Vehicles traffic congestion on the road is reflected as delays while traveling. This congestion has a number of negative effects such as energy consumption, wastage of time and increased tailpipes emission of idling vehicles probably bad for our health. Vehicular congestion has become the serious problem and it is getting worse day by day as the growth of the vehicles significantly increased. I...

This paper describes a new approach to assess high-resolution Carbon Dioxide (CO) distribution for the peninsula of Macao Special Administrative Region (S.A.R.). Firstly, two widely used vehicular pollution models, namely Danish Operational Street Pollution Model (OSPM) and United States intersection vehicular pollution model (CAL3QHC), were applied to evaluate the roadside CO concentration fro...

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ ...

The prediction of regional sulfur dioxide (SO2) emission of thermal power belongs to gray system which has small amounts of samples and little information, so a appropriate forecasting method is essential. Based on thermal power industry SO2 emission data from state department authorities, considering the main factors of China's thermal power industry SO2 predicted emission, we established a co...

Vehicular emissions have increased considerably over the years with the increase in traffic. Modern roundabouts can improve traffic flow as well as cut down vehicular emissions and fuel consumption by reducing the vehicle idle time at intersections and thereby creating a positive impact on the environment. The primary focus of this research is to study the impact of modern roundabouts in cuttin...

This paper presents a method for prediction short-term power demand of a vehicular power system. The forecasting of power demand is presented using wavelet decomposition and artificial neural network, a hybrid model which absorbs some merits of wavelet transform and neural network. The power demand time series is first decomposed into a certain number of levels with discreet wavelet transform a...

The traffic flow at an arterial intersection in a congested urban transportation network in the city of Dublin is modelled in this paper. Three different time-series models, viz. random walk model, Holt-Winters’ exponential smoothing technique and seasonal ARIMA model are used for modeling of traffic flow in Dublin. Simulation and short-term forecasting of univariate traffic flow data are done ...