A framework for qualitative transportation management plan assessment using cognitive task analysis methods

• Main Author: Nittala, Ambareesha
• Format: Others
• Language: en
• Published: 2015
• Subjects: Cognitive task analysis; TMP
• Online Access: http://hdl.handle.net/2152/28673

Increasingly, highway transportation projects are tending to involve maintenance and rehabilitation work. The age and the condition of the transportation asset, in addition to funding constraints have been the key drivers of this trend. This implies that construction operations take place in the presence of traffic flows, leading to the creation of construction work zones. This has safety implications for the commuters and construction workers alike. In addition, construction operations also hamper mobility through the work zone. Effective management of the work zone is thus very important from the perspective of construction and mobility. The preferred and mandated method to manage the impacts of the work zone is the Transportation Management Plan, which prescribes a set of coordinated strategies for the same. The strategies used in a TMP range from enforcing lane closures to modifying the construction sequencing. As the choice of particular strategies or a combination of those affects the work zone, assessing TMP strategies is important to inform future decisions. This thesis proposes a framework for the qualitative assessment of TMP strategies and TMP processes using cognitive task analysis methods. The application of the proposed method is demonstrated through two case studies of large highway reconstruction projects, involving significant bridge reconstruction. The knowledge elicitation techniques are discussed and the obtained knowledge is represented using different knowledge representation structures. The benefits and the applicability of CTA methods are explored through the case studies of projects using different contracting strategies. Finally, recommendations are made for the design of decision support tools, based on the insights obtained through the analysis. === text