Knowing where to park in advance is a most wished feature by many drivers. In recent years, many research efforts have been spent to analyse massive amount of parking information, to learn availability trends and thus to predict, within a Parking Guidance and Information (PGI) system, where there is the highest chance to find free parking spaces. The most of these solutions exploits raw data coming from stationary sensors or crowd-sensed by mobile probes. In both the cases, these massive amounts of data present a high level of noise, which heavily affects the quality of availability predictions. In a previous work we demonstrated that a 2-step approach, based on machine learning techniques to filter out noise, improves the quality of parking availability predictions over raw data. In this paper we propose a further advancement of that approach, by including a technique to perform such noise filtering in real-time, with reduced computational efforts. The proposal has been empirically tested on a real-world dataset of on-street parking information from the SFpark project, and compared against a regression model based on SVR, to perform parking availability predictions. Results show that the predictions obtained with the new on-line approach show a better balance between average and entropy in errors distribution with respect to the use of raw data coming from the sensors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    On-Line Filtering of On-Street Parking Data to Improve Availability Predictions


    Contributors:


    Publication date :

    2019-06-01


    Size :

    3220853 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    METHOD FOR FORECASTING PARKING AREA AVAILABILITY OF A STREET SECTION

    CUNHA CARLOS / CHEN RUOBING / MAYER PHILIPP | European Patent Office | 2017

    Free access

    METHOD FOR FORECASTING PARKING AREA AVAILABILITY OF A STREET SECTION

    CUNHA CARLOS / CHEN RUOBING / MAYER PHILIPP | European Patent Office | 2020

    Free access

    Method for forecasting parking area availability of a street section

    CUNHA CARLOS / CHEN RUOBING / MAYER PHILIPP | European Patent Office | 2019

    Free access