Abstract
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.
Highlights
Walking is an essential mode of transportation and movement of pedestrian remains the major component of today’s urban trans portation networks
This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying virtual reality (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 under stand 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
This study aims to identify the gaps in current data collection methods for pedestrian behaviour studies and pinpoints opportunities for new technologies to bridge these gaps
Summary
Walking is an essential mode of transportation and movement of pedestrian remains the major component of today’s urban trans portation networks. We suspect that the restrictions of the contemporary data collection methods (partially) induce a lack of these specific types of studies, data and insights featuring various types of particular pedestrian behaviour, for instance, pedestrian movement and choice behaviour during disasters, inside complex (multi-level) buildings, and in vast street networks. This study contributes to the existing literature in four ways, namely (1) it develops a pedestrian behaviour taxonomy that can be used to classify the broad range of pedestrian behaviour, (2) it presents a comprehensive review of experimental pedestrian behaviour studies with a specific focus on the capabilities of the adopted data collection methods to study pedestrian behaviour, (3) it identifies the most essential gaps of the contemporary data collection methods for pedes trian behaviour research, and (4) it discusses how new technologies can potentially bridge these gaps. The last section summarises the main conclusions of this review
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