A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

et al. 2019

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Currently, one of the main challenges that large metropolitan areas must face is traffic congestion. To address this problem, it becomes necessary to implement an efficient solution to control traffic that generates benefits for citizens, such as reducing vehicle journey times and, consequently, environmental pollution. By properly analyzing traffic demand, it is possible to predict future traffic conditions, using this information for the optimization of the routes taken by vehicles. Such an approach becomes especially effective if applied in the context of autonomous vehicles, which have a more predictable behavior, thus enabling city management entities to mitigate the effects of traffic congestion and pollution, thereby improving the traffic flow in a city in a fully centralized manner. This paper represents a step forward towards this novel traffic management paradigm by proposing a route server capable of handling all the traffic in a city, and balancing traffic flows by accounting for present and future traffic congestion conditions. We perform a simulation study using real data of traffic congestion in the city of Valencia, Spain, to demonstrate how the traffic flow in a typical day can be improved using our proposed solution. Experimental results show that our proposed traffic prediction equation, combined with frequent updating of traffic conditions on the route server, can achieve substantial improvements in terms of average travel speeds and travel times, both indicators of lower degrees of congestion and improved traffic fluidity.

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Section: Related Workmentioning

confidence: 99%

A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

et al. 2019

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“…The optimal path selection is based on various parameters such as traffic rate, speed of the vehicle, shortest path etc. Nafi et al (2014) propose a system using IEEE 802.11p based vehicle to infrastructure communications system to predict the future traffic intensities at intersections point on road. The vehicles are rerouted based on this prediction to reduce the traffic congestion and minimize the travelling time of the individual.…”

Section: Related Workmentioning

confidence: 99%

A Reference Architecture for Context-Aware Intelligent Traffic Management Platforms

Rehena

Janssen²,

Chattopadhya

2018

International Journal of Electronic Government Research

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Smart cities have been heralded for improving traffic management by utilizing data for making better traffic management decisions. Multi-sided platforms collect data from sensors and citizen-generated data on one side and can provide input for decision-making using data analytics by governments and the public on the other side. However, there is no guidance for creating developing Intelligent Traffic Management Systems (ITMS) platforms. The involvement of various actors having different interest and heterogeneous datasets hampers development. In this article, the authors design a reference architecture (RA) to support intelligent traffic management systems for providing better a commute, and safety and security during travel based on real-time information. The main three layers of this RA are datasets, processes, and actors. The RA for ITMS provides guidance for designing and overcoming the challenges with: 1) heterogeneous datasets; 2) data gathering; 3) data processing; 4) data management; and 5) supporting various types of data users. The illustration and evaluation of the architecture shows possible solutions of the aforementioned challenges. The RA helps to integrate the activities performed by the various actors. In this way it can be used to reduce traffic queues, increase the efficient use of resources, smooth and safe commute of the citizens.

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“…This coordination scheme has a hybrid nature [10], i.e., it gathers information from the longrange bidirectional connection between vehicles and eNBs along with the information from the short-range communication link between vehicles. Hence, obtaining global knowledge is possible to predict the future condition of the network and react accordingly [11]. The remainder of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

An optimal LTE-V2I-based cooperative communication scheme for vehicular networks

Calvo

Mathar

2017

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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In this paper, an optimized cooperative communication scheme based on the recently presented LTE-V2X is introduced. LTE-V2X is the newly proposed technology by 3GPP in its Release 14 in order to obtain a feasible communication scheme between vehicles and infrastructures. This paper investigates the case of centralized network architecture, where the eNodeBs are used as information centers in order to optimize the scheduling scheme by means of clustering the vehicles in their coverage range. The proposed cooperative scheme is based on the shared messages between vehicles using a semi-persistent scheduling (SPS) which fulfills the rigid requirements, i.e., delay and reliability, faced in vehicular communications. In this paper, an enhancement of the SPS is defined using the information gathered by the network infrastructures in order to mitigate the interference. In addition, due to the high mobility of the vehicles, a predictive control model is implemented to estimate the vehicles trajectory, hence, improving the scheduling scheme performance. The aforementioned methods are simulated in a realistic scenario, using a traffic simulator, and compared with the standard LTE-V2X implementation as well as other methods proposed in the literature.

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A predictive road traffic management system based on vehicular ad-hoc network

Cited by 33 publications

References 5 publications

A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

A Reference Architecture for Context-Aware Intelligent Traffic Management Platforms

An optimal LTE-V2I-based cooperative communication scheme for vehicular networks

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