基于冲突理论的平视显示行人预警系统安全效用建模分析

doi:10.16097/j.cnki.1009-6744.2025.06.032

摘要/Abstract

摘要： 为量化车载平视显示系统在行人冲突事件中的安全效用，首先，基于驾驶模拟实验设计两种天气条件（晴/雾）下的行人冲突事件，获取34位被试使用Baseline、HDD(Head-Down Display)和HUD(Head-Up Display)这3种人机交互系统的驾驶操纵及车辆运行数据；其次，分析人车冲突过程中车辆的速度特征，并基于交通冲突理论提取驾驶人制动反应时间、最小碰撞时间和后侵占时间，刻画冲突前-中-后的时间安全裕度变化规律；最后，对3个时间维度指标分别构建Cox比例风险模型，探究系统条件、天气条件和驾驶人个体属性对安全裕度的作用机制。结果表明，与HDD组和Baseline组相比，HUD组驾驶人在冲突前及冲突中的车辆速度显著降低，制动反应时间更短，最小碰撞时间更长，冲突后车辆恢复速度显著更高，但后侵占时间与其他两组相比无显著差异。进一步分析表明，驾驶人性别及驾驶频率与后侵占时间有关，表现为男性驾驶人和驾驶频率较低的驾驶人后侵占时间较长。研究结果可为HUD预警系统的优化设计提供理论支撑，提升HUD系统在复杂风险驾驶环境中的安全效能。

关键词: 智能交通, 平视显示系统, Cox比例风险模型, 行人预警, 安全裕度, 驾驶模拟

Abstract: This paper aims to quantify the safety utility of in-vehicle head-up display systems in pedestrian conflict events. First, pedestrian conflict events under two weather conditions (sunny/foggy) were designed based on a driving simulator experiment, and driving maneuvers and vehicle operation data were acquired from 34 participants utilizing three human-computer interaction systems: Baseline, HDD (Head-Down Display), and HUD (Head-Up Display). Then, the speed characteristics of vehicles during human-vehicle conflicts were analyzed, and the driver's braking reaction time, minimum time-to-collision and post-encroachment time were extracted based on the traffic conflict theory, in order to characterize the pattern of variation of temporal safety margins before, during, and after the conflict. A Cox proportional hazard model was developed for the three time-dimensional indicators to explore the mechanism of the system conditions, weather conditions and individual driver attributes on safety margins. The results show that, compared to the HDD and Baseline groups, drivers in the HUD group exhibited significantly lower vehicle speeds before and during the conflict, shorter braking reaction times, longer minimum time-to-collision, and significantly higher post conflict recovery speeds. However, there was no significant difference in post-encroachment time compared to the other two groups. Further analysis showed that driver gender and driving frequency were related to post-encroachment time, with male drivers and drivers with lower driving frequency exhibiting longer post-encroachment time. The research results can provide theoretical support for the optimization design of the HUD warning system and enhance the safety performance of the HUD system in complex risk-driving environments.

Key words: intelligent transportation, head-up display (HUD), Cox proportional hazard model, pedestrian warning, safety margin, driving simulation

中图分类号:

U491.2+5

李雪玮, 孙齐, 刘筱萌, 康学建, 赵晓华. 基于冲突理论的平视显示行人预警系统安全效用建模分析[J]. 交通运输系统工程与信息, 2025, 25(6): 350-359.

LI Xuewei, SUN Qi, LIU Xiaomeng, KANG Xuejian, ZHAO Xiaohua. Analysis of Safety Utility of Head-up Display Pedestrian Warning System Based on Conflict Theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(6): 350-359.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2025.06.032

http://www.tseit.org.cn/CN/Y2025/V25/I6/350

参考文献

[1] DANDEKAR A,RISHAAN R,READ O, et al. Howin vehicle message location can impact driver's attention management[C]//Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces andInteractiveVehicularApplications,2023:115-120.

[2] LIU Y C, WEN M H. Comparison of head-up display (HUD)vs. head-down display (HDD): Driving performance of commercial vehicle operators in Taiwan [J]. International Journal of Human-Computer Studies, 2004,61(5):679-697.

[3] RUSSELL S M, RADLBECK J, ATWOOD J, et al. Head-up displays and distraction potential[R]. United States: Department of Transportation, National Highway Traffic SafetyAdministration,2023.

[4] GUAN L. Interface design of automobile head-up display from the perspective of human-machine interaction[C]. Luoyang, China: Proceedings of the 3rd International Conference on Art Design and Digital Technology, ADDT2024.

[5] PARK J, IMY. Visual enhancements for the driver's information search on automotive head-up display[J]. International Journal of Human-Computer Interaction, 2021,37(18):1737-1748.

[6] ZHANGY, YANGT, ZHANGX, et al. Effects of full windshield head-up display on visual attention allocation [J]. Ergonomics, 2021, 64(10): 1310-1321.

[7]LI R, CHEN Y V, ZHANG L, et al. Effects of perception of head-up display on the driving safety of experienced and inexperienced drivers[J]. Displays, 2020, 64: 101962.

[8]GERBER M A, SCHROETER R, JOHNSON D, et al. An eye gaze heatmap analysis of uncertainty head-up display designs for conditional automated driving[C]// Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, 2024: 1-16.

[9] 朱培培,邵丽青,吴硕,等.AR-HUD技术发展与产业化进程分析[J]. 汽车文摘,2024(12): 14-20. [ZHU P P, SHAO L Q, WU S, et al. Analysis of the development and industrialization process of AR-HUD technology[J]. Auto Digest, 2024(12): 14-20.]

[10] World Health Organization. Global status report on road safety 2018[M]. Geneva: World Health Organization, 2018.

[11] KIEFER R J. Quantifying head-up display (HUD) pedestrian detection benefits for older drivers[C]// Proceedings 16th International Conference on the Enhanced Safety of Vehicles. 1998: 428-437.

[12] PHAN M T, THOUVENIN I, FREMONT V. Enhancing the driver awareness of pedestrian using augmented reality cues[C]//2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), IEEE, 2016: 1298-1304.

[13] ZHANG Y, BIAN Y, ZHAO X, et al. Improving pedestrian safety with head-up display warning in a connected environment[J]. International Journal of Human-Computer Interaction, 2025, 41(6): 3724-3744.

[14] WU Y, ABDEL-ATY M, PARK J, et al. Effects of real time warning systems on driving under fog conditions using an empirically supported speed choice modeling framework[J]. Transportation Research Part C: Emerging Technologies, 2018, 86: 97-110.

[15] MUELLER A S, TRICK L M. Driving in fog: The effects of driving experience and visibility on speed compensation and hazard avoidance[J]. Accident Analysis & Prevention, 2012, 48: 472-479.

[16] HAJISEYEDJAVADI F, AGRAWAL R, FISHER D, et al. Effectiveness of visual collision warning alerts on young drivers' latent hazard anticipation[C]// Driving Assessment Conference, 2017: 151-157.

[17] 成卫.城市道路交通事故与交通冲突技术理论模型及方法研究[D]. 长春: 吉林大学, 2004. [CHENG W. Research on the theoretical models and methods of urban road traffic accidents and traffic conflicts [D]. Changchun: Jilin University, 2004.]
[18] YANG Z, SHI J, ZHANG Y, et al. Head-up display graphic warning system facilitates simulated driving performance[J]. International Journal of Human Computer Interaction, 2019, 35(9): 796-803.

[19] 戢晓峰, 戴秉佑,普永明,等.基于生存分析的山区双车道公路超车持续时间模型[J].交通运输系统工程与信息,2022, 22(6): 183-190. [JI X F, DAI B Y, PU Y M, et al. Overtaking duration model for two-lane mountain roads based on survival analysis [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 183-190.]

[20] 李岩, 南斯睿,胡文斌,等.机非标线分隔道路电动自行车越线风险模型[J].重庆交通大学学报(自然科学版), 2021, 40(2): 13-20. [LI Y, NAN S R, HU W B, et al. Risk model of electric bicycle crossing line on roads with motor-vehicle and non-motorized vehicle lane markings [J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2021, 40(2): 13-20.]

[21] 白桦, 刘秀彩,曹璐.基于Cox比例风险模型的山地城市快速路拥堵因素影响分析[J].智能城市,2022,8(4): 11-13. [BAI H, LIU X C, CAO L. Analysis of congestion factors on urban expressways in mountainous cities based on Cox proportional hazards model [J]. Smart City, 2022, 8(4): 11-13.]

[22] 李聪颖,张浩星,谭倩,等.基于Cox比例风险模型的交通违法间隔时间研究[J].中国安全科学学报,2023,33 (3): 126-133. [LI C Y, ZHANG H X, TAN Q, et al. Study on the interval time of traffic violations based on the Cox proportional hazards model[J]. China Safety Science Journal, 2023, 33(3): 126-133.]

[23] 冯天军, 孙玉姝.基于生存分析方法的学区行人闯红灯行为研究[J]. 山东交通科技,2022(1): 88-90. [FENG T J, SUN Y S. Research on pedestrian red-light running behavior in school zones based on survival analysis method[J]. Shandong Transportation Science and Technology, 2022(1): 88-90.]

[24] LARGE D R, KIM H, MERENDA C, et al. Investigating the effect of urgency and modality of pedestrian alert warnings on driver acceptance and performance[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2019, 60: 11-24.