Traffic Condition Recognition of Probability Neural Network Based on Floating Car Data

2009 ◽  
pp. 1007-1016
Author(s):  
Gengqi Guo ◽  
Chengtao Cao ◽  
Jiuzhong Li ◽  
Shuo Shi
Keyword(s):  
Neural Network ◽  
Traffic Condition ◽  
Floating Car Data ◽  
Probability Neural Network ◽  
Condition Recognition

Coordinate Signal Control in Urban Traffic of Two-Direction Green Wave Based on Genetic BP Neural Network

2013 ◽  
Vol 823 ◽  
pp. 665-668 ◽  
Author(s):  
Shao Jiao Lv ◽  
Chun Gui Li ◽  
Zhe Ming Li ◽  
Qing Kai Zang
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Bp Neural Network ◽  
Urban Traffic ◽  
Signal Control ◽  
Traffic Condition ◽  
Real Time Traffic ◽  
Coordinate Control ◽  
Analytical Algorithm ◽  
Trunk Road

To maximize the bandwidth of green wave of trunk road is a main issue in the research of signal control in urban traffic. However, the traditional analytical algorithmcan not be applied in actual traffic widely. A novel dynamic two-direction green wave coordinate control strategy was proposed to overcome the problem. By combining the genetic BP neural network with the traditional analytical algorithm, the urban traffic of two-direction was controlled coordinately online. Finally, an actual example was presented. It shows that not only the green wave bandwidth, the phase difference of each intersection and the critical cycle of trunk road were optimized according to real-time traffic flow, but also our algorithm can be used in different traffic condition by adjusting the parameters of the model.

Entropie analysis of floating car data systems

2005 ◽  
Vol 2 ◽  
pp. 169-174
Author(s):  
F. Gössel ◽  
E. Michler ◽  
B. Wrase
Keyword(s):  
Field Trials ◽  
Vehicle Speed ◽  
Data Systems ◽  
Traffic Condition ◽  
Time Profiles ◽  
Spatial Segmentation ◽  
Floating Car Data ◽  
Original Variable ◽  
Vehicle Velocity ◽  
Basic Prerequisite

Abstract. The knowledge of the actual traffic state is a basic prerequisite of modern traffic telematic systems. Floating Car Data (FCD) systems are becoming more and more important for the provision of actual and reliable traffic data. In these systems the vehicle velocity is the original variable for the evaluation of the current traffic condition. As real FCDsystems are operating under conditions of limited transmission and processing capacity the analysis of the original variable vehicle speed is of special interest. Entropy considerations are especially useful for the deduction of fundamental restrictions and limitations. The paper analyses velocity-time profiles by means of information entropy. It emphasises in quantification of the information content of velocity-time profiles and the discussion of entropy dynamic in velocity-time profiles. Investigations are based on empirical data derived during field trials. The analysis of entropy dynamic is carried out in two different ways. On one hand velocity differences within a certain interval of time are used, on the other hand the transinformation between velocities in certain time distances was evaluated. One important result is an optimal sample-rate for the detection of velocity data in FCD-systems. The influence of spatial segmentation and of different states of traffic was discussed.

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