基于交通标志信息量的驾驶负荷加载有效性研究

过高的驾驶负荷是导致驾驶绩效受损和交通事故的重要原因，因此驾驶行为和交通安全研究中需要采用适当的负荷加载形式；通过试验分析不同信息量的交通标志对驾驶人认知负荷的影响规律，验证交通标志信息量对负荷加载的有效性。基于不同信息量的交通标志，对驾驶人的驾驶负荷进行试验验证。招募44名被试在静态控制环境下进行交通标志认知试验，采用信息理论对交通标志信息量进行量化计算，用不同信息量的交通标志进行认知负荷加载，采集被试对每个标志的主观负荷评价及反应时间。试验结果表明：主观驾驶负荷与交通标志信息量有高度相关性，反应时间随着信息等级的增加而增加；而驾驶人性别和驾驶经验对交通标志视认反应时间和主观驾驶负荷量化没有显著影响，这说明在驾驶试验中，交通标志信息量可以用于驾驶试验中的认知负荷的加载，而这种负荷的加载对于驾驶人的性别和驾驶经验是无差别的。该研究更多地考虑了驾驶人的认知特性，研究成果可用于驾驶负荷试验的次任务加载，帮助进行交通安全理论研究。

Research on the Effectiveness of Driving Workload Based on Traffic Sign Information Volume

Excessive driving workload is the leading contributing factor to driving performance impairment and traffic crashes. Therefore, establishing a controlled workload environment is significant for driving behavior and traffic safety studies. This study aims to evaluate traffic safety by analyzing the cognitive workload of drivers during driving behavior and prove the effectiveness of traffic sign information volume on workload. The driving workload of drivers was tested based on traffic signs with different information volumes. 44 subjects were recruited to conduct a traffic sign cognition experiment under a static controlled cognition environment. The traffic sign information volume was quantified by using information theory. Different complex traffic signs were used for loading cognitive workload. Subjective workload assessment and recognition time of subjects for every traffic sign were collected. The results reveal that workload is highly related to the volume of information on traffic signs, and reaction time increases with information volume, while the driver's gender and driving experience have no significant effect on the reaction time and the subjective driving workload quantification. This shows that the cognitive workload of the subsequent driving experiment can be controlled by the information volume on traffic signs, with no difference due to gender and driving experience. The research results can be used to evaluate traffic safety by involving a secondary task of driving, which better considers the drivers' cognitive characteristics.