Transportation Research Group, Faculty of Engineering and Physical Science, University of Southampton, Southampton, UK.
Transportation Research Group, Faculty of Engineering and Physical Science, University of Southampton, Southampton, UK.
Appl Ergon. 2022 Oct;104:103801. doi: 10.1016/j.apergo.2022.103801. Epub 2022 Jun 1.
Passengers' travel behaviour is one of the significant factors affecting train overcrowding. Train occupancy information has been introduced as a tool to stimulate passengers' behaviour change to ease in-vehicle crowding. However, there are limitations to this strategy as it often fails to consider other elements in the complex rail system that influence behaviour. This research provides insights to service providers to promote passenger behaviour change by revealing the behavioural constraints in the environment. Cognitive Work Analysis (CWA) was applied to systematically analyse passengers' behaviour and related constraints in the environment. Specifically, Work Domain Analysis (WDA) and Social Organisation and Cooperation Analysis (SOCA) were conducted and presented in the forms of Abstraction Hierarchy (AH) and Contextual Activity Template (CAT). Results showed that a wide range of informational, navigational and physical support alongside provision of occupancy information could better encourage passengers to select and use less busy carriages and trains. Behaviour change goals are likely to be achieved more effectively when the constraints of the system are better understood.
乘客的出行行为是影响列车拥挤的重要因素之一。列车满载率信息的引入是一种激励乘客改变行为以缓解车内拥挤的工具。然而，这种策略存在局限性，因为它往往没有考虑到影响行为的复杂铁路系统中的其他因素。本研究通过揭示环境中的行为约束，为服务提供商提供了促进乘客行为改变的思路。认知工作分析（CWA）被应用于系统地分析乘客的行为和相关的环境约束。具体来说，进行了工作域分析（WDA）和社会组织与合作分析（SOCA），并以抽象层次（AH）和情境活动模板（CAT）的形式呈现。结果表明，提供大量信息、导航和物理支持以及满载率信息，可以更好地鼓励乘客选择和使用不太拥挤的车厢和列车。当更好地理解系统的约束时，更有可能更有效地实现行为改变目标。
