Available Parking Space Prediction Based on Long Short-Term Memory Network


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    Prediction of available parking spaces is the critical technique in the intelligent parking guidance system. The prediction technology based on neural network can achieve high accuracy in short-term prediction. And existing techniques can reach an average absolute prediction error of about 10. However, with the increase of prediction steps or time-span, the prediction accuracy will decrease dramatically. To solve this problem, a prediction method that can keep the characteristics of data changes in the long-span is introduced in this paper. The method uses the fuzzy information granulation to obtain the feature data sets. Then, a long shortterm memory network is trained to predict the future feature data sets. Finally, an interpolation procedure is applied to reconstruct the curve of the parking space. The simulation results show that the proposed method can achieve better prediction accuracy and higher computation efficiency when compared with traditional prediction methods.

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SUN Min, PENG Lei, LI Huiyun. Available Parking Space Prediction Based on Long Short-Term Memory Network[J]. Journal of Integration Technology,2018,7(6):39-48

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  • Online: November 20,2018
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