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高速公路交通标志的认知及评价综述 被引量:7

A Review on Cognition and Evaluation of Traffic Signs on Expressways
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摘要 交通标志作为高速公路与驾驶人进行信息交流的纽带,是道路交通必不可少的一部分。目前关于交通标志的研究已取得一定的成就,但在某些方面仍存在不足之处。为此从视认性、识别率、驾驶人理解能力以及驾驶水平4个方面分析交通标志认知的影响因素;将有效性评价分为定量评价方法以及定性定量结合的评价方法。并从这2个角度对目前的研究进行综述和评论,结果表明,高速公路与城市道路的差异较大,应考虑二者不同处,对高速公路交通标志认知的影响因素进行研究;由于每个信息中含有的信息量不同,建议引入信息理论,得出准确的信息量阈值;未来需加强不同学科的交叉融合,建议将统计概率模型与认知模型结合起来,建立新的认知模型;驾驶补偿策略和交感神经的兴奋范围是未来重点的研究方向;交通标志大多是以组合的形式出现,未来需要开展对交通标志组的研究。 Traffic signs,as the link of information exchange between highways and drivers,are an essential part of road traffic.At present,some achievements have been made in studying traffic signs,but there are still some shortcom⁃ings in some aspects.Therefore,this paper summarizes influencing factors of recognizing traffic signs.The analysis is performed from legibility,recognition rate,the understanding ability of drivers,and driver's driving level.The effec⁃tiveness evaluation is divided into quantitative analysis and qualitative and quantitative analysis.The results show that there are big differences between the expressways and urban roads,which should be considered to study the influenc⁃ing factors of recognizing traffic signs.Since the amount of information contained in each sign varies,the information theory should be introduced to obtain an accurate threshold of information.In the future,the cross integration of differ⁃ent disciplines should be strengthened.The statistical probability model is combined with a cognitive model to estab⁃lish a new cognitive model.The compensation strategy of driving and the range of sympathetic arousal will be the key directions.Traffic signs mostly appear in the form of combinations,so traffic sign groups should be studied in the future.
作者 王仁杰 周晓宏 WANG Renjie;ZHOU Xiaohong(School of Economics and Management,Anhui Polytechnic University,Wuhu 241000,Anhui,China)
出处 《交通信息与安全》 CSCD 北大核心 2021年第2期9-18,共10页 Journal of Transport Information and Safety
基金 安徽省高校人文社会科学研究重大项目(SK2020ZD20)资助。
关键词 交通标志 高速公路 认知 综述 有效性评价模型 traffic signs expressway cognition review effectiveness evaluation model
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