Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This systematic review of 145 studies aims to determine the capability of contemporary data collection methods in collecting different pedestrian behavioural data, identify research gaps and discuss the possibilities of using new technologies to study pedestrian behaviour. The review finds that there is an imbalance in the number of studies that feature various aspects of pedestrian behaviour, most importantly (1) pedestrian behaviour in large complex scenarios, and (2) pedestrian behaviour during new types of high-risk situations. Additionally, three issues are identified regarding current pedestrian behaviour studies, namely (3) little comprehensive data sets featuring multi-dimensional behaviour data simultaneously, (4) generalizability of most collected data sets is limited, and (5) costs of pedestrian behaviour experiments are relatively high. A set of new technologies offers opportunities to overcome some of these limitations. This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying VR experiments to study pedestrian behaviour in the environments that are difficult or cannot be mimicked in real-life, repeat experiments to determine the impact of factors on pedestrian behaviour and collect more accurate behavioural data to understand the decision-making process of pedestrian behaviour deeply, (2) applying large-scale crowd monitoring to study pedestrian movements in large complex environments and incident situations, and (3) utilising the Internet of Things to track pedestrian movements at various locations that are difficult to investigate at the moment.

中文翻译：

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研究行人行为的数据收集方法：系统评价

收集行人行为数据对于了解行人行为至关重要。对 145 项研究的系统回顾旨在确定当代数据收集方法在收集不同行人行为数据方面的能力，确定研究差距并讨论使用新技术研究行人行为的可能性。审查发现，以行人行为的各个方面为特征的研究数量不平衡，最重要的是 (1) 大型复杂场景中的行人行为，以及 (2) 新型高风险情况下的行人行为。此外，目前行人行为研究确定了三个问题，即（3）同时具有多维行为数据的综合数据集很少，(4) 大多数收集到的数据集的泛化能力有限， (5) 行人行为实验的成本相对较高。一组新技术提供了克服其中一些限制的机会。本综述确定了三种类型的技术，它们可以成为行人行为研究方法的宝贵补充，即 (1) 应用 VR 实验来研究现实生活中难以或无法模仿的环境中的行人行为，重复实验以确定因素对行人行为的影响，收集更准确的行为数据，以深入了解行人行为的决策过程，（2）应用大规模人群监测，研究大型复杂环境和事件情况下的行人运动，