Reduction of Fuel Consumption and Exhaust Pollutant Using Intelligent Transport Systems

Nasir, Mostofa Kamal; Noor, Rafidah Md; Kalam, M.A.; Masum, B.M.

doi:10.1155/2014/836375

Cited by 54 publications

(22 citation statements)

References 38 publications

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“…However, velocities between 16.7 m/s and 22. 2 m/s result in reduced fuel consumption and pollution [32]. Variations in velocity can be reduced with the regulation parameter b in autonomous vehicles to reduce fuel consumption and pollution.…”

Section: Resultsmentioning

confidence: 99%

A macroscopic traffic model for traffic flow harmonization

Khan

Gulliver

2018

Eur. Transp. Res. Rev.

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Traffic flow will harmonize to forward conditions. The time and distance required for harmonization can have a significant effect on the traffic density behavior. The flow can evolve into clusters of vehicles or become uniform depending on parameters such as safe time headway and safe distance headway. In this paper, a new model is presented to provide a realistic characterization of traffic behavior during the harmonization period. Results are presented for a discontinuous density distribution on a circular road which shows that this model produces more realistic traffic behavior than other models in the literature.

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Section: Resultsmentioning

confidence: 99%

A macroscopic traffic model for traffic flow harmonization

Khan

Gulliver

2018

Eur. Transp. Res. Rev.

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“…Therefore, green driver make headway without obstructing other drivers and maintain the safe distance to other vehicles without compromising traffic flow. Tang et al [73] have investigated the impact of traffic density to multiple headways from the perspective of fuel consumption. They found that at a 20-m initial headway, a lower car density (20 nos) results in 13.4 L/100 km fuel consumption compared to a higher car density (80 nos), which consumes 13.1 L/100 km under the influence of ramps.…”

Section: Literature Content Analysis and Synthesizementioning

confidence: 99%

Green Driver: Travel Behaviors Revisited on Fuel Saving and Less Emission

et al. 2018

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Road transportation is the main energy consumer and major contributor of ever-increasing hazardous emissions. Transportation professionals have raised the idea of applying the green concept in various areas of transportation, including green highways, green vehicles and transit-oriented designs, to tackle the negative impact of road transportation. This research generated a new dimension called the green driver to remediate urgently the existing driving assessment models that have intensified emissions and energy consumption. In this regard, this study aimed to establish the green driver's behaviors related to fuel saving and emission reduction. The study has two phases. Phase one involves investigating the driving behaviors influencing fuel saving and emission reduction through a systematic literature review and content analysis, which identified twenty-one variables classified into four clusters. These clusters included the following: (i) FE f1 , which is driving style; (ii) FE f2 , which is driving behavior associated with vehicle transmission; (iii) FE f3 , which is driving behavior associated with road design and traffic rules; and (iv) FE f4 , which is driving behavior associated with vehicle operational characteristics. The second phase involves validating phase one findings by applying the Grounded Group Decision Making (GGDM) method. The results of GGDM have established seventeen green driving behaviors. The study conducted the Green Value (GV) analysis for each green behavior on fuel saving and emission reduction. The study found that aggressive driving (GV = 0.16) interferes with the association between fuel consumption, emission and driver's personalities. The research concludes that driver's personalities (including physical, psychological and psychosocial characteristics) have to be integrated for advanced in-vehicle driver assistance system and particularly, for green driving accreditation.

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“…Traffic signal coordination could promote traffic flow and reduced CO 2 and NO x emissions by 10%. Nasir et al [14] conducted vehicle exhaust pollutant emissions tests concerning HC, CO, CO 2 , particulate matter (PM) and NO x under traffic conditions of free-flow conditions, moderate congestion and severe congestion. ey indicated that the shortest path was not the path with the least emissions.…”

Section: Introductionmentioning

confidence: 99%

“…e quantitative evaluations regarding the overall effects of one-way traffic management on traffic network emissions are lacking. Moreover, microscopic emission models and traffic simulation tools are generally applied for traffic emission assessment [14], since it is o en not feasible to evaluate the environmental effects of traffic management measures based on the trial-and-error field experiments. However, the majority of studies using the microscopic traffic simulation with instantaneous emission models in the assessment, did not calibrate and examine the emission models based on the real world emission data that consider vehicle dynamics and di erent vehicle standards in di erent regions [21].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Effects of One-Way Traffic Management on Different Vehicle Exhaust Emissions Using an Integrated Approach

Fan

Gao

Xing

et al. 2019

Journal of Advanced Transportation

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One-way traffic management is a recognized traffic organization to improve traffic efficiency and safety, but its effects on different traffic emissions remains unclear. This paper aims to investigate the impacts of one-way traffic management on three typical vehicle exhaust emissions including Carbonic Oxide (CO), Hydrocarbon Compounds (HC), and Nitrogen Oxides (NOx) in a traffic system using an integrated approach. Field experiment was conducted to collect the vehicular emission data under different traffic conditions using the onboard portable emission measurement system. An instantaneous emission model (i.e., Vehicle Specific Power) is calibrated using the collected field emission data and is incorporated into the microscopic traffic simulation tool VISSIM for quantifying the emissions before and after one-way traffic management through simulation. Two scenarios based on real networks and traffic demands of peak hours in part areas of Shanghai are developed for simulation and evaluation. The results show that in the intersections, the emission rates of COHC, NOx after one-way traffic management is significantly reduced by 20.46%, 21.29% and 21.06%, respectively. In the road sections, the emission rates of CO, HC, NOx in the road sections decrease by 23.38% and 26.29%. The overall CO, HC, NOx emissions in the studied network reduce by 21.34%, 22.29% and 23.77% separately due to one-way traffic management. The results provide insights into the derivative effects of one-way traffic management on traffic emissions in the intersections, road sections and network levels, and thus support scientific traffic management for promoting the sustainability of transport system.

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Reduction of Fuel Consumption and Exhaust Pollutant Using Intelligent Transport Systems

Cited by 54 publications

References 38 publications

A macroscopic traffic model for traffic flow harmonization

A macroscopic traffic model for traffic flow harmonization

Green Driver: Travel Behaviors Revisited on Fuel Saving and Less Emission

Evaluating the Effects of One-Way Traffic Management on Different Vehicle Exhaust Emissions Using an Integrated Approach

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