Safety Science最新文献

A system-theoretic approach to assess territory readiness for safe advanced air mobility operations 一种评估安全先进空中机动作战的领土准备状态的系统理论方法

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-16 DOI: 10.1016/j.ssci.2026.107146

Manuel Lombardi , Natalia Guskova , Elena Stefana , Giulio Di Gravio , Riccardo Patriarca

The evolution of disruptive technologies, such as Vertical Take-Off and Landing (VTOL) vehicles and Advanced Air Mobility (AAM), is reshaping civil aviation operations. As AAM and VTOL bring innovations, the European Union (EU) and the European Union Aviation Safety Agency (EASA) must adapt to these developments to ensure continued aviation safety. Integrating VTOL vehicles into air and ground infrastructure (e.g., airports and vertiports) presents new safety and regulations challenges, as these new systems must safely fit into an already complex environment. The implementation of VTOL and AAM into European civil aviation would benefit from the adoption of holistic systemic approaches to managing both primary and emergent risks, which could be reflected in updated regulations and guidance manuals for relevant approvals to operate these disruptive aviation technologies. To this end, this study proposes a methodology leveraging System-Theoretic Process Analysis (STPA) as a baseline to assess territories readiness for VTOL operations through an application of the Air Taxi Readiness Index (ATRI). This methodology helps derive further regulatory specifications and guidelines that must be complied with to ensure safe operations. For demonstration purposes, the methodology is applied to two anonymized European sites to evaluate their preparedness for VTOL operations. The results indicate the readiest site for accommodating safe vertiport operations, highlights specific weaknesses that can be addressed by implementing appropriately defined safety constraints and requirements. The methodology is designed to support both policymakers and operators in decision-making processes regarding design, localization, and operation of vertiports, ensuring safe and efficient integration of VTOL solutions.

颠覆性技术的发展，如垂直起降（VTOL）飞行器和先进空中机动（AAM），正在重塑民用航空运营。由于空对空和垂直起降带来了创新，欧盟（EU）和欧洲航空安全局（EASA）必须适应这些发展，以确保持续的航空安全。将垂直起降车辆集成到空中和地面基础设施（如机场和垂直机场）中，带来了新的安全和法规挑战，因为这些新系统必须安全地适应已经复杂的环境。VTOL和AAM在欧洲民用航空中的实施将受益于采用整体系统方法来管理主要和紧急风险，这可以反映在更新的法规和指导手册中，以便相关批准操作这些颠覆性航空技术。为此，本研究提出了一种利用系统理论过程分析（STPA）作为基线的方法，通过应用空中滑行准备指数（ATRI）来评估垂直起降操作的区域准备情况。该方法有助于推导出必须遵守的进一步法规规范和指导方针，以确保安全操作。为了演示目的，将该方法应用于两个匿名的欧洲站点，以评估其垂直起降操作的准备情况。研究结果表明，最适合安全垂直起降作业的地点，突出了可以通过实施适当定义的安全约束和要求来解决的具体弱点。该方法旨在支持决策者和运营商在垂直起降设计、定位和操作方面的决策过程，确保安全高效地集成垂直起降解决方案。

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引用次数: 0

Improving system design to support resilience through self-organisation: The case of a network of labour inspectors for accident investigations 通过自组织改进系统设计以支持弹性：事故调查劳动检查员网络的案例

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-14 DOI: 10.1016/j.ssci.2026.107147

Bruna Carolina de Quadros , Tarcisio Abreu Saurin , Stela Xavier Terra

Although resilient performance through self-organisation is intrinsic to complex sociotechnical systems, it might benefit from system design. To explore how to design such supportive system, this article presents a case study of an advice-seeking network among government labour inspectors responsible for accident investigations in Brazil. This network emerged from the self-organisation of inspectors and is not part of the formal design of the labour inspectorate system. The method involved a social network analysis (SNA) survey that ranked inspectors based on an indicator that reflected their contribution to system resilience. A follow-up survey gathered improvement suggestions. These improvements were justified based on the SNA results and resilience concepts. Findings revealed a low-density network reliant on a few key actors who were experts in generalist management regulations. Nevertheless, even peripheral actors were deemed reliable sources for industry-specific regulatory advice. Improvements aimed to identify and facilitate access to experts, improve access to prior investigation findings, and expand inspectors’ knowledge. These measures reduce dependence on key individuals, shorten the path to reach them, and enrich the quality of interactions. An emerging framework that integrates SNA, a resilience-based ranking of inspectors, and a feedback-based redesign process is presented. This framework is a methodological contribution intended to support resilience through self-organisation in collaborative networks.

虽然通过自组织的弹性性能是复杂社会技术系统的内在特征，但它可能受益于系统设计。为了探讨如何设计这样的支持系统，本文以巴西负责事故调查的政府劳动检查员之间的咨询网络为例进行了研究。这个网络是从检查员的自我组织中产生的，并不是劳动检查员系统正式设计的一部分。该方法涉及社会网络分析（SNA）调查，该调查根据反映检查员对系统弹性的贡献的指标对检查员进行排名。一项后续调查收集了改进建议。基于SNA结果和弹性概念，这些改进是合理的。调查结果显示，低密度的网络依赖于几个关键行为者，他们是通才管理条例的专家。然而，即使是外围参与者也被认为是行业特定监管建议的可靠来源。改进的目的是确定和促进专家的接触，改善获得先前调查结果的机会，并扩大检查员的知识。这些措施减少了对关键个人的依赖，缩短了与他们接触的路径，并丰富了互动的质量。提出了一个整合SNA、基于弹性的检查员排名和基于反馈的重新设计过程的新框架。该框架是一种方法上的贡献，旨在通过协作网络中的自组织来支持弹性。

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引用次数: 0

Generative artificial intelligence and urban transport resilience: Rethinking sustainable mobility 生成式人工智能与城市交通弹性：重新思考可持续交通

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-16 DOI: 10.1016/j.ssci.2026.107148

Jinran Wu , Xin Tian , Qingyang Liu , Tong Li , Chanjuan Liu , Jing Xu , Huida Zhao

Urban transport systems face compounding shocks, cascading failures, and rapid context shifts that challenge conventional artificial intelligence (AI) tools designed for structured inputs and stable data regimes. Generative artificial intelligence (GAI) expands disruption management by enabling interaction with heterogeneous information, evidence-grounded synthesis, scenario generation under deep uncertainty, and decision support. This review maps the emerging field and clarifies how GAI can strengthen urban transport resilience while introducing new safety-critical risks. We first conduct a dual-corpus bibliometric analysis of Web of Science Core Collection (2016–2025), covering 1670 AI and resilience publications and a 114-paper GAI subset. We then develop a phase-linked framework that connects four GAI roles — information extraction, knowledge integration, scenario generation, and decision support — to the resilience phases of absorption, adaptation, recovery, and transformation. Synthesising empirical studies across transport operations, planning, and Earth observation (EO) and remote-sensing vision-language model (VLM)–large language model (LLM) pipelines, we find that current evidence is strongest at the capability level, whereas phase-specific transport impacts are less routinely quantified under real operational constraints. Finally, we translate these gaps into an agenda for evaluation and governance, emphasising reliability and uncertainty communication, cybersecurity, data governance and interoperability, and equity-oriented public value.

城市交通系统面临着复杂的冲击、级联故障和快速的环境变化，这些挑战了传统的人工智能（AI）工具，这些工具专为结构化输入和稳定的数据制度而设计。生成式人工智能（GAI）通过支持与异构信息的交互、基于证据的合成、深度不确定性下的场景生成和决策支持来扩展中断管理。这篇综述描绘了新兴领域，并阐明了GAI如何在引入新的安全关键风险的同时加强城市交通弹性。我们首先对Web of Science核心馆藏（2016-2025）进行了双语料库文献计量分析，涵盖了1670篇AI和弹性出版物以及114篇GAI论文子集。然后，我们开发了一个相关联的框架，将四个GAI角色——信息提取、知识集成、场景生成和决策支持——与吸收、适应、恢复和转换的弹性阶段联系起来。综合运输运营、规划、地球观测（EO）和遥感视觉语言模型(VLM) -大型语言模型（LLM）管道的经验研究，我们发现目前的证据在能力层面上是最强的，而在实际运营约束下，特定阶段的运输影响较少被量化。最后，我们将这些差距转化为评估和治理议程，强调可靠性和不确定性通信、网络安全、数据治理和互操作性，以及以公平为导向的公共价值。

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引用次数: 0

Personalized driving stress assessment for enhanced safety: An explainable multimodal framework 提高安全性的个性化驾驶压力评估：一个可解释的多模式框架

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-03-02 DOI: 10.1016/j.ssci.2026.107164

Liu Yang , Wenhao Liu , Jiaqiang Wen , Shuo Zhao , Yunzhou Song

Driving stress has been recognized as an indirect factor increasing the risk of traffic accidents. However, current research predominantly focuses on detection accuracy, often overlooking individual differences in stress response and the underlying mechanisms through which stress influences traffic safety. To address this gap, this study conducted a driving stress simulation experiment involving 44 participants across 10 scenarios, collecting electrocardiogram (ECG), driving behavior, and demographic data. The dataset was first partitioned by gender and occupation to account for individual variability. A Stacking ensemble model was constructed to classify low, medium, and high levels of driving stress. The optimal algorithm was subsequently selected for feature combination experiments, comparing the performance of unimodal and multimodal models while assessing individual differences. Additionally, we further combine SHAP with decision tree-based mining to uncover heterogeneous stress-feature relationships and to derive fuzzy rules associated with stress levels. Results demonstrate that integrating ECG, behavioral, and age features improved the average recognition accuracy by 23.12% compared to using ECG features alone. Following personalisation partitioning at the data layer, stable performance differences emerged across gender and occupational subsets. SHAP analysis further revealed distinct associations between driving stress and age, speed, rotational speed, as well as time-domain and frequency-domain ECG features, depending on drivers’ gender and occupation. The proposed framework contributes to the accurate identification of driving stress and provides valuable insights into stress response patterns across different population groups, with important implications for traffic safety.

驾驶压力已被认为是增加交通事故风险的一个间接因素。然而，目前的研究主要集中在检测精度上，往往忽视了应激反应的个体差异和应激影响交通安全的潜在机制。为了解决这一差距，本研究进行了一项驾驶压力模拟实验，涉及44名参与者，涉及10种场景，收集心电图（ECG）、驾驶行为和人口统计数据。数据集首先按性别和职业划分，以解释个体差异。构建了低、中、高驱动应力水平的叠加系综模型。随后选择最优算法进行特征组合实验，比较单峰和多峰模型的性能，同时评估个体差异。此外，我们进一步将SHAP与基于决策树的挖掘相结合，以揭示异质应力特征关系，并获得与应力水平相关的模糊规则。结果表明，与单独使用心电特征相比，将心电特征、行为特征和年龄特征相结合，平均识别准确率提高了23.12%。在数据层进行个性化划分之后，性别和职业子集之间出现了稳定的性能差异。SHAP分析进一步揭示了驾驶压力与年龄、速度、转速以及时域和频域ECG特征之间的显著相关性，这取决于驾驶员的性别和职业。该框架有助于准确识别驾驶压力，并为不同人群的压力反应模式提供有价值的见解，对交通安全具有重要意义。

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引用次数: 0

Assessing safety culture in the energy industry: empirical validation of the SCEQ-E 评估能源行业的安全文化：SCEQ-E的实证验证

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-23 DOI: 10.1016/j.ssci.2026.107160

Kate Wray , Mario Martínez-Córcoles

This paper presents the adaptation and empirical validation of a tool to assess safety culture enactment in the energy sector. The Safety Culture Enactment Questionnaire-Energy (SCEQ-E) is an adapted version of the SCEQ (De Castro et al., 2017), originally developed for the nuclear industry and validated in Spanish. The SCEQ-E extends this instrument to the broader energy industry and was administered to employees working in different energy organizations (N = 146). The original questionnaire was translated into English, adapted to the energy sector, and reviewed by industry experts. Exploratory factor analysis supported a three-factor structure and two items were removed due to cross-loadings. Confirmatory factor analysis provided support for the proposed three-factor model, showing acceptable model fit and strong internal consistency for the total scale and subscales. The SCEQ-E also demonstrated good convergent validity and evidence of discriminant validity in relation to safety climate. Overall, the results indicate that the SCEQ-E provides initial evidence of reliability and construct validity and represents a promising instrument for assessing safety culture enactment in the energy industry, although further validation using larger and more diverse samples is warranted.

本文提出了一种评估能源部门安全文化制定的工具的适应性和经验验证。安全文化制定问卷-能源（SCEQ- e）是SCEQ的改编版本（De Castro等人，2017），最初是为核工业开发的，并在西班牙进行了验证。SCEQ-E将此工具扩展到更广泛的能源行业，并对在不同能源组织工作的员工进行了管理（N = 146）。最初的调查问卷被翻译成英文，根据能源部门的情况进行了调整，并由行业专家进行了审查。探索性因子分析支持三因素结构，由于交叉加载，删除了两个项目。验证性因子分析为所提出的三因子模型提供了支持，模型拟合良好，总量表和子量表具有较强的内部一致性。SCEQ-E在安全气候方面也表现出良好的收敛效度和判别效度。总体而言，结果表明，SCEQ-E提供了可靠性和结构有效性的初步证据，代表了评估能源行业安全文化制定的有前途的工具，尽管需要使用更大更多样化的样本进行进一步验证。

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引用次数: 0

Risk assessment of hydrogen systems: a review and comparison of frameworks and guidelines from Norwegian regulators 氢系统的风险评估：挪威监管机构框架和指导方针的审查和比较

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-19 DOI: 10.1016/j.ssci.2026.107163

Ingrid Glette-Iversen, Dikshya Bhandari, Jon Tømmerås Selvik

The transition towards hydrogen as a sustainable energy carrier has increased the focus on ensuring its safe implementation across various applications. A key instrument to obtain a satisfactory level of safety is adherence to regulatory frameworks and guidelines. However, the hydrogen industry faces a complex landscape of various frameworks and guidelines from different regulatory bodies. This complexity could result in inconsistent practices for hydrogen safety across sectors, such as maritime, transportation systems and industry. In Norway, this issue is exemplified by the differing frameworks and guidelines set by the Norwegian Ocean Industry Authority (Havtil), the Norwegian Maritime Authority (NMA) and the Norwegian Directorate for Civil Protection (DSB). In this paper, we present a qualitative comparative analysis of existing risk analysis frameworks and guidelines referred to by the aforementioned Norwegian regulatory bodies. The main purpose is to examine the key principles, methodologies and approaches, highlighting potential differences and conflicts in regulatory expectations. The findings reveal significant differences when it comes to how the frameworks define fundamental concepts, integrate human and organizational factors, address uncertainty and knowledge aspects and establish principles for risk evaluation and acceptance. These variations have implications for the coherence and suitability of risk assessment practices for hydrogen systems and activities. The paper concludes with recommendations to enhance the coherence and consistency of safety practices within the hydrogen sector, with the aim of facilitating a safer and more efficient adoption of hydrogen technologies across industries.

向氢作为可持续能源载体的过渡增加了对确保其在各种应用中的安全实施的关注。获得令人满意的安全水平的一个关键手段是遵守监管框架和准则。然而，氢工业面临着来自不同监管机构的各种框架和指导方针的复杂局面。这种复杂性可能导致海事、运输系统和工业等部门的氢安全实践不一致。在挪威，挪威海洋工业管理局（Havtil）、挪威海事管理局（NMA）和挪威民防局（DSB）制定的不同框架和指导方针体现了这一问题。在本文中，我们对上述挪威监管机构提到的现有风险分析框架和指导方针进行了定性比较分析。主要目的是检查关键原则、方法和方法，强调监管期望中的潜在差异和冲突。当涉及到框架如何定义基本概念、整合人力和组织因素、解决不确定性和知识方面以及建立风险评估和接受原则时，研究结果揭示了显著的差异。这些变化对氢系统和氢活动风险评估实践的一致性和适宜性有影响。该文件最后提出了加强氢行业安全实践的一致性和一致性的建议，目的是促进各行业更安全、更有效地采用氢技术。

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引用次数: 0

Crossing Confidently: The role of Walking speed and visual exploration in older Adults’ Street-Crossing decisions 自信地过马路：行走速度和视觉探索在老年人过马路决策中的作用

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-27 DOI: 10.1016/j.ssci.2026.107149

A. Anic , T.B. McGuckian , A.J. Carrigan , P. Wilson , D.A Greene , J. Duckworth , L.P Thong , R. Eldridge , M. Psarakis , A.C. McKinnon , J.M. Bennett

Older adults (> 65 years old) are vulnerable road users who are overrepresented in collisions with vehicles. Apart from walking speed, visual function and visual exploration factors may explain the street-crossing behaviours contributing to the increased risk. Although previous research compared street-crossing behaviour profiles between younger and older adults, no studies investigated the relative role of visual function and visual exploration of older adults in detecting hazards and identifying safe gaps. 101 older adult pedestrians (Mage = 68.83, SDage = 5.25; 60–83 years old) completed a suite of visual function and physical tasks. Hazard perception and gap acceptance tasks were administered via an established pedestrian street crossing virtual reality (VR) paradigm. Head and eye movements were measured using VR. We showed that walking speed did not predict hazard perception and gap acceptance suggesting walking speed was not factored when crossing the street, which may increase their risk. Contrast sensitivity significantly predicted hazard perception response time; whereas, visual acuity, head turn excursions, and the number of fixations predicted the number of correct responses within the hazard perception time window. For gap acceptance, the results showed that head turn frequency significantly predicted response time and the number of correct responses in the gap acceptance window. The findings show that contrast sensitivity is associated with improved hazard perception, whereas head movements is associated with safe crossing decisions in older adults. Street crossing is complex with specific visual exploration and visual function factors contributing uniquely to gap acceptance and hazard perception in older adult pedestrians.

老年人（65岁）是易受伤害的道路使用者，在车辆碰撞中所占比例过高。除了行走速度外，视觉功能和视觉探索因素也可能解释过马路行为导致风险增加的原因。虽然以前的研究比较了年轻人和老年人过马路的行为特征，但没有研究调查老年人的视觉功能和视觉探索在发现危险和确定安全间隙方面的相对作用。101名老年行人（Mage = 68.83, SDage = 5.25, 60-83岁）完成了一套视觉功能和身体任务。危险感知和差距接受任务通过建立的行人过街虚拟现实（VR）范式进行。头和眼的运动是用VR来测量的。我们发现步行速度不能预测危险感知和间隙接受度，这表明步行速度在过马路时没有被考虑在内，这可能会增加他们的风险。对比敏感度显著预测危害感知反应时间；而视敏度、头部转动偏移量和注视次数预测了危险感知时间窗内正确反应的数量。对于间隙接受，结果表明，转头频率显著预测响应时间和间隙接受窗口内的正确响应数。研究结果表明，对比敏感度与改善的危险感知有关，而头部运动与老年人安全过马路的决定有关。街道过马路是复杂的，具有特定的视觉探索和视觉功能因素，对老年行人的间隙接受和危险感知有独特的影响。

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引用次数: 0

A multi-stage modeling framework for pedestrian exit choice: Decision-node identification and cross-scenario validation 行人出口选择的多阶段建模框架：决策节点识别和跨场景验证

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-17 DOI: 10.1016/j.ssci.2026.107151

Weiqiao Ruan , Jia Liu , Hongqin Tang , Jianping Zhu , Chang Liu

Accurately understanding and predicting pedestrian exit choice during evacuations is a critical scientific issue for enhancing public safety management. Addressing the limitations of existing studies in terms of data realism, incomplete process modeling, and cross-scenario applicability, this paper proposes a multi-stage modeling framework for pedestrian exit choice. Grounded in behavioral science theories, a stage division procedure and identification criteria based on decision nodes are developed. Furthermore, a video-based trajectory extraction and analysis method is introduced to construct large-scale structured pedestrian data, upon which stage-specific discrete choice models are employed to capture exit choice behaviors at different stages. Through cross-scenario case studies of daily routine egress in a metro station and emergency evacuation during an earthquake in a university library, the adaptability and effectiveness of the proposed framework are demonstrated. Results reveal significant scenario and stage dependence in evacuation behavior. Under normal conditions, pedestrian decision-making is guided by convenience, with visibility and distance being dominant factors. In contrast, during emergencies, the decision mode shifts toward efficiency, with flow speed emerging as a key determinant. Moreover, as evacuation progresses into later stages, pedestrians exhibit heightened crowding sensitivity and stronger herding behavior. Differentiated management strategies are proposed accordingly. Bootstrap resampling and agent-based simulations further confirm the robustness and predictive accuracy of the proposed framework. The main contribution of this study lies in establishing a systematic multi-stage evacuation modeling paradigm that links behavioral theory with predictive choice models, quantifies the behavioral shifts across both different scenarios and evacuation stages, and provides a methodological basis for analyzing the entire evacuation process.

准确理解和预测疏散过程中行人出口的选择是加强公共安全管理的关键科学问题。针对现有研究在数据真实性、过程建模不完整、跨场景适用性等方面的局限性，提出了一种行人出口选择的多阶段建模框架。在行为科学理论的基础上，提出了基于决策节点的阶段划分程序和识别准则。引入基于视频的轨迹提取与分析方法，构建大规模结构化行人数据，并在此基础上采用基于阶段的离散选择模型捕捉不同阶段的出口选择行为。通过对地铁车站日常疏散和大学图书馆地震时紧急疏散的跨场景案例研究，验证了该框架的适应性和有效性。结果表明，疏散行为具有明显的情景和阶段依赖性。在正常情况下，行人的决策以便利性为导向，能见度和距离是主导因素。相反，在紧急情况下，决策模式转向效率，流速成为关键的决定因素。此外，随着疏散进入后期阶段，行人表现出更强的拥挤敏感性和更强的羊群行为。并据此提出差异化经营策略。自举重采样和基于智能体的仿真进一步验证了该框架的鲁棒性和预测准确性。本研究的主要贡献在于建立了一个系统的多阶段疏散建模范式，将行为理论与预测选择模型联系起来，量化了不同情景和疏散阶段的行为变化，为分析整个疏散过程提供了方法论基础。

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引用次数: 0

Machine learning in pedestrian and evacuation dynamics for the built environment: A systematic literature review 机器学习在行人和疏散动力学的建筑环境：系统的文献综述

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-23 DOI: 10.1016/j.ssci.2026.107143

Patrick Berggold, Ana Čukarska, Stavros Nousias, Felix Dietrich, André Borrmann

The study of pedestrian and crowd movement has produced a plethora of publications over the past decades. Numerous knowledge-based models have been developed to describe, analyze and predict human motion behavior, particularly with respect to evacuation analysis to ensure public safety. In recent years, Machine Learning (ML) models have become widely successful across many disciplines, including applications for human behavior in the built environment, city planning, robotics and autonomous driving. In this review article, based on a systematic search of the Scopus database (2022–2024), we present a comprehensive overview of ML-based pedestrian and crowd models, highlighting the most popular approaches, as well as modern data collection methods that have led to public benchmark datasets and increasingly standardized model validation techniques. We analyze ML models that provide insights into crowd movement and evacuation performance, potentially supporting building design and safety assessment in the built environment, while outlining similarities and differences between these models with regards to behavioral traits such as goal-driven behavior and collision avoidance. Moreover, we review the involved learning paradigms, including supervised and reinforcement learning, and the associated quantities of interest that can be predicted, such as velocity, density, flow, and evacuation time.

在过去的几十年里，对行人和人群运动的研究产生了大量的出版物。已经开发了许多基于知识的模型来描述、分析和预测人类的运动行为，特别是在疏散分析方面，以确保公共安全。近年来，机器学习（ML）模型在许多学科中取得了广泛的成功，包括在建筑环境、城市规划、机器人和自动驾驶中的人类行为应用。在这篇综述文章中，基于对Scopus数据库（2022-2024）的系统搜索，我们全面概述了基于ml的行人和人群模型，重点介绍了最流行的方法，以及现代数据收集方法，这些方法导致了公共基准数据集和日益标准化的模型验证技术。我们分析了ML模型，这些模型提供了对人群移动和疏散性能的见解，可能支持建筑环境中的建筑设计和安全评估，同时概述了这些模型在目标驱动行为和避免碰撞等行为特征方面的异同。此外，我们回顾了所涉及的学习范式，包括监督学习和强化学习，以及可以预测的相关兴趣量，如速度、密度、流量和疏散时间。

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引用次数: 0

How do workers decide to work safely? Mechanisms of occupational safety decision-making failure 工人如何决定安全工作？职业安全决策失效的机制

IF 5.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Safety Science

Pub Date : 2026-06-01 Epub Date: 2026-02-18 DOI: 10.1016/j.ssci.2026.107144

Yang Liu , Gui Ye , Qingting Xiang , Sen Wang

Occupational safety decision-making failures among employees represent a fundamental challenge for organizations, as such failures are a significant factor in unsafe behaviors and accidents. However, the specific causes of occupational safety decision-making failure remain inadequately understood. To address this research gap, this study explores the mechanisms of occupational safety decision-making failure from the perspective of the matching degree between safety decision-making capability and task demands. Drawing on the task-capability interface model and resource limitation theory, this study proposes that a U-shaped relationship between the matching degree of safety decision-making capability and task demands, and safety decision-making failure. Through an experimental vignette study involving 252 industry employees and hierarchical regression analysis, the study validates the proposed model. The results indicate that the impact of the matching degree between safety decision-making capability and task demands on safety decision-making failure is U-shaped. Additionally, optimism bias moderates this U-shaped relationship. Theoretically, this study is the first to propose and validate the U-shaped impact of safety decision-making capability-task demand matching degree on safety decision-making failure. This finding not only deepens the understanding of the potential mechanisms of occupational safety decision-making failure but also contributes to the development of the task-capability interface model. Practically, the study emphasizes the importance of dynamically balancing safety decision-making capability and task demands. Organizations should not only prevent risks arising from insufficient safety decision-making capability relative to task demands but also avoid decision laxity and distraction caused by excessive capability. This balance ensures optimal decision-making and reduces occupational safety accidents.

员工的职业安全决策失误对组织来说是一个根本性的挑战，因为这种失误是不安全行为和事故的重要因素。然而，职业安全决策失败的具体原因仍然没有得到充分的了解。为弥补这一研究空白，本研究从安全决策能力与任务需求匹配度的角度探讨职业安全决策失效的机制。利用任务-能力接口模型和资源限制理论，提出安全决策能力与任务需求匹配程度与安全决策失败呈u型关系。通过252名行业从业人员的实验研究和层次回归分析，验证了模型的有效性。结果表明：安全决策能力与任务需求的匹配程度对安全决策失败的影响呈u型；此外，乐观偏见调节了这种u型关系。在理论上，本研究首次提出并验证了安全决策能力-任务需求匹配度对安全决策失败的u型影响。这一发现不仅加深了对职业安全决策失败潜在机制的理解，而且有助于任务-能力界面模型的发展。实际上，研究强调了安全决策能力与任务需求动态平衡的重要性。组织既要防止安全决策能力相对于任务需求不足带来的风险，又要避免能力过大导致的决策松弛和分散注意力。这种平衡确保了最佳决策并减少了职业安全事故。

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引用次数: 0