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Xiang Huaikun
Shenzhen Polytechnic

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Research on Short-term Traffic Forecast Algorithm based on Cloud Model Xiang Huaikun
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Short-term traffic flow is difficult to predict because of high uncertainty. This paper proposes a short-term traffic forecast algorithm based on cloud similarity. By taking advantage of quantitative and qualitative cloud model mutual conversion function and traffic flow predictability, the historical traffic data can be processed with cloud transformation. Set the current traffic cloud as a standard, traverse the historical traffic cloud to find the best traffic flow period which is with best similarities to the current traffic clouds. Set the future short-term traffic flow of this very period of time as the prediction result of the current period of time. Experiments show that the average prediction error was 3.25 (vehicles) and the prediction error distribution probability was 0.29. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4655
Research on the BP neural Network of Bus Unsafe Driving Behavior Xiang Huaikun
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

The security issue of urban bus is increasingly prominent in our country. Promoting scientific and reasonable unsafe driving events record system is an effective way to improve the level of public transport safety management. At the same time, the reasonable record system contribute to make the correct bus driving behavior, and it is also can reduce the loss of public traffic resources. At first, this paper puts forward using tri-axial acceleration sensor to collect the data of the car. Then classifying of bus driving behavior, setting up a series of driving behavior model, including the brake model, throttle model, a sharp turn model, according to the driving behavior model of data processing, and further by BP neural network to establish a BP neural network to effectively supervise bus driver's driving behavior. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4657
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