A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data

Published:2019-02 Issue: Volume:123 Page:274-281
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Osman Osama A.^ORCID,Hajij Mustafa,Karbalaieali Sogand^ORCID,Ishak Sherif^ORCID

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference43 articles.

1. Exploring the impacts of adverse weather conditions on speed and headway behaviors using the SHRP2 naturalistic driving study data;Ahmed,2017

2. The 2nd Strategic Highway Research Program Naturalistic Driving Study Dataset;Anon,2013

3. Traffic Safety Facts 2012 Data: Older Population;Anon,2014

4. Effect of secondary tasks and driver behavior on crash and near-crash risk: naturalistic driving study;Ashley,2017

5. Assessing safety critical braking events in naturalistic driving studies;Bagdadi;Transp. Res. Part F Traffic Psychol. Behav.,2013

Cited by 51 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Intelligent Real-Time Driver Activity Recognition System Using Spatio-Temporal Features;Applied Sciences;2024-09-06

2. A human-in-the-loop ensemble fusion framework for road crash prediction: coping with imbalanced heterogeneous data from the driver-vehicle-environment system;Transportation Letters;2024-09-03

3. Unfolding the dynamics of driving behavior: a machine learning analysis from Germany and Belgium;European Transport Research Review;2024-07-01

4. Text and Voice Message Distraction Detection: A Machine Learning Approach Using Vehicle Trajectory Data;Transportation Research Record: Journal of the Transportation Research Board;2024-06-24

5. Critical review on data-driven approaches for learning from accidents: Comparative analysis and future research;Safety Science;2024-03

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3