scholarly journals Modelling road traffic Noise under heterogeneous traffic conditions using the graph-theoretic approach

2021 ◽  
Author(s):  
Towseef Ahmed Gilani ◽  
Mohammad Shafi Mir
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Heterogeneous Traffic ◽  
Road Traffic Noise ◽  
Theoretic Approach ◽  
Graph Theoretic ◽  
Traffic Conditions ◽  
Graph Theoretic Approach

scholarly journals Integrated road traffic noise mapping in urban Indian context

Noise Mapping ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 99-113 ◽  
Author(s):  
Dipeshkumar R. Sonaviya ◽  
Bhaven N. Tandel
Keyword(s):  
Prediction Models ◽  
Road Traffic ◽  
Traffic Noise ◽  
Traffic Volume ◽  
Heterogeneous Traffic ◽  
Road Traffic Noise ◽  
Noise Mapping ◽  
Traffic Conditions ◽  
Road Geometry ◽  
Vehicular Speed

AbstractRoad traffic noise has been recognized as a serious issue that affects the urban regions. Due to urbanization and industrialization, transportation in urban areas has increased. Traffic noise characteristics in cities belonging to a developing country like India are highly varied compared to developed nations because of its heterogeneous conditions. The objective of the research study is to assess noise pollution due to heterogeneous traffic conditions and the impact of horn honking due to un-authorized parked vehicles on the main roadside. Noise mapping has been done using the computer simulation model by taking various noise sources and noise propagation to the receiver point. Traffic volume, vehicular speed, noise levels, road geometry, un-authorized parking, and horn honking were measured on tier-II city roads in Surat, India. The study showed not so significant correlation between traffic volume, road geometry, vehicular speed and equivalent noise due to heterogeneous road traffic conditions. Further, analysis of traffic noise showed that horn honking due to un-authorized parked vehicles contributed an additional up to 11 dB (A), which is quite significant. The prediction models such as U.K’s CoRTN, U.S’s TNM, Germany’s RLS-90 and their modified versions have limited applicability for heterogeneity. Hence, the noise prediction models, which can be used for homogeneous road traffic conditions are not successfully applicable in heterogeneous road traffic conditions. In this research, a new horn honking correction factor is introduced with respect to unauthorized parked vehicles. The horn honking correction values can be integrated into noise model RLS-90, while assessing heterogeneous traffic conditions.

scholarly journals An Empirical Model of Road Traffic Noise on Heterogeneous Traffic Situation

2018 ◽  
Vol 203 ◽  
pp. 03002
Author(s):  
Muralia Hustim ◽  
Isran M. Ramli
Keyword(s):  
Prediction Model ◽  
Empirical Model ◽  
Noise Level ◽  
Road Traffic ◽  
Traffic Noise ◽  
Empirical Relationship ◽  
Heterogeneous Traffic ◽  
Road Traffic Noise ◽  
Traffic Situation ◽  
The Road

The motorcycle domination on heterogeneous traffic situation in many cities in developing countries including Indonesia leads to the decreasing of environment qualities such noise pollution. Regarding the road traffic noise (RTN) pollution, this paper attempts to develop an empirical model for a RTN prediction model. The model based on a motorcycle unit as reference unit to consider flow rate of the road traffic which dominated by motorcycles. The study collected the RTN data such volume of each vehicle types, i.e., motorcycle; light vehicle; and high vehicle, and the noise level on the forty arterial roads in Makassar, Indonesia. The survey methods based on the traffic count method and the measurement noise level using a video camera and a sound level meter, respectively. We collected data during ten minutes of each one-hour period of each road. The empirical relationship models between the noise level and the traffic volume based on the motorcycle unit were developed using various types of regression models. The results showed that the polynomial model is more significant than the other models. We expected that the model provides a basic RTN prediction model in order to simulate some measures of the traffic management system in reducing the RTN level in Makassar City.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Maghrour Zefreh ◽  
Adam Torok
Keyword(s):  
Traffic Flow ◽  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Traffic Lights ◽  
Urban Road ◽  
Traffic Conditions

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.

scholarly journals Influence of Honking on the Road Traffic Noise Generated at Urban Rotaries for Heterogeneous Traffic

2020 ◽  
Vol 24 (1) ◽  
pp. 23-42
Author(s):  
Kamineni Aditya ◽  
Venkaiah Chowdary
Keyword(s):  
Noise Level ◽  
Road Traffic ◽  
Noise Analysis ◽  
Traffic Noise ◽  
Heterogeneous Traffic ◽  
Road Traffic Noise ◽  
Good Precision ◽  
Heavy Vehicles ◽  
Noise Levels ◽  
Noise Data

AbstractThis paper presents a study conducted at major rotaries for quantifying the traffic noise levels by considering the vehicle volume and their respective honking as governing parameters for heterogeneous traffic. Traffic volume and traffic noise data was collected using a digital video camera and a class 1 sound level meter, respectively. The traffic noise data was analysed using noise tools for identifying the noise level variation. The data collected was subjected to statistical analysis for light, medium and heavy vehicles, and their contribution towards noise levels is proven to be effective with the forthright fact that, heavy vehicles and their corresponding honking were majorly affecting the equivalent noise level compared to other vehicular proportion. An equivalent noise level [LAeq (dB)] rise of 2 to 6 dB (A) is solely caused by heavy vehicles, which is an important observation to be considered for traffic noise analysis at the rotaries. Based on the obtained results from one of the rotaries, noise prediction model is developed for estimating the LAeq (dB), which is able to predict the noise levels with good precision when validated with the data collected at second rotary intersection for different vehicle volumes.

Modelling and Analysis of Urban Traffic Noise System Using Algebraic Graph Theoretic Approach

2016 ◽  
Vol 44 (2) ◽  
pp. 249-261 ◽  
Author(s):  
Daljeet Singh ◽  
S. P. Nigam ◽  
V. P. Agrawal ◽  
Maneek Kumar
Keyword(s):  
Traffic Noise ◽  
Urban Traffic ◽  
Theoretic Approach ◽  
Graph Theoretic ◽  
Graph Theoretic Approach ◽  
Urban Traffic Noise

scholarly journals 2-D noise maps for tier-2 city urban Indian roads

Noise Mapping ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Dipeshkumar R. Sonaviya ◽  
Bhaven N. Tandel
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Field Measurements ◽  
Noise Pollution ◽  
Heterogeneous Traffic ◽  
Computer Simulation Model ◽  
Road Traffic Noise ◽  
Noise Mapping ◽  
Traffic Condition ◽  
Traffic Composition

Abstract In today’s era, vehicular noise pollution has been identified as a serious danger that influence the attribute of the urban regions. To identify the influence of noise effects, noise maps are very useful. A noise mapping study has been carried out to study the propagation of urban road traffic noise in the areas along with field measurements. The computer simulation model (Sound- PLAN software) is used to developed noise maps. In developing nations like India, traffic composition is heterogeneous. These traffic compositions contain vehicles, which have different sizes, speeds variations and operating systems. Because of fluctuating speeds, deficiency of lane disciplines, and non-authorized parking on main road lanes, honking events becomes inevitable, which changes and affects the urban soundscape of nations like India. Due to horn events (heterogeneous traffic condition), noise level (LAeq) increase by 0.5–8 dB (A) as compared to homogeneous traffic conditions.

Road Traffic Noise Prediction Model

2012 ◽  
Vol 3 (4) ◽  
pp. 110-112
Author(s):  
Rahul Singh ◽  
◽  
Parveen Bawa ◽  
Ranjan Kumar Thakur
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction
Sign in / Sign up

Export Citation Format

Share Document