An adaptive and VANETs-based Next Road Re-routing system for unexpected urban traffic congestion avoidance

Wang, Shen; Djahel, Soufiene; McManis, Jennifer

doi:10.1109/vnc.2015.7385577

Cited by 26 publications

(20 citation statements)

References 15 publications

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“…In NRR, the values of the factors used in the next road cost function vary depending on the different time stamp (i.e., e.OC, e.T T ) and different current/destination location of the vehicle to be rerouted (i.e., e.GD, e.GC). Therefore, a suitable weight value allocation w should be variable for different rerouting requests [14]. In the next road selection, for a particular factor of e, the greater the variation of its value is, the more importance should be given to this factor in the computation of the rerouting decision.…”

Section: Routing Cost Function In Nrrmentioning

confidence: 99%

Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

Wang

Djahel

Zhang

et al. 2016

IEEE Trans. Intell. Transport. Syst.

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114

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Abstract-During peak hours in urban areas, unpredictable traffic congestion caused by en route events (e.g., vehicle crashes) increases drivers' travel time and, more seriously, decreases their travel time reliability. In this paper, an original and highly practical vehicle rerouting system, which is called Next Road Rerouting (NRR), is proposed to aid drivers in making the most appropriate next road choice to avoid unexpected congestions. In particular, this heuristic rerouting decision is made upon a cost function that takes into account the driver's destination and local traffic conditions. In addition, the newly designed multiagent system architecture of NRR allows the positive rerouting impacts on local traffic to be disseminated to a larger area through the natural traffic flow propagation within connected local areas. The simulation results based on both synthetic and realistic urban scenarios demonstrate that, compared with the existing solutions, NRR can achieve a lower average travel time while guaranteeing a higher travel time reliability in the face of unexpected congestion. The impacts of NRR on the travel time of both rerouted and nonrerouted vehicles are also assessed, and the corresponding results reveal its higher practicability.

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Section: Routing Cost Function In Nrrmentioning

confidence: 99%

Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

Wang

Djahel

Zhang

et al. 2016

IEEE Trans. Intell. Transport. Syst.

Self Cite

114

View full text Add to dashboard Cite

show abstract

“…Knorr et al [20] proposed a beacon-based solution to warn drivers about changes in the flow of vehicles when considering the perturbations caused by drivers during vehicles' movement. Wang et al [21] proposed an adaptive beacon-based system for unexpected traffic congestion avoidance. These two solutions are effective to increase locally the traffic flow, however, there are some issues to consider: (i) a high number of transmitted messages among vehicles; (ii) low quality in the traffic estimation of alternative routes; and (iii) selfish decisions.…”

Section: Vehicular Traffic Managementmentioning

confidence: 99%

Vehicular Traffic Management Based on Traffic Engineering for Vehicular Ad Hoc Networks

et al. 2020

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Urbanization causes many problems to human mobility, since people living in the cities tend to increase the vehicular traffic flow. City road infrastructure does not increase faster than the number of vehicles, thus causing traffic congestion in dense urban centers. Besides travel delay, vehicular traffic congestion results in serious problems to human beings (e.g., health problems due to stress), to the planet (e.g., increase in pollution) and to the economy (e.g., waste of a large amount of money due to time spent in traffic jams). In order to improve vehicular traffic flow in dense urban areas, this paper presents a new Vehicular Traffic Management Service based on Traffic Engineering theory, called ReRouTE. The ReRouTE service relies on the density of vehicles in roads and applies the flow-density macroscopic traffic engineering model to identify congested routes. Roads are represented by a weighted graph, which is then used to discover routes without traffic jams and with a small increase in the travel distance. The main goal of ReRouTE is to reduce traffic jams while increasing the global vehicular traffic flow of the road network. Moreover, the service was designed to reduce traffic jams instead of moving them to a different road/area. Simulation results show the ability of ReRouTE to improve travel time, travel distance, speed and the number of messages transmitted when compared to a literature solution.

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“…solutions for this problem [3], [4]. Although most of the existing VTRSs obtained promising results for reducing travel time or improving traffic flow; however, they cannot guarantee consideration of non-recurring congestion (unexpected events such as working zones, vehicle accident/breakdown and weather condition) as well as reduction of the trafficrelated nuisances such as air pollution, noise, and fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

Modeling Traffic Congestion Based on Air Quality for Greener Environment: An Empirical Study

et al. 2019

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The primary focus of this paper is to govern traffic congestion on urban road networks based upon a cumulative approach comprising of traffic flow modeling, vehicle emission modeling, and air quality modeling. Based upon the traffic conditions, a simulation model is proposed and further tested for performance metrics, which is relative to three main aspects, namely, the waiting time of the vehicles at the junctions/intersections/signals, the type of pollutant emitted by a vehicle, and the traveling time. The experimental analysis and validation are carried out for different case studies in Malaysia, such as Petaling Jaya, Shah Alam, Mont Kiara, and Jalan Tun Razak. Three different scenarios (morning, afternoon, and evening) are analyzed and tested to explore the traffic usage parameter. The results showed that when traffic is modeled and governed based upon traffic flow, vehicle emission, and air quality index (AQI), nearly 75% of traffic congestion is mitigated, hence making the atmosphere pollution free as well as avoiding Urban Heat Island (UHI) effect due to the heat generated from vehicles. The experimental results are tested, validated, and compared with existing solutions for performance analysis. The proposed model is aimed toward overcoming the major drawbacks of existing approaches, such as single-path suggestions, traffic delay during peak hours/emergencies, non-recurring congestion consideration, congestion avoidance instead of recovering from it, improper reporting of road accidents, and notifications about traffic jam ahead to the users and high vehicle usage rate.

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An adaptive and VANETs-based Next Road Re-routing system for unexpected urban traffic congestion avoidance

Abstract: Some rights reserved. For more information, please see the item record link above.

Cited by 26 publications

References 15 publications

Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

Vehicular Traffic Management Based on Traffic Engineering for Vehicular Ad Hoc Networks

Modeling Traffic Congestion Based on Air Quality for Greener Environment: An Empirical Study

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