short-term traffic flow forecasting plays a significant role in the intelligent transportation systems (its), especially for the traffic signal control and the transportation planning research. two mainly problems restrict the forecasting of urban freeway traffic parameters. one is the freeway traffic changes non-regularly under the heterogeneous traffic conditions, and the other is the success...

conclusions there was a decreasing trend in the study and the future years. it seems that implementation of some interventions in the recent decade has had a positive effect on the decline of rta fatalities. nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents. results the mean age of the victims was 37.22 ...

conclusions applying this information can be useful to policy makers and managers for planning and implementing special interventions to prevent and limit future accidental deaths. background traffic accidents are the main cause of deaths in developing countries. fatalities due to traffic accidents are assessed through a three-year time series forecast. objectives the aim of this study is to us...

Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multilayer perceptron neural network and the mutual information (MI) technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and fu...

Short-term traffic forecasting aims to provide more reliable travel information service, so as to assist people in making more reasonable travel decisions. With the increasing availability of traffic data along with the development of communication technology, both the capability and accuracy of travel time forecasting have been significantly enhanced in real-time conditions and a great number ...

1 Introduction This Recommendation is the first in a series of three Recommendations that cover international telecommunications forecasting. In the operation and administration of the international telephone network, proper and successful development depends to a large degree upon estimates for the future. Accordingly, for the planning of equipment and circuit provision and of telephone plant ...

Grey-markov forecasting model of traffic volume was founded by applying the model of GM (1,1) and Markov random process theory. The model utilizes the advantages of Grey-markov GM (1,1) forecasting model and Markov random process in order to discover the developing and varying tendency of the forecasting data sequences of traffic volume. The analysis of an example indicates that the grey-markov...

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting...

Elevator traffic demand forecasting is the essential prerequisite for effectively implementing elevator group control system (EGCS). Considering that there exists lots of abnomal information in elevator traffic caused by subjectivity and occasionality in human behaviour and that observing traffic information continuously is costly and difficult, an improved grey forecasting based method using m...

The effective capacity of inter-urban motorway networks is an essential component of traffic control and information systems, particularly during periods of daily peak flow. However, slightly inaccurate capacity predictions can lead to congestion that has huge social costs in terms of travel time, fuel costs and environment pollution. Therefore, accurate forecasting of the traffic flow during p...