Forecasting road traffic conditions using a context-based random forest algorithm

Evans Jonny; Waterson Ben; Hamilton Andrew

首页> 外文期刊>Transportation planning and technology >Forecasting road traffic conditions using a context-based random forest algorithm

【24h】

Forecasting road traffic conditions using a context-based random forest algorithm

机译：使用基于上下文的随机森林算法预测道路交通状况

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

With the ability to accurately forecast road traffic conditions several hours, days and even months ahead of time, both travellers and network managers can take pro-active measures to minimise congestion, saving time, money and emissions. This study evaluates a previously developed random forest algorithm, RoadCast, which was designed to achieve this task. RoadCast incorporates contexts using machine learning to forecast more accurately contexts such as public holidays, sporting events and school term dates. This paper evaluates the potential of RoadCast as a traffic forecasting algorithm for use in Intelligent Transport System applications. Tests are undertaken using a number of different forecast horizons and varying amounts of training data, and an implementation procedure is recommended.

机译：凭借能够提前数小时，数天甚至数月准确预测道路交通状况的能力，旅行者和网络管理员都可以采取积极措施以最大程度地减少交通拥堵，节省时间，金钱和排放。这项研究评估了以前开发的随机森林算法RoadCast，该算法旨在实现此任务。 RoadCast结合了使用机器学习的上下文，可以更准确地预测诸如公众假期，体育赛事和学校开学日期之类的上下文。本文评估了RoadCast作为交通预测算法在智能交通系统应用中使用的潜力。使用许多不同的预测范围和不同数量的培训数据进行测试，并建议实施程序。

著录项

来源
《Transportation planning and technology》 |2019年第6期|554-572|共19页
作者
Evans Jonny; Waterson Ben; Hamilton Andrew;
展开▼
作者单位

Univ Southampton, Transportat Res Grp, Bldg 176,Boldrewood Innovat Campus, Southampton, Hants, England;

Univ Southampton, Transportat Res Grp, Bldg 176,Boldrewood Innovat Campus, Southampton, Hants, England;

Siemens Mobil Ltd, Poole, Dorset, England;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
Traffic forecasting; random forest; loop detector; machine learning; context; RoadCast;

机译：交通预测;随机森林;循环探测器;机器学习;背景;roadcast;

相似文献

外文文献
中文文献
专利

1. A hybrid forecasting framework based on support vector regression with a modified genetic algorithm and a random forest for traffic flow prediction [J] . Lizong Zhang, Nawaf R Alharbe, Guangchun Luo, Tsinghua Science and Technology . 2018,第4期

机译：基于支持向量回归与改进遗传算法和随机森林的交通流量混合预测框架
2. A Hybrid Forecasting Framework Based on Support Vector Regression with a Modified Genetic Algorithm and a Random Forest for Traffic Flow Prediction [J] . Lizong Zhang, Nawaf R Alharbe, Guangchun Luo, 清华大学学报（英文版） . 2018,第004期

机译：基于支持向量回归与改进遗传算法和随机森林的交通流量混合预测框架
3. Traffic Flow Forecasting for Road Tunnel Using PSO-GPR Algorithm with Combined Kernel Function [J] . Guo Jiaqi, Chen Fan, Xu Chong Mathematical Problems in Engineering . 2017,第pta8期

机译：结合核函数的PSO-GPR算法在公路隧道交通流量预测中的应用
4. A Random Forest Algorithm Applied to Condition-Based Wastewater Deterioration Modeling and Forecasting [C] . D. Vitorino, S.T. Coelho, P. Santos Water Distribution System Analysis Conference . 2015

机译：一种随机林算法应用于条件的污水劣化建模与预测
5. Analytical models and efficient dimensioning algorithms for communication systems in randomly changing traffic environments [D] . Tian, Wenhong 2008

机译：随机变化交通环境中通信系统的分析模型和有效尺寸确定算法
6. Impact of passenger engagement through road safety bus stickers in public service vehicles on road traffic crashes in Zambia: a randomized controlled trial [O] . Sydney Chauwa Phiri, Marta R. Prescott, Margaret L. Prust, 2018

机译：乘坐公共服务车辆的道路安全公交车贴纸的乘客参与对赞比亚道路交通事故的影响：一项随机对照试验
7. A hybrid forecasting framework based on support vector regression with a modified genetic algorithm and a random forest for traffic flow prediction [O] . Lizong Zhang, Nawaf R Alharbe, Guangchun Luo, 2018

机译：一种基于支持向量回归的混合预测框架与修改遗传算法和随机林进行交通流预测

Forecasting road traffic conditions using a context-based random forest algorithm

摘要

著录项

相似文献

相关主题

期刊订阅