卡车与无人车协同作业的应急物资配送研究数据集

针对情景演变下的物资动态需求问题，面向航空、铁路、公路及无人机等多种运输方式建立应急物资动态调度模型，实现群智感知获取实时多维数据基础上的多演化阶段、多运输方式、多物资品类的物流优化调度。为研究卡车-无人车协同配送的路径优化问题，选取了湖南省长沙市宁远市为配送点依据，并利用实际数据和仿真结合的方法进行参数设置。配送网络包括12个镇，4个乡共16个受灾点以及宁远县政府配送中心。各临时配送点有对应的经纬度、需求量、卡车和无人车可达性等信息。配送点的经纬度通过百度地图获取，需求量及可达性基于实际需求设置，数据量6KB。

Aiming at the dynamic material demand problem under scenario evolution, a dynamic emergency material scheduling model is established for multiple transportation modes including aviation, railway, highway, and unmanned aerial vehicles (UAVs), to achieve optimal logistics scheduling covering multi-evolutionary stages, multi-transport modes, and multi-material categories based on real-time multi-dimensional data collected through crowdsourced sensing. To investigate the route optimization problem of truck-unmanned vehicle collaborative delivery, Ningyuan City, Changsha, Hunan Province was selected as the basis for delivery locations. The parameter setting was conducted using a method that combines actual data and simulation. The delivery network consists of 16 disaster-stricken points in total, including 12 towns and 4 townships, as well as the Ningyuan County Government Distribution Center. Each temporary delivery point has corresponding information such as longitude and latitude, demand volume, accessibility to trucks and unmanned vehicles, etc. The longitude and latitude of the delivery points were obtained via Baidu Maps, while the demand volume and accessibility were set based on actual requirements. The total data volume of the dataset is 6 KB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于卡车与无人车协同作业的应急物资配送路径优化问题，基于湖南省长沙市宁远市的16个受灾点（包括12个镇和4个乡）和配送中心，提供经纬度、需求量和车辆可达性等地理与需求数据，用于支持多运输方式动态调度模型的研究。数据集由北京京东乾石科技有限公司创建，属于国家重点研发计划项目，旨在通过实际数据与仿真结合，优化应急物流中的协同配送效率。