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Title: Human factors in the design of traffic management systems
Author: Price, Joshua
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2016
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This research seeks to investigate how application of Human Factors techniques could be used to improve performance resulting from the use of technical traffic management and SCOOT validation systems. The systems used in both domains have historically been developed without consideration given to the social factors important to their use, designs instead being based solely on technical constraints. In the first stages of the project traffic management is investigated through conduction of a literature review covering the objectives, functions and constraints acting upon Traffic Management Centres (TMCs) in road, rail, maritime and air domains. Congestion management is then considered in urban road TMCs through application of the Event Analysis of Systematic Teamwork (EAST) method based on observational data collected from four TMCs, Bristol, Cardiff, Dorset and Nottingham, in which the tasks, social agents, information and relationships between these elements are considered. The EAST method is then expanded to enable investigation into TMCs’ resilience, providing further knowledge about the domain. The later stages of the project are concerned with SCOOT validation, the process by which adaptively controlled traffic lights using SCOOT are set up to reflect real traffic conditions. The domain, using the current PC SCOOT Urban Traffic Control system, is assessed through Cognitive Work Analysis (CWA) with the findings used to propose areas suitable for development. One of these areas, STOC validation, is then developed further by applying Ecological Interface Design to develop an alternative display addressing limitations with PC SCOOT’s display. This concept display is then evaluated through two empirical experiments examining performance compared to traditional displays and investigating the role of experience within the domain. Finally, by using insights obtained into the STOC validation process an automated STOC selection algorithm is developed which has the potential to redefine how STOC validation is conducted.
Supervisor: Stanton, Neville Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available