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dc.contributor.authorBakker-Reynolds, Gabrielle
dc.date.accessioned2022-04-26T21:29:16Z
dc.date.available2022-04-26T21:29:16Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/10652/5670
dc.description.abstractRESEARCH QUESTION How can computer vision be used to support traffic flow analysis? RESEARCH SUB-QUESTIONS What is required within the planning, development and implementation phases of a prototype that performs accurate vehicle detection? How will the performance of a vehicle-detection prototype be measured? What are the barriers to the development of a vehicle-detection prototype? Computer vision holds the capabilities of performing duties by replicating tasks that the human visual system accomplishes. For this reason, computer vision is being employed as a tool to modernise and advance the management of traffic on a global scale. Traffic management remains an issue in many regions of the world, evidenced by barriers such as street obstacles, inefficient road signals, vehicles speeding, traffic congestion, and underdevelopment of freeways. Due to this, computer vision-driven management systems have been developed to combat such problems, demonstrated by their role in travel assistance and navigation, parking management and enforcement, real-time traffic control, and license plate recognition (Buch et al., 2011). Subsequently, this research explores how vehicle detection can be applied to support traffic flow analysis within Hawkes Bay, New Zealand through the use of computer vision approaches. This research assumes a design-based approach, comprised of two iteration-based approaches employed to develop a prototype for vehicle detection utilising an Nvidia Jetson Nano. The approaches are analysed according to accuracy, processing time, cost, and overall suitability. Results show that the prototype has great potential as an alternative approach to current traffic flow analysis. Finally, recommendations are offered for future research and other users working with similar devices.en_NZ
dc.language.isoenen_NZ
dc.rightsAll rights reserveden_NZ
dc.subjectHawke's Bay (N.Z.)en_NZ
dc.subjectNew Zealanden_NZ
dc.subjectvehicle detectionen_NZ
dc.subjectNvidia Jetson Nano Developer Kiten_NZ
dc.subjectobject detectionen_NZ
dc.subjecttraffic managementen_NZ
dc.subjectcomputer visionen_NZ
dc.subjecttraffic flowsen_NZ
dc.titleModernising traffic flow analysis: A computer vision-driven prototype for vehicle detectionen_NZ
dc.typeMasters Dissertationen_NZ
dc.rights.holderAuthoren_NZ
thesis.degree.nameMaster of Information Technologyen_NZ
thesis.degree.levelMastersen_NZ
thesis.degree.grantorEastern Institute of Technology (EIT)en_NZ
dc.subject.marsden460304 Computer visionen_NZ
dc.subject.marsden330409 Transport planningen_NZ
dc.identifier.bibliographicCitationBakker-Reynolds, G. (2020). Modernising traffic flow analysis: A computer vision-driven prototype for vehicle detection. (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Information Technology). Eastern Institute of Technology (EIT), New Zealand. https://hdl.handle.net/10652/5670en
unitec.pages142en_NZ
unitec.institutionEastern Institute of Technology (EIT)en_NZ
dc.contributor.affiliationEastern Institute of Technologyen_NZ
unitec.publication.placeNew Zealanden_NZ
unitec.advisor.principalErturk, Emre
unitec.advisor.associatedLengyel, Istvan
unitec.institution.studyareaInformation Technologyen_NZ


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