多方式出行需求短时预测精度功能测试数据集

本数据集中，苏州地理空间栅格数据为苏州市中心城区地理空间数据，将苏州市中心城区用栅格均匀划分，整理为shp文件。公交栅格出行需求数据基于苏州市公交出行刷卡数据，按出发地对应栅格进行集计统计，采集设备为车载收费终端、自动售检票系统（AFC）刷卡设备等。出租车栅格出行需求数据基于苏州市出租车出行上下车数据，按出发地对应栅格进行集计统计，采集设备为车载收费终端等。公共自行车栅格出行需求数据基于苏州市公共自行车OD数据，按出发地对应栅格进行集计统计，采集设备为车载收费终端等。网约车栅格出行需求数据基于苏州市网约车数据，按出发地对应栅格进行集计统计，采集来源为网约车订单信息等。地铁栅格出行需求数据基于苏州市轨道出行刷卡数据，按出发地对应栅格进行集计统计，采集来源为地铁AFC刷卡数据等。数据量196MB。

In this dataset, the Suzhou geospatial raster data refers to the geospatial data of the central urban area of Suzhou. The central urban area of Suzhou is evenly divided into grids and organized into shapefile (SHP) format. The bus raster travel demand data is derived from Suzhou's bus swipe card travel data, which is aggregated and counted based on the grid corresponding to the departure location. The collection equipment includes on-board payment terminals, automatic fare collection (AFC) swipe card devices, etc. The taxi raster travel demand data is based on Suzhou's taxi pick-up and drop-off trip data, aggregated and counted by the grid corresponding to the departure location, with collection equipment including on-board payment terminals and others. The public bicycle raster travel demand data is based on the origin-destination (OD) data of Suzhou's public bicycle system, aggregated and counted by the grid corresponding to the departure location, with collection equipment including on-board payment terminals and others. The online car-hailing raster travel demand data is based on Suzhou's online car-hailing trip data, aggregated and counted by the grid corresponding to the departure location, and the collection sources include online car-hailing order information and others. The subway raster travel demand data is based on Suzhou's rail transit swipe card travel data, aggregated and counted by the grid corresponding to the departure location, with collection sources including subway AFC swipe card data and others. The total data volume is 196 MB.

搜集汇总

背景与挑战

背景概述

该数据集包含苏州市中心城区多方式出行需求的短时预测精度功能测试数据，涵盖公交、出租车、公共自行车、网约车和地铁等多种交通方式的出行需求数据，数据量为196MB。数据集基于实际出行数据采集，用于短时预测特征提取和交通运输工程研究。