Simulation and Evaluation of Scalable Demand Transportation using Wireless Network

使用无线网络的可扩展需求运输的仿真和评估

• 批准号: 23710177
• 负责人: MUKAI Naoto
• 金额: $ 2万
• 依托单位: Sugiyama Jogakuen University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Young Scientists (B)
• 财政年份: 2011
• 资助国家: 日本
• 起止时间: 2011 至 2012
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23710177/
• 关键词: デマンド型交通; タクシープローブデータ; 交通ビッグデータ; 交通システム; デマンド交通; 無線ネットワーク; プローブデータ; 交通シミュレータ; 車両配送問題

The objective of this research is to improve the efficiency of demand-based transportation by using collected information of vehicle and customers via the wireless network. At the beginning, we tried to find a correlation between customer demand and other factors (i.e., time zone, a day of the week, and so on) from taxi probe data in 23 wards of Tokyo. We believe that this result will contribute to improve the assignment of vehicles in the city. Moreover, in order to analyze the collected information via network in real-time, we adopted "Hadoop Map Reduce" which is one of the distributed processing software. We realized the online visualization system for vehicle distribution and vehicle flow by using its technology.

本研究的目的是通过无线网络收集车辆和客户的信息，以提高基于需求的交通效率。一开始，我们试图从东京23个区出租车探测数据中找到客户需求与其他因素（即时区、一周中的某一天等）之间的相关性。我们相信这一结果将有助于改善城市车辆的分配。此外，为了对通过网络采集到的信息进行实时分析，我们采用了分布式处理软件之一“Hadoop Map Reduce”。利用其技术实现了车辆分布和车辆流量的在线可视化系统。

项目成果

Knowledge Discovery from Taxi Probe Information in Tokyo by Using Hadoop MapReduce

使用 Hadoop MapReduce 从东京出租车探测信息中发现知识

• 作者: Naoto Mukai

Optimization of Charging Station Placement by Using Taxi Probe Data for On-Demand Electrical Bus System

• DOI: 10.1007/978-3-642-23854-3_64
• 发表时间: 2011-09
• 作者: H. Kameda;Naoto Mukai

Taxi Demand Forecasting Based on Taxi Probe Data by Neural Network

• DOI: 10.1007/978-3-642-29934-6_57
• 发表时间: 2012
• 作者: Naoto Mukai;Naoto Yoden

Knowledge Discovery from Taxi Probe Information in Tokyo by Using Hadoop Map Reduce

使用 Hadoop MapReduce 从东京出租车探测信息中发现知识

• 发表时间: 2013
• 期刊: Proceedings of 20th ITS World Congress Tokyo 2013, Technical /Scientific Session, 20131000
• 作者: Shogo Kato;Yoshinori Iizuka;Satoko Tsuru;佐久間 大;Naoto Mukai
• 通讯作者: Naoto Mukai