Assessing the Need for Applying Multimodal Speed Distribution in Road Transport Macro Emission Estimation

Török, Ádám; Zefreh, Mohammad Maghrour

doi:10.14513/actatechjaur.v9.n2.402

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…The development of mathematical tools focused on the modelling of the speed distribution in a traffic flow is widely reported in the scientific literature [21][22][23][24]. Many papers concern this problem since vehicles speed distribution is an important input parameter in lots of issues, such as kinematical traffic simulation model, road design, speed limit evaluation, road traffic noise prediction, traffic safety evaluation, bicycle performance evaluation, analysis of pedestrian walking, road transport emission estimation [25][26][27][28][29][30][31][32][33], [46] etc. Since 1940 majority of papers considered speed distribution as Gaussian or Normal distribution (Fig.…”

Section: Methodsmentioning

confidence: 99%

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

2016

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Abstract. Underlying a fundamental diagram is a relation between traffic speed and density which roughly corresponds to drivers' speed choices under varying car-following distances. Stochastic and deterministic models are mainly two different categories of speed-density models. The advantages of deterministic models are their mathematical simplicity and analytical tractability though their results will show just the average parameters. Although the stochastic models may represent more accurate results taking uncertainty into account, they are often hard to use and analytically not tractable. The aim of this paper is to investigate the possibility of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions. Monte Carlo Method has been used to generate different speed distributions based on different traffic conditions and consequently generating their relevant densities. Surveying the relation between the mentioned speed distributions and the obtained densities kept the chance of presenting a model which is neither completely deterministic nor completely stochastic but easy to use and understand which incorporates different traffic conditions and speed distributions.

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Section: Methodsmentioning

confidence: 99%

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

2016

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“…multimodal. For example, in measurement of speed distribution of road traffic vehicular data is multimodal (Torok and Zefreh, 2016), where the authors found that the emission level for applying combined multimodal speed distribution function was lower as compared to unimodal speed distribution. Haze particle size in a chemically oxidising atmosphere follows multimodal distribution (Fan et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Multimodal Extension of the Balakrishnan Alpha Skew Normal Distribution: Properties and Applications

Shah¹,

Hazarika

Pathak³

et al. 2023

Pak.j.stat.oper.res.

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This paper introduces a new class of Balakrishnan distribution by extending the multimodal skew-normal distribution proposed by Chakraborty et al. (2015). Statistical properties of the new family of distributions are studied in detail. In particular, explicit expressions of the density and distribution function, moments, skewness, kurtosis and the moments generating function are derived. Furthermore, estimation of the parameters using the maximum likelihood method of the new family of distributions is considered. Finally, the paper ends with an illustration of real-life data sets and then comparing the value of Akaike Information Criterion and Bayesian information criterion of the new distribution with some other known distributions. For the nested models, the Likelihood Ratio Test is carried out.

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“…In the current study, different traffic conditions have been represented by the distribution of traffic speed in that traffic condition obtained by on-field data collection. It is worth to mention that the role of speed distribution on road traffic emission [29] and noise has been investigated in the literature. For instance, the effects of speed distributions on the Harmonoise model predictions have been investigated by [30].…”

Section: Introductionmentioning

confidence: 99%

Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

Zefreh

Török

2018

Journal of Advanced Transportation

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Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.

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Assessing the Need for Applying Multimodal Speed Distribution in Road Transport Macro Emission Estimation

Cited by 5 publications

References 28 publications

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

Assessing the Possibility of Presenting a Semi-Stochastic Speed-Density Function

The Multimodal Extension of the Balakrishnan Alpha Skew Normal Distribution: Properties and Applications

Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

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