Review of Pedestrian Traffic Research with Virtual Reality Technology

doi:10.16097/j.cnki.1009-6744.2026.03.017

Abstract

Abstract: This paper reviews 200 studies that employ virtual reality (VR) technology in pedestrian traffic research, and systematically summarizes the existing work from the perspectives of experimental tasks, experimental scenarios, research subjects, and research themes. A comprehensive overview of the current research progress is provided, and future development directions are proposed. Results show that evacuation and street-crossing tasks take account for the highest proportion of VR-based pedestrian experiments, which reflects the advantages and applicability of VR in simulating high-risk and complex traffic environments. Different tasks emphasize different scenario components: evacuation and wayfinding tasks focus on spatial structure and signage, and street-crossing tasks emphasize roadway and vehicle characteristics, while walking tasks highlight the interpersonal influences. By enabling the flexible configuration and fine-grained control of dynamic and static environmental variables, VR provides a precise and controllable technical support for exploring the underlying mechanisms of pedestrian traffic. With the respect to research subjects, path choice and street-crossing decision-making constitute the core areas of investigation, and physiological and psychological attributes appear with comparable frequency across different tasks. Research has gradually shifted from simple behavioral observation to the analysis of multidimensional coupled mechanisms. In terms of research themes, studies which examine pedestrian interactions with the environment, vehicles, and other individuals dominate across all types of experimental tasks. As new technologies, facilities, and services emerge in the era of digital intelligence, interaction-oriented research is expected to further expand. Research on heterogeneous and special populations has become a hotspot, while hazardous behavior identification remains concentrated in street-crossing tasks. VR provides dynamic tools for observing and analyzing the individual cognition, responses, and behavior, which offers a substantial potential for further exploration of individual differences and behavioral diversity. Studies on VR validity, system performance, and intervention effectiveness are found across various tasks, and the scientific evaluation and calibration of VR systems will help unlock their full potential. In view of the current research landscape, future work may focus on improving the accuracy and applicability of VR experiments, enhancing multimodal data fusion and behavioral-mechanism modeling, advancing pedestrian street-crossing studies under automated-vehicle scenarios, and further leveraging VR to identify and mitigate hazardous pedestrian behaviors across diverse environments.

Key words: traffic engineering, decision and behavior, bibliometric statistic, pedestrian traffic, virtual reality, VR experiment

摘要： 针对应用虚拟现实（VR）技术研究行人交通的200篇文献进行综述，从实验任务、实验场景、研究对象与研究主题方面系统地归纳阐述，全面梳理相关研究现状，并对未来研究方向提出建议。研究表明：行人交通VR实验任务中，撤离与过街任务占比最高，反映VR技术在模拟高风险和复杂交通场景方面的优势和适用性。不同的实验任务侧重选择不同的场景要素，撤离与寻路任务强调空间结构和标志标识，过街任务聚焦道路与车辆特征，行走任务突出他人作用。通过对动态和静态环境变量的灵活设置与精细调控，VR为发掘行人交通内在规律与作用机制提供精准可控的技术支持。研究对象方面，路径选择与过街决策占据核心地位，生理属性与心理属性在各类任务中占比相当，研究从单纯行为观察逐渐转向多维耦合机制的揭示。研究主题方面，揭示人与环境以及车辆和他人交互关系的研究在各类实验任务中均占主导地位，随着数智时代新型设施、装备与服务的更新，交互关系的研究有望进一步拓展；异质性与特殊人群研究成为热点，危险行为识别暂集中于过街任务，VR为个体级的认知、反应和行为提供动态的观察视角与分析手段，在进一步探索个体差异性与行为多样性方面仍具备潜力；VR有效性和系统及措施性能评价的研究在各类实验任务中均有涉及，对VR系统的科学评价与校准将助力其充分发挥潜能。针对以上发展现状，未来可强化VR实验的准确性与适用性研究，加强多模态数据融合与行为机制建模，完善自动驾驶汽车应用下行人过街研究，并充分发挥VR技术在不同场景中识别及纠正行人危险行为的作用。

关键词: 交通工程, 决策与行为, 文献计量统计, 行人交通, 虚拟现实, VR实验

CLC Number:

U491

ZHANG Qi, ZHANG Siyu, LI Dewei. Review of Pedestrian Traffic Research with Virtual Reality Technology[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(3): 176-191.

张琦, 张思雨, 李得伟. 应用虚拟现实技术的行人交通研究综述[J]. 交通运输系统工程与信息, 2026, 26(3): 176-191.

Add to citation manager EndNote|Ris|BibTeX

URL: http://www.tseit.org.cn/EN/10.16097/j.cnki.1009-6744.2026.03.017

http://www.tseit.org.cn/EN/Y2026/V26/I3/176

References

[1] 张凤军,戴国忠,彭晓兰.虚拟现实的人机交互综述 [J]. 中国科学: 信息科学, 2016, 46(12): 1711-1736. [ZHANG F J, DAI G Z, PENG X L. A survey on human computer interaction in virtual reality[J]. Scientia Sinica Information, 2016, 46(12): 1711-1736.]

[2]FENG Y, DUIVES D, DAAMEN W, et al. Data collection methods for studying pedestrian behaviour: A systematic review[J]. Building and Environment, 2020, 187: 107329.

[3]DAAMEN W, HOOGENDOORNS P. Experimental research of pedestrian walking behavior[J]. Transportation Research Record, 2003, 1828(1): 20-30.

[4]DEB S, CARRUTH D W, SWEEN R, et al. Efficacy of virtual reality in pedestrian safety research[J]. Applied Ergonomics, 2017, 65: 449-460.

[5]MAN S S, HUANG C, YE Q, et al. Pedestrians' interaction with eHMI-equipped autonomous vehicles: A bibliometric analysis and systematic review[J]. Accident Analysis & Prevention, 2025, 209: 107826.

[6] TRAN T T M, ARKER C, TOMITSCH M. A review of virtual reality studies on autonomous vehicle-pedestrian interaction[J]. IEEE Transactions on Human-Machine Systems, 2021, 51(6): 641-652.

[7]LIU Q, LIU R. Virtual reality for indoor emergency evacuation studies: Design, development, and implementation review[J]. Safety Science, 2025, 181: 106678.

[8] HAGHANI M. Empirical methods in pedestrian, crowd and evacuation dynamics: Part I, Experimental methods and emerging topics[J]. Safety Science, 2020, 129: 104743.

[9] SCHNEIDER S, BENGLER K. Virtually the same? Analysing pedestrian behaviour by means of virtual reality[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2020, 68: 231-256.

[10] KITCHENHAM B, BRERETON O P, BUDGEN D, et al. Systematic literature reviews in software engineering: A systematic literature review[J]. Information and Software Technology, 2009, 51(1): 7-15.

[11] 周前祥,姜世忠,姜国华.虚拟现实技术的研究现状与进展[J]. 计算机仿真, 2003(7): 1-4, 93. [ZHOU Q X, JIANG S Z, JIANG G H. Comments on virtual reality research and its development trends[J]. Computer Simulation, 2003(7): 1-4, 93.]

[12] DENG K, XING S, WANG G, et al. A clarity-intensity model for evacuation panic by fNIRS and VR[J]. Journal of Environmental Psychology, 2024, 93: 102228.

[13] KHADEMI N, MAZLOUM S, ZABIHPOUR A, et al. Designing safer intersections: Exploring the impact of visual and auditory warnings on pedestrian behavior in a virtual simulated environment[J]. Safety Science, 2024, 178: 106604.

[14] FENG Y, DUIVES D C, HOOGENDOORN S P. Development and evaluation of a VR research tool to study wayfinding behaviour in a multi-story building[J]. Safety Science, 2022, 147: 105573.

[15] DAI Z, LI D, FENG Y, et al. A study of pedestrian wayfinding behavior based on desktop VR considering both spatial knowledge and visual information[J]. Transportation Research Part C: Emerging Technologies, 2024, 163: 104651.

[16] BUHLER M A, LAMONTAGNE A. Coordinating clearance and postural reorientation when avoiding physical and virtual pedestrians[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022, 30: 1612-1620.

[17] DE SCHOT L, NILSSON D, LOVERGLIO R, et al. Exploring single-line walking in immersive virtual reality [J]. Fire Safety Journal, 2023, 140: 103882.

[18] KOILIAS A, NELSON M G, ANAGNOSTOPOULOS C, et al. Immersive walking in a virtual crowd: The effects of the density, speed, and direction of a virtual crowd on human movement behavior[J]. Computer Animation and Virtual Worlds, 2020, 31(6): e1928.

[19] DAVIS C, SOLE C, KHAN H, et al. Investigating movement through smoke in virtual reality[J]. Fire Safety Journal, 2023, 140: 103890.

[20] HU X, XU L. How guidance signage design influences passengers' wayfinding performance in metro stations: Case study of a virtual reality experiment[J]. Transportation Research Record, 2023, 2677(1): 1118 1129.

[21] XIA X, CHEN J, ZHANG J, et al. How the strength of social relationship affects pedestrian evacuation behavior: A multi-participant fire evacuation experiment in a virtual metro station[J]. Transportation Research Part C: Emerging Technologies, 2024, 167: 104805.

[22] DEB S, CARRUTH D W, HUDSON C R. How communicating features can help pedestrian safety in the presence of self-driving vehicles: Virtual reality experiment[J]. IEEE Transactions on Human-Machine Systems, 2020, 50(2): 176-186.

[23] ILIC M, LINDNER J, VOLLMER M et al. Virtual reality study on pedestrians' perceived trust in interactions with automated vehicles[J]. Transportation Research Record, 2025: 03611981241281734.

[24] SHIPMAN A, MAJUMDAR A, FENG Z, et al. A quantitative comparison of virtual and physical experimental paradigms for the investigation of pedestrian responses in hostile emergencies[J]. Scientific Reports, 2024, 14(1): 6892.

[25] LOVREGLIO R, DILLIES E, KULIGOWSKI E, et al. Exit choice in built environment evacuation combining immersive virtual reality and discrete choice modelling [J]. Automation in Construction, 2022, 141: 104452.

[26] ZHANG X, CHEN L, JIANG J, et al. Risk analysis of people evacuation and its path optimization during tunnel fires using virtual reality experiments[J]. Tunnelling and Underground Space Technology, 2023, 137: 105133.

[27] RIOS A, PELECHANO N. Follower behavior under stress in immersive VR[J]. Virtual Reality, 2020, 24(4): 683 694.

[28] FUJIMI T, FUJIMURA K. Testing public interventions for flash flood evacuation through environmental and social cues: The merit of virtual reality experiments[J]. International Journal of Disaster Risk Reduction, 2020, 50: 101690.

[29] XIA X, LI N, GONZALEZ V A. Exploring the influence of emergency broadcasts on human evacuation behavior during building emergencies using virtual reality technology[J]. Journal of Computing in Civil Engineering, 2021, 35(2): 04020065.

[30] LUU D T, EOM H, CHO G H, et al. Cautious behaviors of pedestrians while crossing narrow streets: Exploration of behaviors using virtual reality experiments[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2022, 91: 164-178.

[31] FENG Y, DUIVES D C, HOOGENDOORN S P. Using virtual reality to study pedestrian exit choice behaviour during evacuations[J]. Safety Science, 2021, 137: 105158.

[32] TONG Y, BODE N W F. The value pedestrians attribute to environmental information diminishes in route choice sequences[J]. Transportation Research Part C: Emerging Technologies, 2021, 124: 102909.

[33] ŞAHIN H, HEMESATH S, BOLL S. Deviant behavior of pedestrians: A risk gamble or just against automated vehicles? How about social control? [J]. Frontiers in Robotics and AI, 2022, 9: 885319.

[34] KWON H J, WON J, CHO H G. Investigating the dynamics of collective behavior among pedestrians crossing roads: A multi-user virtual reality approach[J]. Accident Analysis & Prevention, 2024, 199: 107477.

[35] ZHAO Y, LIU Z, XIAO J, et al. Research on emotion modeling of intelligent agents in earthquake evacuation simulation[J]. Cognitive Systems Research, 2024, 87: 101242.

[36] KALATIAN A, FAROOQ B. Decoding pedestrian and automated vehicle interactions using immersive virtual reality and interpretable deep learning[J]. Transportation Research Part C: Emerging Technologies, 2021, 124: 102962.

[37] WANG K, XU L, JIANG H. Analysis of the effect of human-machine co-driving vehicle on pedestrian crossing speed at uncontrolled mid-block road sections: A VR-based case study[J]. International Journal of Environmental Research and Public Health, 2022, 19 (12): 7208.

[38] MADIGAN R, LEE Y M, LYU W, et al. Pedestrian interactions with automated vehicles: Does the presence of a zebra crossing affect how eHMIs and movement patterns are interpreted?[J]. Transportation Research Part F: Psychology and Behaviour, 2023, 98: 170-185.

[39] SONG Y, JIANG Q, CHEN W, et al. Pedestrians' road crossing behavior towards eHMI-equipped autonomous vehicles driving in segregated and mixed traffic conditions[J]. Accident Analysis and Prevention, 2023, 188: 107115.

[40] ZOU F, OGLE J, JIN W, et al. Pedestrian behavior interacting with autonomous vehicles during unmarked midblock multilane crossings: Role of infrastructure design, AV operations and signaling[J]. Transportation Research Part F: Psychology and Behaviour, 2024, 100: 84-100.

[41] WANG H, WANG A, SU F, et al. The effect of age and sensation seeking on pedestrian crossing safety in a virtual reality street[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2022, 88: 99-110.

[42] MORRONGIELLO B A, CORBETT M, STEWART J. Understanding sex differences in children's injury risk as pedestrians[J]. Journal of Pediatric Psychology, 2020, 45 (10): 1144-1152.

[43] CHEN N, ZHAO M, GAO K, et al. Experimental study on the evaluation and influencing factors on individual's emergency escape capability in subway fire[J]. International Journal of Environmental Research and Public Health, 2021, 18(19): 10203.

[44] LIN J, CAO L, LI N. How the completeness of spatial knowledge influences the evacuation behavior of passengers in metro stations: A VR-based experimental study[J]. Automation in Construction, 2020, 113: 103136.

[45] YE Y, ZHENG P, LIANG H, et al. Safety or efficiency? Estimating crossing motivations of intoxicated pedestrians by leveraging the inverse reinforcement learning[J]. Travel Behaviour and Society, 2024, 35: 100760.

[46] TONG Y, BODE N W F. An investigation of how context affects the response of pedestrians to the movement of others[J]. Safety Science, 2023, 157: 105919.

[47] LIN J, ZHU R, LI N, et al. Do people follow the crowd in building emergency evacuation? A cross cultural immersive virtual reality-based study[J]. Advanced Engineering Informatics, 2020, 43: 101040.

[48] WANG H, GAO Z, SHEN T, et al. Roles of individual differences and traffic environment factors on children's street-crossing behaviour in a VR environment[J]. Injury Prevention, 2020, 26(5): 417-423.

[49] 卫大可,段性快.基于VR实验的老年人照料设施交通空间寻路绩效研究[J]. 建筑学报, 2023(S2): 88-93. [WEI D K, DUAN X K. Wayfinding performance review of traffic space in nursing home based on virtual reality experiments[J]. Architectural Journal, 2023(S2): 88-93.]

[50] HAN S, YOON P, REN X, et al. The effects of walk-in place and overground walking on the acquisition of spatial information by people with visual impairment in virtual reality wayfinding[J]. International Journal of Human-Computer Interaction, 2025, 41(4): 2541-2559.

[51] SCHWEBEL D C, DAVIS A L, O'NEAL E E. Child pedestrian injury: A review of behavioral risks and preventive strategies[J]. American Journal of Lifestyle Medicine, 2012, 6(4): 292-302.

[52] MORRONGIELLO B A, CORBETT M, MILANOVIC M, et al. Innovations in using virtual reality to study how children cross streets in traffic: Evidence for evasive action skills[J]. Injury Prevention, 2015, 21(4): 266-270.

[53] TIAN K, MARKKULA G, WEI C, et al. Impacts of visual and cognitive distractions and time pressure on pedestrian crossing behaviour: A simulator study[J]. Accident Analysis & Prevention, 2022, 174: 106770.

[54] YI X, ZHAO R, LIN Y. The impact of nighttime car body lighting on pedestrians' distraction: A virtual reality simulation based on bottom-up attention mechanism[J]. Safety Science, 2024, 180: 106633.

[55] LUO H, YANG T, KWON S, et al. Using virtual reality to identify and modify risky pedestrian behaviors amongst Chinese children[J]. Traffic Injury Prevention, 2020, 21 (1): 108-113.

[56] WICZOREK R, PROTZAK J. Evaluation of an assistance system supporting older pedestrians' road crossing in virtual reality and in a real-world field test[J]. Frontiers in Psychology, 2022, 13: 966096.

[57] SHI M, ZHANG Z, ZHANG W, et al. The study of self organised behaviours and movement pattern of pedestrians during fire evacuations: Virtual experiments and survey[J]. Safety Science, 2024, 170: 106373.

[58] vAN B A, DUIVES D C, FENG Y, et al. Comparison of pedestrian wayfinding behavior between a real and a virtual multi-story building: A validation study[J]. Transportation Research Part C: Emerging Technologies, 2024, 163: 104650.

[59] FELDSTEIN T I, DYSZAK N G. Road crossing decisions in real and virtual environments: A comparative study on simulator validity[J]. Accident Analysis & Prevention, 2020, 137: 105356.

[60] MARTIN S S, IZQUIERDO R, GARCIA D, et al. Behavioural gap assessment of human-vehicle interaction in real and virtual reality-based scenarios in autonomous driving[J]. International Journal of Human-Computer Interaction, 2025, 41(11): 6879-6892.

[61] LI J, ZHANG J, SONG X, et al. The validation of pedestrian trajectories during turning and obstacle avoidance in virtual environments[J]. Physica A: Statistical Mechanics and its Applications, 2024, 633: 129340.

[62] FENG Y, DUIVES D C, HOOGENDOORN S P. Wayfinding behaviour in a multi-level building: A comparative study of HMD VR and Desktop VR[J]. Advanced Engineering Informatics, 2022, 51: 101475.

[63] SCHNEIDER S, MARUHN P, DANG N T, et al. Pedestrian crossing decisions in virtual environments: Behavioral validity in CAVEs and head-mounted displays [J]. Human Factors, 2022, 64(7): 1210-1226.

[64] PALA P, CAVALLO V, DANG N T, et al. Is the street crossing behavior with a head-mounted display different from that behavior in a CAVE? A study among young adults and children[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2021, 82: 15-31.

[65] FELDSTEIN I, DIETRICH A, MILINKOVIC S, et al. A pedestrian simulator for urban crossing scenarios[J]. IFAC-Papers OnLine, 2016, 49(19): 239-244.

[66] CUMMINGS J J, BAILENSON J N. How immersive is enough? A meta-analysis of the effect of immersive technology on user presence[J]. Media Psychology, 2016, 19(2): 272-309.

[67] FU M, LIU R, ZHANG Y. Why do people make risky decisions during a fire evacuation? Study on the effect of smoke level, individual risk preference, and neighbor behavior[J]. Safety Science, 2021, 140: 105245.

[68] ANGULO V A, ROBARTES E, GUO X, et al. Evaluating current and future pedestrian mid-block crossing safety treatments using virtual reality simulation[J]. Accident Analysis and Prevention, 2024, 206: 107715.