Effect of fog weather warning system under cooperative vehicle infrastructure on vehicle operating eco-characteristics
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摘要: 为探究车路协同技术对车辆运行生态特性的影响，基于驾驶模拟试验平台构建车路协同条件下的雾天预警系统，测试了驾驶人在浓雾条件下驾驶车辆的能耗排放特征；设计了空白对照组、可变情报板(DMS)预警组、人机交互界面(HMI)预警组以及DMS+HMI预警组4种试验场景，招募43名驾驶人开展驾驶模拟试验，通过对比不同预警方式作用下车辆总体和道路关键区段的能耗排放差异，明确不同预警系统对车辆运行生态特性的影响效用。分析结果表明：相对于空白组，3种车路协同雾天预警系统均能显著降低车辆整体能耗与排放，但是不同预警方式的作用效果并无明显差别；道路场景分为了预警前、预警区、渐变区和雾区4个关键区段，3种预警系统在预警区及渐变区均可有效降低车辆能耗及排放；HMI从发出预警信息后开始生效，DMS可在车辆进入预警区前产生效果，DMS+HMI在预警区的效果最为显著，但进入雾区后不能有效降低车辆能耗与排放。可见，虽然车路协同雾天预警系统整体可以提升车辆运行生态特性，但是单一增加预警强度或改变预警方式并不能有效保证整个雾天影响区域不同区段均具有节能减排效用，合理设置车路协同预警系统应综合考虑不同预警方式、预警信息触发点位及时机、驾驶人特性等因素的匹配关系。Abstract: To explore the effectiveness of cooperative vehicle infrastructure (CVI) technology on vehicle operating eco-characteristics, a fog weather warning system under CVI condition was built based on the driving simulation experiment platform. The fuel consumption and emission features of driving vehicles under the heavy fog weather environment were tested. Four testing scenes, including blank control group, group of warning by dynamic message sign (DMS), group of warning by human machine interface (HMI), and group of warning by DMS+HMI, were designed. A driving simulator experiment was carried out by recruiting 43 drivers. The effects of different warning methods on vehicle operating eco-characteristics were obtained by comparing the differences in vehicle fuel consumption and emissions as a whole and on key sections of the road. Analysis results show that compared with the blank group, the three types of fog weather warning systems under CVI can significantly reduce the overall fuel consumption and emissions of vehicles. However, the effects of the different warning methods are not significantly different. The road scene is divided into pre-warning, warning, gradient and fog zones, and the three warning systems can effectively reduce vehicle fuel consumption and emissions in the warning and gradient zones. The HMI takes effect as the warning message is issued, and the DMS is effective before the vehicle enters the warning zone. The DMS+HMI has the most significant effect in the warning zone, but it can not effectively reduce the vehicle fuel consumption and emissions after the vehicle enters the fog zone. Therefore, although fog weather warning system under CVI can improve the overall eco-characteristics of vehicle operation, it can not effectively guarantee energy savings and emission reduction effect of different sections in the fog-affected area by only increasing the warning intensity or changing the warning mode. The matching relationship among different warning modes, warning information trigger points and timing, driver characteristics and other factors should be comprehensively considered in a reasonable setting of the fog weather warning system under CVI. 4 tabs, 8 figs, 30 refs.
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图 1 车路协同雾天预警系统
Figure 1. Fog weather warning system under cooperative vehicle infrastructure
图 5 不同预警方式下车辆油耗均值与标准差
Figure 5. Mean values and standard deviations of vehicle fuel consumption corresponding to different warning types
图 6 不同预警方式下车辆油耗变化过程
Figure 6. Changing process of fuel consumption corresponding to different warning types
图 7 不同预警方式下车辆排放均值与标准差
Figure 7. Mean values and standard deviations of vehicle emissions corresponding to different warning types
图 8 不同预警方式下车辆排放变化过程
Figure 8. Changing processes of vehicle emissions corresponding to different warning types
表 1 被试基本信息
Table 1. Basic information of participants
性别 统计值 年龄 驾龄/年 年平均驾驶里程/km 男性 均值 37.5 16.0 18 524.0 标准差 13.1 10.2 3 548.2 女性 均值 25.0 13.0 9 584.0 标准差 13.0 9.3 5 514.2 
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表 2 不同预警方式在各关键路段影响车辆油耗的差异性对比
Table 2. Difference comparison of vehicle fuel consumptions in key road segments corresponding to different warning types
表 3 不同预警方式下车辆排放均值方差分析结果
Table 3. Analysis results of variance for mean vehicle emissions corresponding to different warning types
排放物 CO2 CO HC NOx F(3, 936) 11.541 15.698 11.357 13.658 P < 0.001
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表 4 不同预警方式在各关键路段影响车辆排放的差异性对比
Table 4. Difference comparison of vehicle emissions in key road segments corresponding to different warning types
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