five

Toward the development of a hybrid approach to speed estimation in urban and rural areas|交通速度估计数据集|道路安全数据集

收藏
DataCite Commons2021-07-21 更新2024-07-28 收录
交通速度估计
道路安全
下载链接:
https://tandf.figshare.com/articles/dataset/Toward_the_development_of_a_hybrid_approach_to_speed_estimation_in_urban_and_rural_areas/14842632/1
下载链接
链接失效反馈
资源简介:
Given the strong relationship between road accident and traffic speed, the evaluation and prediction of this latter have always been considered as a critical issue for road safety analysis and for the evaluation of road network safety improvements. Prediction models developed to date mainly focused on spot speed in a rural environment or on running speed in an urban one. Very few analyze the speed estimation in “transition” areas. The objective of this paper is to develop a generalized speed estimation model able to predict mean speed in urban, rural, and “transition” environment as a function of road layout characteristics. It is believed that the proposed estimation tool can be effectively employed by road engineers in the road safety design and retrofitting stage. The basic idea of the paper is to shed some light on this issue by making use of a hybrid estimation approach able to combine the information gathered from both previously mentioned models within a generalized speed adaptation framework that reflects road user behavior. The calibration and validation of the generalized estimation model have been carried out following a collection of Floating Car Data (FCD) on several candidate sites. Preliminary results seem to indicate that the methodology proposed may be effective in estimating the spot speed in two-lane rural and urban arterials. FCD data can be useful to develop more efficient estimation models to better manage the safety of urban and rural roads.
提供机构:
Taylor & Francis
创建时间:
2021-06-24
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作