A diverse range of measurements collected from the transportation infrastructure facilitate day to day operation, surveillance, forecasting, and dissemination of current condition information to the general public. The mechanisms for assessing current system conditions rely on multiple sensor types and mobile probes. The quality and completeness of traffic data is generally regarded as suboptim...

The purpose of this paper is to define factors that influence the emergence of induced i.e. generated traffic for experts involved in highway feasibility studies. An explanation of the practical methods for forecasting generated traffic is done by reviewing international experiences in the relevant literature. Also, the idea underlying this paper is to explain the different treatments of genera...

For traffic prediction forecasting in WIMAX, generally the genetic algorithm were used ,but due to certain limitation of genetic algorithms, problems was created in the traffic prediction .So there is a need to proposed a new approach that is better than Genetic algorithm .this approach need to update the limitation of the Genetics algorithm. There is a need to enhance the prediction capability...

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic s...

Network systems need to be able to detect malicious activity and characterize it so that proper actions may be taken. This need is clearly demonstrated through the observed growth rate of informational and economic damage caused by intentionally or unintentionally induced attacks, faults, defects, etc. Network traffic characterization needs to take place accurately and quickly in real time to f...

Abstract The design parameters serve as an integral part of developing a robust short-term traffic forecasting model. These include scope determination, input data preparation, output and modelling techniques. This paper takes further leap to analyse the recent trend through systematic literature review based on peer-reviewed articles up 2021. key important findings are summarized along with ch...

In this paper, we propose a strategy to improve the forecasting of traffic accidents in Concepción, Chile. The forecasting strategy consists of four stages: embedding, decomposition, estimation and recomposition. At the first stage, the Hankel matrix is used to embed the original time series. At the second stage, the Singular Value Decomposition (SVD) technique is applied. SVD extracts the sing...

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are...