Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/3647
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Allopi, Dhiren | - |
dc.contributor.author | Sarjoo, Arvin Ramsunder | en_US |
dc.date.accessioned | 2021-08-19T05:00:17Z | - |
dc.date.available | 2021-08-19T05:00:17Z | - |
dc.date.issued | 2020-06 | - |
dc.identifier.uri | https://hdl.handle.net/10321/3647 | - |
dc.description | Submitted in fulfilment of the academic requirements for the degree of Master of Engineering: Civil Engineering and Geomatics, Durban University of Technology, Durban, South Africa, 2020. | en_US |
dc.description.abstract | The word “accident” is a familiar term used to describe a collision involving one or more transportation vehicles that results in property damage, injury or death. The term implies a random event that occurs due to no specific reason other than human error or unforeseen circumstances. The American National Highway Traffic Safety Administration (NHTSA) suggests replacing the word “accident” with “crash” as the word “crash” implies that the collision could have been prevented or minimised by improving driver behaviour, vehicle design, roadway geometry or the environment (Garber and Hoel 2015: 150). In the global context, South Africa, as is characteristic of many developing countries with limited resources, faces the challenge to proactively managing, reducing and eliminating the high incidence of road crashes, injuries and fatalities. Due to an absence of routine Road Safety Assessment and Audit procedures within the relevant departments at the City of Tshwane Metropolitan Municipality (CTMM), the main aim of this research was to develop procedures with measurable benefits which would promote a safer road environment. The data analysis and findings describe statistically significant relationships between Average Daily Traffic (ADT) as the independent variable and Accident Frequency as the dependant variable. The linear regression models and equations as developed allowed for the prediction of crash rates and the prioritisation of CTMM road safety projects. The findings indicated significant increases in accident rates on higher order roads (typically traffic signalled controlled intersections) with factors such as a greater number of intersection conflict points, greater pedestrian volumes and increased intersection saturation or volume/capacity levels contributing to higher accident rates. Intersection controls and traffic safety measures such as traffic circles, traffic signals, and traffic signs were assessed for effectiveness in reducing the Rate of Accidents per Million of Entering Vehicles (RMEVs). The research highlights the vulnerability of Non-Motorised Transport (NMT) (particularly pedestrians) which contributed to approximately 40% of all accident fatalities (Department of Transport 2016: 31). The recommendation therefore is for a road safety assessment and screening process to focus and allocate greater resources in the effort to proactively reduce the number of pedestrian fatalities. | en_US |
dc.format.extent | 110 p | en_US |
dc.language.iso | en | en_US |
dc.subject | Road accidents | en_US |
dc.subject | Transportation vehicles | en_US |
dc.subject | Road Safety Assessment and Audit procedures | en_US |
dc.subject | Average Daily Traffic (ADT) | en_US |
dc.subject.lcsh | Traffic safety--South Africa | en_US |
dc.subject.lcsh | Roads--South Africa--Design and construction | en_US |
dc.subject.lcsh | Roads--Safety measures | en_US |
dc.subject.lcsh | Automobiles--Collision avoidance systems | en_US |
dc.title | The development of road safety assessment screening procedures for the City Tshwane Metropolitan Municipality | en_US |
dc.type | Thesis | en_US |
dc.description.level | M | en_US |
dc.identifier.doi | https://doi.org/10.51415/10321/3647 | - |
local.sdg | SDG03 | - |
local.sdg | SDG11 | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en | - |
item.openairetype | Thesis | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | Theses and dissertations (Engineering and Built Environment) |
Files in This Item:
File | Description | Size | Format | |
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Arvin Sarjoo_Final_MEng Dissertation_2020.pdf | 3.75 MB | Adobe PDF | View/Open |
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