Artificial Neural Networks (ANN) have been shown to perform well in classifying and prediction problems. Such a peculiarity was exploited to evaluate the flow-density relationship of a motorway section so as to define the time and spacing stability or instability of its traffic flow. The data base used in this study was built up on the basis ofthe data collected over the ltalian motorway running between Padua and Mestre. These data are suitable for the present study be cause they provi de a sample of t ime an d space, along with the collection of data on weather conditions
The paper deals with the identification of variables and models that can explain why a certain sever...
80/20 SPRTo achieve the objectives of this study, a neural network based system will be developed, u...
A neural network model for predicting the traffic speed under adverse weather conditions is proposed...
Artificial Neural Networks (ANN) have been shown to perform well in classifying and prediction probl...
AbstractThis study applies Artificial Neural Network (ANN) for short term prediction of traffic flow...
Vehicle headways play a role of paramount importance in many traffic engineering applications. They ...
As traffic demands are ever increasing and building new infrastructure poses challenges in densely p...
AbstractTo be able to predict reliably traffic conditions over the short term (15 minutes into the f...
This paper discusses a neural network development approach based on an exponential smoothing method ...
In this paper, were conducted a study on the noise produced by traffic on the freeway. In particular...
It is possible for routing and navigation applications to provide more accurate and more effective r...
This study proposes a Neural Network (NN) classifier model for predicting crashes on freeways and ar...
Proper prediction of traffic flow parameters is an essential component of any proactive traffic cont...
An investigation was made as to how short-term traffic forecasting on motorways and other trunk road...
Non-recurring congestion caused by incidents is a major source of traffic delay in freeway systems. ...
The paper deals with the identification of variables and models that can explain why a certain sever...
80/20 SPRTo achieve the objectives of this study, a neural network based system will be developed, u...
A neural network model for predicting the traffic speed under adverse weather conditions is proposed...
Artificial Neural Networks (ANN) have been shown to perform well in classifying and prediction probl...
AbstractThis study applies Artificial Neural Network (ANN) for short term prediction of traffic flow...
Vehicle headways play a role of paramount importance in many traffic engineering applications. They ...
As traffic demands are ever increasing and building new infrastructure poses challenges in densely p...
AbstractTo be able to predict reliably traffic conditions over the short term (15 minutes into the f...
This paper discusses a neural network development approach based on an exponential smoothing method ...
In this paper, were conducted a study on the noise produced by traffic on the freeway. In particular...
It is possible for routing and navigation applications to provide more accurate and more effective r...
This study proposes a Neural Network (NN) classifier model for predicting crashes on freeways and ar...
Proper prediction of traffic flow parameters is an essential component of any proactive traffic cont...
An investigation was made as to how short-term traffic forecasting on motorways and other trunk road...
Non-recurring congestion caused by incidents is a major source of traffic delay in freeway systems. ...
The paper deals with the identification of variables and models that can explain why a certain sever...
80/20 SPRTo achieve the objectives of this study, a neural network based system will be developed, u...
A neural network model for predicting the traffic speed under adverse weather conditions is proposed...