交通信息与安全2018，Vol.36Issue(1)：21-27,7.DOI:10.3963/j.issn.1674-4861.2018.01.003
重复驾驶条件下驾驶员记忆增长模型研究
Memory Growth Models of Drivers under Repeated Driving Environment
摘要
Abstract
Memory affects driving behaviors of drivers such as visual search and route planning,and then influences efficiency and safety of road traffic.In order to describe characteristics of drivers′memory variation under repeated driv-ing situations,a driving simulation experiment is designed.Cumulative stimulus of repeated driving in a same scene is studied.A memory scale is adopted to measure memory degrees,and dynamic relationship between memory growth of drivers and the number of repeated driving is analyzed.Models of memory growth of drivers under cumulative stimulus are developed by using Mitscherlich,Modified Weibull,and Richards function,respectively.In addition,fitting effects of these models are compared by overall evaluation indices of adjusted determination coefficient,sum of the squared errors, and root mean square error.The results show that these three models can effectively describe the characteristics of driv-ers′memory growth.In conclusion,the model using Richards function has the best precision,of which the average adjus-ted R-square is 0.988 4,which reveals the essence of memory assimilation and dissimilation.It fits for being applied to study memory growth of drivers under repeated driving situations.关键词
驾驶行为/驾驶员记忆/记忆增长模型/驾驶模拟/Richards方程Key words
driving behavior/memory of drivers/model of memory growth/driving simulation/Richards function分类
交通工程引用本文复制引用
李雪玮,李振龙,赵晓华..重复驾驶条件下驾驶员记忆增长模型研究[J].交通信息与安全,2018,36(1):21-27,7.基金项目
北京市交通工程重点实验室(北京工业大学)开放课题(2017BJUT-JTJD002)资助 （北京工业大学）
