ReFOCUS: A hybrid fog-cloud based intelligent traffic re-routing system

Rezaei, Mahboobe; Noori, Hamed; Rahbari, Dadmehr; Nickray, Mohsen

doi:10.1109/kbei.2017.8324943

Cited by 18 publications

(14 citation statements)

References 23 publications

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“…This is the so-called ''common resource distribution problem'', from which the so-called ''Minority Game'' or ''Farol Bar Problem'' [43] derives. It is therefore clear that there is a need for more precise control of vehicle routes, that requires precise individuals feedback and/or highly distributed sensor networks [24], [42], [50]. This control could be exercised through individualised management at the microscopic level of each route.…”

Section: A Backgroundmentioning

confidence: 99%

Urban Traffic Routing Using Weighted Multi-Map Strategies

Paricio

López-Carmona

2019

IEEE Access

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Urban traffic routing has to deal with individual mobility and collective wellness considering citizens, multi-modal transport, and fleet traffic with conflicting interests such as electric vehicles, local distribution, public transport, and private vehicles. Different interests, goals, and regulations, suggest the development of new multi-objective routing mechanisms which may improve traffic flow. In this work, Traffic Weighted Multi-Maps (TWM) is presented as a novel traffic routing mechanism based on the strategical generation and distribution of complementary cost maps for traffic fleets, oriented towards the application of differentiated traffic planning and control policies. TWM is built upon a centralized control architecture, where a Traffic Management Center generates and distributes customized cost maps of the road network. These maps are used individually to calculate routes. In this research, we present the TWM theoretical model and experimental results based on microscopic simulations over a real city traffic network under multiple scenarios, including traffic incidents management. Experimental evaluation takes into account driver's adherence to the system and considers a multi-objective analysis both for the global network parameters (congestion, travel time, and route length) and for the subjective driving experience. Experimental results deliver performance improvements from 20% to 50%. TWM is fully compatible with existing traffic routing systems and has promising future evolution applying new algorithms, policies and network profiles.

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Section: A Backgroundmentioning

confidence: 99%

Urban Traffic Routing Using Weighted Multi-Map Strategies

Paricio

López-Carmona

2019

IEEE Access

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“…Finally, Rezaei et al [10] introduced ReFOCUS, that aims at optimally re-routing vehicles in congested areas, or approaching congested areas, by leveraging on fogcloud computing performed by vehicles. The focus of the work is on minimising the information exchanged and the complexity of the algorithms.…”

Section: Related Workmentioning

confidence: 99%

Centralised Versus Decentralised Traffic Optimisation of Urban Road Networks: A Simulation Study

Vallati¹

2020

2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)

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One of the pivotal challenges presented to urban road traffic controllers is the effective utilisation of transport infrastructure, as a result of growing urbanisation, the finite network capacity, and of the increasing number of road vehicles. In this context, the arrival of connected autonomous vehicles (CAVs) represents a unique opportunity for a fundamental change in urban traffic optimisation, and urban traffic control should take an active role in integrating CAVs into the mobility ecosystem in order to maximise benefits. Traditional approaches, commonly exploited by SATNAVs, are based on a decentralised logic, where each vehicle decides the route to follow in isolation, possibly by considering the current network conditions. The arrival of connected vehicles would allow the exploitation of centralised traffic optimisation, where a central urban traffic controller can suggest routes to vehicles by taking into account the current network conditions, and predicted future evolution. This paper introduces a centralised approach for traffic optimisation of urban road networks, and presents an extensive evaluation of the capabilities of centralised and decentralised approaches. Evaluation is based on a validated and calibrated SUMO simulation model of the town centre of Milton Keynes, United Kingdom.

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“…The recent advanced in wireless technologies along with emerging Internet of Things (IoT) technologies, opened up a new form of low cost and long range communication which can help with the raised issue and immediate implementation of the ITS application in real world. By integration with IoT, the ITS can apply advanced technologies in the processing, storing, and wireless communication to create the Internet of Vehicles (IoV) and Road Side Elements (IoRSE) [2], [3] and allows the vehicles and infrastructures communicate to effectively collect the traffic data to improve the traffic conditions [4].…”

Section: Introductionmentioning

confidence: 99%

“…For ITS applications, due to the huge amount of generated data, by sensors installed on vehicles or Road Side Units (RSUs), transferring them to cloud servers could lead to unnecessary communication overhead, high bandwidth consume, increased response delay in sensitive traffic information, etc. [2], [5]. Recently, considering these challenges and to reduce central computing power and reduce the amount of required data transfer to central location, various computing technologies have been introduced to solve services of processing, storing, and communication for the Internet of vehicles such as: Cloud computing [6], cloudlets [7], edge computing [8], Mobile Edge Computing (MEC) [9], and fog computing.…”

Section: Introductionmentioning

confidence: 99%

LPWAN-Based Hybrid Backhaul Communication for Intelligent Transportation Systems: Architecture and Performance Evaluation

Shahgholi

Sheikhahmadi

Khamforoosh

et al. 2020

Preprint

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There are more than 1.3 billion vehicles around the world and rapidly growing which causing worldwide challenges such as congestion, huge fuel consumption, and emissions. The solution to these issues could be expansion of infrastructure or making efficient use of the current infrastructure using current technological advances by implementing Intelligent Transportation Systems (ITSs). In this paper, we proposed and explored the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and Narrowband Internet of Things (NB-IoT), for ITS applications. LTE-M and NB-IoT are designed to provide long-range, low power, and lowcost communication infrastructure and can be a viable promising option for immediate implementation in the real world. In order to understand the feasibility of using LPWAN for ITS, we investigated two applications with low and high delay requirements: road traffic monitoring and emergency vehicle management and preemption. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end to end latency per user. SUMO traffic simulator has been used for realistic traffic generation and a Python-based program with the ability to live data exchange with SUMO has been developed for communication performance evaluations. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure where it was in favor of the LTE-M over NB-IoT.

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ReFOCUS: A hybrid fog-cloud based intelligent traffic re-routing system

Cited by 18 publications

References 23 publications

Urban Traffic Routing Using Weighted Multi-Map Strategies

Urban Traffic Routing Using Weighted Multi-Map Strategies

Centralised Versus Decentralised Traffic Optimisation of Urban Road Networks: A Simulation Study

LPWAN-Based Hybrid Backhaul Communication for Intelligent Transportation Systems: Architecture and Performance Evaluation

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