In recent years, the volume of traffic is rapidly increasing. When vehicles running through the tunnel are more intensive or move slowly, the tunnel environment occurs deteriorated sharply, which affects the normal operation of the vehicle in the tunnel. This paper uses the result of previous mining association rules to select feature items and to establish four training samples divided by time...

Abstract. The operation of the urban traffic exist a high degree of complexity and randomness. The key of Intelligent Transportation System is the real-time and accurate traffic flow prediction. Taking effective measures in a timely manner would prevent the occurrence of traffic accidents since traffic congestion brings much traffic inconvenience to people. Real-time traffic flow prediction pla...

In recent years, a number of studies had been done on the issues of fastest navigation path planning due to wide applications. Most of previous studies focused on the fastest path planning by mining historical traffic logs. However, the real time traffic situations in the road network always vary continuously due to the occurrences of traffic events. Therefore, a better planning strategy should...

In its simplest form, the traffic flow prediction problem is restricted to predicting a single time-step into the future. Multi-step traffic flow prediction extends this set-up to the case where predicting multiple time-steps into the future based on some finite history is of interest. This problem is significantly more difficult than its single-step variant and is known to suffer from degradat...

Network traffic flow prediction model is fundamental to the network performance evaluation and the design of network control scheme which is crucial for the success of high-speed networks. Aiming at shortcoming of the conventional network traffic time series prediction model and the problem that BP training algorithms easily plunge into local solution, a network traffic prediction model based o...

The paper proposes a traffic speed prediction algorithm for urban road traffic networks. The motivation of the prediction is to provide short time forecast in order to support ITS (Intelligent Transport System) functionalities, such as traveler information systems, route guidance (navigation) systems, as well as adaptive traffic control systems. A potential and efficient solution to this proble...

Real-time and accurate short-term traffic flow prediction is the premise and key of intelligent traffic control and guidance system. According to this problem, this paper put forward a prediction model based on multivariable phase space reconstruction and least squares support vector machine (LSSVM). First, the model confirms embedding dimension and delay time of the traffic flow, occupancy and...

The growth in magnitude and various impacts of traffic noise has created an increasing attention on the prediction and control of noise levels. This study aims at developing a noise level prediction model under the local conditions of Amman, the capital of Jordan. Thirty four sites, representing different characteristics, were selected for use in model development. The resulting prediction mode...