Vehicular emissions prediction with CART-BMARS hybrid models

Urban transportation emissions mitigation: Coupling high-resolution vehicular emissions and traffic models for traffic signal optimization

Article history: Received 18 June 2014 Received in revised form 11 December 2014 Accepted 29 December 2014 Available online 4 May 2015

Regional Distribution of Vehicular Emissions

Application of ANN-ICA Hybrid Algorithm toward Prediction of Engine Power and Exhaust Emissions

Artificial neural network was considered in previous studies for prediction of engine performance and emissions. ICA methodology was inspired in order to optimize the weights of multilayer perceptron (MLP) of artificial neural network so that closer estimation of output results can be achieved. Current paper aimed at prediction of engine power, soot, NOx, CO2, O2, and temperature with the ai...

Pedestrian and Vehicular Traffic Characteristics for Synthetic-Hybrid Mobility Models

Synthetic mobility models can be used to simulate the movement of a traffic unit or a group of traffic units in a telecommunication network. Characteristics of pedestrian and vehicular traffic, such as speed-flow, speed-density and flow density are often neglected in current synthetic mobility models. The analysis, emulation and simulation of telecommunication networks with mobile users using m...

Vehicular Route Prediction In City Environment Based On Statistical Models

Travel route analysis and prediction are essential for the success of many applications in Vehicular Ad-hoc Networks (VANETs). It is challenging to make accurate route prediction for general vehicles in city settings due to several practical issues such as very complicated traffic networks, the highly dynamic real-time traffic conditions and their interaction with driver’s route selections. The...