基于数据包络分析的高速公路指路标志地名数研究

随着路网的复杂化,指路标志信息量过载导致交通事故发生的现象日益显著。为了全面、系统地确定高速公路互通区指路标志的合理地名数,为高速公路指路标志的设置提供相应的改进建议,基于数据包络分析（DEA）方法,从驾驶人角度选取了反映其对指路标志认知反应水平的代表性指标,构建了高速公路互通区指路标志地名数研究的宏观模型。使用眼动仪和脑电仪在相关场景中进行室内驾驶模拟试验,以获取被试在不同地名数指路标志场景下的眼动行为、脑电以及驾驶行为数据。利用模型进行数据分析,得到驾驶人在地名数为4,5,6,7,8,9六种场景下,对指路标志认知反应的综合效率均值分别为0.983,0.956,0.902,0.796,0.699和0.617,再针对不同的指标集,进行指标敏感性分析,获取驾驶人在6种场景下的综合效率指数。通过试验发现：随着地名数的增多,驾驶人对指路标志认知反应的综合效率均值呈现下降趋势,当信息量超过其认知阈值时,系统综合效率值会迅速下降;不同地名数指路标志场景下,导致驾驶人认知反应效率低的原因存在差异,在对指路标志版面设计时应有针对性地予以改进;不同驾驶人对指路标志认知反应效率存在差异,所对应的标志地名数合理阈值也存在轻微差异,但总体上从驾驶人认知反应的角度考虑,高速公路指路标志的地名数阈值为6个。该研究从驾驶人对指路标志认知反应的角度,使用DEA方法构建了全面、系统的指标体系对指路标志的地名数进行了探析,为中国高速公路互通区指路标志的版面设置提供了参考。

Number of Place Names of Freeway Guide Signs Based on Data Envelopment Analysis

With the complication of the road network, the phenomenon of traffic accidents caused by the overloaded information of the guide signs present serious problems. To comprehensively determine the reasonable number of place names for guide signs in freeway interchange areas and propose corresponding suggestions to improve the setting of freeway guide signs, we studied the setting of guide signs on the driver's response efficiency based on the data envelopment analysis (DEA) method, selected representative indicators reflecting the driver's cognitive response level on guide signs, and constructed a macro model for the study of the number of place names of the freeway guide signs. We used the eye tracker and electroencephalogram (EEG) while performing the driving simulation experiments in relevant scenes and obtained eye movement parameters, EEG brain wave data, and driving behavior of the subjects with different six scenes. Using the model for data analysis, the average efficiencies of the driver's cognitive response to the guide signs in six scenes (divided by the number of 4,5,6,7,8,and 9 place names) were observed to be 0. 983,0. 956,0. 902,0. 796,0. 699,and 0. 617, respectively. Then, according to the different indicator sets, we performed the indicator sensitivity analysis to obtain the comprehensive efficiency index of the drivers in the six scenarios. The results reveal that as the number of place names increases, the average efficiency of the driver's cognitive response to guide signs exhibits a downward trend. When the amount of information exceeds the drivers' cognitive threshold, the system's overall efficiency value decreases rapidly. The drivers have different level of cognitive response efficiency in different place names scenarios, leading to target efforts to improve the response efficiency by modifying the layout design on the guide signs. From the perspective of a driver's cognitive response, the results show that the threshold of place names of freeway guidance signs is suggested at 6. This study used the DEA method to construct a comprehensive index system to analyze the number of place names of the guide signs from the perspective of a driver's cognitive response to the guiding signs, and provided a practical reference for the layout of the guide signs for freeway interchange areas in China.