Select Language

公开数据集

出租车服务轨迹-预测挑战,ECMLPKDD2015数据集

出租车服务轨迹-预测挑战,ECMLPKDD2015数据集

Scene:

Automobiles and Vehicles

Data Type:

Clustering
所需积分:9 去赚积分?
  • 281浏览
  • 0下载
  • 0点赞
  • 收藏
  • 分享

Data Preview ? 509M

    Data Structure ?

    *数据结构实际以真实数据为准

    Challenge Chair: Luis Moreira-Matias

    Steering Committee:
    - Michel Ferreira
    - Joao Mendes-Moreira

    tst.challenge '@' ecmlpkdd2015.org

    http://www.geolink.pt/ecmlpkdd2015-challenge/whoweare.html


    Data Set Information:

    For complete information see the official challenge page:
    [Web link]


    Attribute Information:

    Each data sample corresponds to one completed trip. It contains a total of 9 (nine) features, described as follows:

    TRIP_ID: (String) It contains a unique identifier for each trip;

    CALL_TYPE: (char) It identifies the way used to demand this service. It may contain one of three possible values:
     - 'A' if this trip was dispatched from the central;
     - 'B' if this trip was demanded directly to a taxi driver at a specific stand;
     - 'C' otherwise (i.e. a trip demanded on a random street).

    ORIGIN_CALL: (integer) It contains a unique identifier for each phone number which was used to demand, at least, one service. It identifies the trip's customer if CALL_TYPE='A'. Otherwise, it assumes a NULL value;

    ORIGIN_STAND: (integer): It contains a unique identifier for the taxi stand. It identifies the starting point of the trip if CALL_TYPE='B'. Otherwise, it assumes a NULL value;

    TAXI_ID: (integer): It contains a unique identifier for the taxi driver that performed each trip;

    TIMESTAMP: (integer) Unix Timestamp (in seconds). It identifies the trip's start;

    DAYTYPE: (char) It identifies the daytype of the trip's start. It assumes one of three possible values:
     - 'B' if this trip started on a holiday or any other special day (i.e. extending holidays, floating holidays, etc.);
     - 'C' if the trip started on a day before a type-B day;
     - 'A' otherwise (i.e. a normal day, workday or weekend).

    importANT NOTICE: This field has not been correctly calculated. Please see the following links as reliable sources for official holidays in Portugal.
    [Web link]
    [Web link]

    MISSING_data: (Boolean) It is FALSE when the GPS data stream is complete and TRUE whenever one (or more) locations are missing;

    POLYLINE: (String): It contains a list of GPS coordinates (i.e. WGS84 format) mapped as a string. The beginning and the end of the string are identified with brackets (i.e. [ and ], respectively). Each pair of coordinates is also identified by the same brackets as [LONGITUDE, LATITUDE]. This list contains one pair of coordinates for each 15 seconds of trip. The last list item corresponds to the trip's destination while the first one represents its start.


    Relevant Papers:

    Moreira-Matias L., Gama J., Ferreira M., Mendes-Moreira J. and Damas L.,: "Time-Evolving OD Matrix Estimation using high-speed GPS data streams". In: Expert Systems with Applications, vol. 44, pp. 275-288, February (2016)

    Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., Damas, L., ”Predicting Taxi–Passenger Demand Using Streaming Data”. In: IEEE Transactions on Intelligent Transportation Systems, vol.14, no.3, pp.1393-1402, September (2013)



    Citation Request:

    Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., Damas, L., ”Predicting Taxi–Passenger Demand Using Streaming Data”. In: IEEE Transactions on Intelligent Transportation Systems, vol.14, no.3, pp.1393-1402, September (2013)

    0相关评论
    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。