为探究不同模态转换下任务切换对监控人员警觉度衰减现象的影响,采用脑电实验法,设计了危险动作识别、危险场景识别等任务,并结合行为数据及事件相关电位(Event Related Potential,ERP)技术进行综合分析;实验重点考察在任务切换过程中,...为探究不同模态转换下任务切换对监控人员警觉度衰减现象的影响,采用脑电实验法,设计了危险动作识别、危险场景识别等任务,并结合行为数据及事件相关电位(Event Related Potential,ERP)技术进行综合分析;实验重点考察在任务切换过程中,不同模态的任务之间进行切换对监控人员警觉度的具体影响;通过对煤矿监控调度人员的实证研究,揭示了切换任务的模态差异性对监控员警觉度的影响及其内在机制。结果表明:当在相同刺激任务间进行切换时带来的工作绩效下降,主要原因在于任务切换产生的切换成本导致注意力分散,具体体现在任务切换后P300和P200平均波幅的升高;但是在不同刺激任务间进行切换时,尤其是切换到听觉刺激任务时,被试者的警觉度水平反而得到了一定程度的提升。展开更多
The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones ge...The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones generally by crash frequency or density,which is effective for roadway engineering improvements but neglects characteristics related to other improvements such as safety education.As safety education would be more effective if targeted at the residences of crash-involved road users,the traditional approach to hot zones may therefore provide biased results for such alternative countermeasures.After confirming that 77.17%of NMV crashes occurred outside the involved riders’areas of residence,this study compared the differences between the locations of crashes and the residences of NMV crash-involved riders in safety influencing factors and hot zone identification.A Poisson lognormal bivariate conditional autoregressive(PLN-BCAR)model was developed to account for potential correlations between crashes and involved riders.The model was compared with the univariate Poisson lognormal conditional autoregressive(UPLN-CAR)model and the bivariate Poisson lognormal conditional autoregressive(BPLNCAR)model;the PLN-BCAR model outperformed the other two models in its better interpretation of the influencing factors and its more efficient parameter estimation.Model results indicated that crashes were mainly associated with roadway and land use characteristics,while involved road users were mainly associated with socioeconomic and land use characteristics.The potential for safety improvement method was adopted to identify hot zones for countermeasure implementation.Results showed over 60%of the identified hot zones were inconsistent:they needed improvement in either engineering or education but not both.These findings can help target the type of improvement to better utilize resources for NMV safety.展开更多
文摘为探究不同模态转换下任务切换对监控人员警觉度衰减现象的影响,采用脑电实验法,设计了危险动作识别、危险场景识别等任务,并结合行为数据及事件相关电位(Event Related Potential,ERP)技术进行综合分析;实验重点考察在任务切换过程中,不同模态的任务之间进行切换对监控人员警觉度的具体影响;通过对煤矿监控调度人员的实证研究,揭示了切换任务的模态差异性对监控员警觉度的影响及其内在机制。结果表明:当在相同刺激任务间进行切换时带来的工作绩效下降,主要原因在于任务切换产生的切换成本导致注意力分散,具体体现在任务切换后P300和P200平均波幅的升高;但是在不同刺激任务间进行切换时,尤其是切换到听觉刺激任务时,被试者的警觉度水平反而得到了一定程度的提升。
基金the International Science and Technology Cooperation Programme of China(2017YFE0134500)。
文摘The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones generally by crash frequency or density,which is effective for roadway engineering improvements but neglects characteristics related to other improvements such as safety education.As safety education would be more effective if targeted at the residences of crash-involved road users,the traditional approach to hot zones may therefore provide biased results for such alternative countermeasures.After confirming that 77.17%of NMV crashes occurred outside the involved riders’areas of residence,this study compared the differences between the locations of crashes and the residences of NMV crash-involved riders in safety influencing factors and hot zone identification.A Poisson lognormal bivariate conditional autoregressive(PLN-BCAR)model was developed to account for potential correlations between crashes and involved riders.The model was compared with the univariate Poisson lognormal conditional autoregressive(UPLN-CAR)model and the bivariate Poisson lognormal conditional autoregressive(BPLNCAR)model;the PLN-BCAR model outperformed the other two models in its better interpretation of the influencing factors and its more efficient parameter estimation.Model results indicated that crashes were mainly associated with roadway and land use characteristics,while involved road users were mainly associated with socioeconomic and land use characteristics.The potential for safety improvement method was adopted to identify hot zones for countermeasure implementation.Results showed over 60%of the identified hot zones were inconsistent:they needed improvement in either engineering or education but not both.These findings can help target the type of improvement to better utilize resources for NMV safety.
