Research And Implementation Of Urban On-street Parking Space Availability Prediction And Visual Analysis System

In recent years,due to the sharp increase in the number of vehicles used in China’s cities,The imbalance between on-street parking resources and vehicle number leads to more and more serious problems such as parking difficulties and traffic congestion.Real-time parking availability is of great value to optimize the on-street parking resource utilization and improve congested traffic conditions.However,the existing parking availability sensing system is expensive,which limits its large-scale application in more cities and regions.This paper proposes a parking space prediction algorithm,which is cheap and easy to use in more areas and implements a visual parking space analysis system on this basis.This paper presents the prediction method to predict real-time citywide on-street parking availability at a fine-grained temporal level based on the readily accessible parking meter transactions data and other context data,together with the parking events data reported from a limited number of specially deployed sensors.We design an iterative mechanism to effectively integrate the aggregated inflow prediction and individual parking duration prediction for adequately exploiting the transactions data.Meanwhile,we extract discriminative features from multi-source data,combine multiple-graph convolution neural network and long short-term memory to capture complex Spatial-temporal correlations.Finally,the extensive experimental results based on a four-month real-world on-street parking dataset in Shenzhen,China demonstrates the advantages of our approach over various baselines.Secondly,we implement a visual analysis system of parking space,which mainly includes three functional modules:the overall analysis module of all street parking occupancy,the analysis module of single street parking occupancy,and the display module of available parking space prediction results.Through the realization of the above functions,this system can correctly guide the parking behavior of users,effectively reduce parking time,and assist the relevant departments to optimize the management of on-street parking resources,alleviate the problems of traffic congestion and resource waste.