人机交互系统影响下城市无信号交叉口驾驶人负荷和行为特性

鞠云杰; 陈丰

doi:10.3963/j.jssn.1674-4861.2025.04.013

人机交互系统影响下城市无信号交叉口驾驶人负荷和行为特性

doi: 10.3963/j.jssn.1674-4861.2025.04.013

鞠云杰^{1, 2,},
陈丰^{1, 2, ,}

1.
同济大学交通学院上海 201804
2.
同济大学道路与交通工程教育部重点实验室上海 201804

基金项目:

国家重点研发计划项目 2023YFB2504403

详细信息

作者简介:
鞠云杰（1995—），博士研究生. 研究方向：交通安全. E-mail：yunjieju@tongji.edu.cn

通讯作者:
陈丰（1982—），博士，教授. 研究方向：交通安全、风工程等. E-mail：fengchen@tongji.edu.cn

中图分类号: U491.6+2
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出版历程
- 收稿日期: 2025-01-01

Driver Workload and Behavioral Characteristics at Urban Unsignalized Intersections Under the Influence of Human-machine Interaction Systems

JU Yunjie^{1, 2
,},
CHEN Feng^{1, 2
, ,}

1.
College of Transportation, Tongji University, Shanghai 201804, China
2.
The Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China

摘要

摘要: 人机交互系统（human-machine interaction system, HMIs）在提升驾驶体验方面发挥着至关重要的作用。然而，额外交互信息的引入是否会导致驾驶人工作负荷超载以及其对行为绩效的影响尚不明确。为此，本研究招募29名被试进行驾驶模拟器试验，测量检测-响应任务（detection response task，DRT）、美国航空航天局认知负荷指数（national aeronautics and space administration task load index，NASA-TLX）和驾驶行为参数，分析不同人机交互系统和冲突类型下的驾驶人工作负荷和行为特性，并考虑其交互效应。结果表明：①DRT结果显示：在综合视听信息影响下，驾驶人的DRT响应时间减少12.1%且命中率增加5.8%~48.5%，意味着驾驶人建立了高级别的态势感知，能够分配更多认知资源响应DRT请求。此外，交叉冲突环境中的驾驶人需要频繁监控周边交通环境以确定其他道路使用者位置和运动轨迹，致使DRT响应时间增加14.8%，命中率减少22.6%；②基于NASA-TLX测量的主观负荷结果显示，综合视听信息作用下的个人努力维度得分减少21.7%~22.8%，驾驶人认为他们可以比其他人更轻松地达到预期性能水平；驾驶人感受到的时间压力减少19.8%，驾驶节奏舒缓且从容；挫败感维度得分减少31.4%~32.9%，不安全、气馁、烦躁、紧张和恼怒等负面情绪减少；③由于应对安全关键事件的充足空间和时间裕度，具有综合视听信息的驾驶人的速度标准差、加速噪声和横向偏移标准差分别减少32.1%、26.9%和7.1%，驾驶更加平稳、舒适感更强、车道保持能力和横向控制稳定性更好。
- 交通安全 /
- 人机交互系统 /
- 驾驶人负荷 /
- 行为特性 /
- 检测-响应任务 /
- 美国航空航天局认知负荷指数
Abstract: Human-machine interaction systems (HMIs) play a vital role in enhancing the driving experience. However, whether additional interaction information overloads driver workload and affects behavioral performance remains unclear. For this purpose, the study recruits 29 participants for a driving-simulator experiment. It measures the detection response task (DRT), NASA Task Load Index (NASA-TLX), and driving behavior parameters, and analyzes driver workload and behavioral characteristics across HMI systems and conflict types, while considering their interaction effects. Results show that: ①Under integrated visual-auditory information, drivers'DRT response time decreases 12.1% and hit rate increases 5.8%—48.5%. This suggests drivers establish high situational awareness and can allocate more cognitive resources to DRT requests. Additionally, in cross-conflict environments, drivers frequently monitor surrounding traffic to determine other road users'positions and trajectories. As a result, DRT response time increases 14.8%, and hit rate decreases 22.6%. ②Based on NASA-TLX, under integrated visual-auditory information, effort scores decrease 21.7%—22.8%. Drivers consider they can reach expected performance levels more easily than others. Perceived time pressure decreases 19.8%, indicating a more relaxed and composed driving pace. Frustration scores decrease 31.4%—32.9%, and negative emotions including insecurity, discouragement, irritability, tension, and annoyance decrease. ③With sufficient space and time margins for safety-critical events, drivers with integrated visual-auditory information show a 32.1% reduction in speed standard deviation. Acceleration noise decreases 26.9%, and lateral offset standard deviation decreases 7.1%. Driving becomes smoother and more comfortable, with better lane-keeping ability and improved lateral control stability.
- traffic safety /
- human-machine interaction system /
- driver workload /
- behavioral characteristics /
- detection response task /
- NASA-TLX

HTML全文

图 1 固定基座驾驶模拟器

Figure 1. Fixed-base driving simulator

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图 2 人机交互界面中的视觉反馈信息

Figure 2. Visual feedback in human-machine interaction interfaces

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图 3 目标指向不同方向的4×4箭头矩阵

Figure 3. 4×4 arrow matrix with targets pointing in different directions

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图 4 驾驶人与测试车辆在无信号控制交叉口的交互和冲突

Figure 4. Driver interaction and conflict with test vehicles at unsignalized intersections

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图 5 驾驶模拟试验流程

Figure 5. Driving simulator experimental procedure

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图 6 统计检验标准流程（单因素/两因素重复测量方差分析）

Figure 6. Standardized procedure for statistical tests(one-way/two-way repeated measures ANOVA)

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图 7 人机交互系统和冲突类型对DRT响应时间的主效应

Figure 7. Main effects of HMIs and conflict type on DRT response time

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图 8 人机交互系统和冲突类型对DRT响应时间的主效应

Figure 8. Main effects of HMIs and conflict type on DRT response time

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图 9 不同冲突类型下的DRT命中率

Figure 9. DRT hit rates for different conflict types

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图 10 不同人机交互系统的NASA-TLX维度得分

Figure 10. NASA-TLX dimension scores for different HMIs

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图 11 不同人机交互系统的速度标准差

Figure 11. Standard deviation of speed for different HMIs

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图 12 不同人机交互系统的加速噪声

Figure 12. Acceleration noise for different HMIs

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图 13 不同人机交互系统的横向偏移标准差

Figure 13. Standard deviation of lateral offset for different HMIs

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