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

Anjum, Shaik Shabana and Noor, Rafidah Md and Aghamohammadi, Nasrin and Ahmedy, Ismail and Mat Kiah, Miss Laiha and Hussin, Nornazlita and Anisi, Mohammad Hossein and Qureshi, Muhammad Ahsan (2019) 'Modeling Traffic Congestion Based on Air Quality for Greener Environment: An Empirical Study.' IEEE Access, 7. 57100 - 57119. ISSN 2169-3536

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Abstract

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.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 06 Jun 2019 15:05
Last Modified: 06 Jun 2019 15:05
URI: http://repository.essex.ac.uk/id/eprint/24767

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