In this paper, we show anew image sensor for measuring traffic flow. The image sensor is set at an intersection. The image sensor measures t r af f i c flow by vehicle tracking. The tracking is done by gray level pattern matching. Gray level pattern matching is suitable for outdoor use since it is robust against change of scene brightness. Then we provide the hardware for high speed gray level ...

Traffic conditions vary over time, and therefore, traffic behavior should be modeled as a stochastic process. In this study, a probabilistic approach utilizing Autocorrelation is proposed to model the stochastic variation of traffic conditions, and subsequently, predict the traffic conditions. Using autocorrelation of the time series samples of density and flow which are collected from segments...

Problem of traffic jams is common in large cities. Urban traffic control systems aim to solve this problem. The major difficulty in urban traffic is large number of variables for representing the state of traffc, such as traffic flow,speed, and density. Lack of precise relations between these variables is another problem. In this paper, we present a new model for traffic flow and introduce a tr...

It is an important to quickly and accurately forecasting road network traffic flow in intelligent transportation systems, Aiming at the forecasting problem of short-term traffic flow, this paper proposed a traffic flow prediction algorithm, which based on traffic flow sequence partition and neural network model. Firstly, the algorithm divided the traffic flow into different patterns and time se...

When monitoring network traffic, a flow measurement approach can provide the advantage of data reduction in near real-time. RTFM, the IETF’s standard, generalised architecture for measuring traffic flows, and NeTraMet, an open-source implementation of that architecture, are introduced. The results of a NeTraMet usage survey are presented, together with a detailed description of the NeTraMet com...

The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...

203 words) In ITS (Intelligent Transportation System) equipped urban transportation systems noncritical junctions are often ignored in short-term traffic condition prediction algorithms as the traffic data collection systems in these junctions are not adequate. The paper proposes a shortterm traffic volume model based on a combination of discrete wavelet transform (DWT) and Bayesian hierarchica...

the performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. one of the most applicable traffic flow model in traffic control and management is lwr or metanet model. practically, key parameters in lwr model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...