Automatic detection of traffic rule violations at road junctions
| dc.contributor.advisor | ||
| dc.contributor.author | Alexander, Denis | |
| dc.date.accessioned | 2020-03-30T18:00:46Z | |
| dc.date.available | 2020-03-30T18:00:46Z | |
| dc.date.issued | 2017 | |
| dc.description | Available in print form, East Africana Collection, Dr. Wilbert Chagula Library, Class mark (THS EAF HE5614.5.T34A43) | en_US |
| dc.description.abstract | Traffic rule violations are common at road junctions. Violations cause accidents and congestion which can be minimized by improving the enforcement of road rules and regulations. The current enforcement methods use variety of deployment options including the use of traffic police sometimes in police patrol cars. The problem with this method includes high demand of human resource at all the problematic areas which requires more budget for hiring more police officers and for operation expenses which are scarce. Other challenges of the current methods include inconsistent, discontinuous, and involving one officer in many cases. This study used quantitative approach in data collection and analysis when determining traffic light violation at road junctions. Also, observations of driver’s behavior were made at selected junctions to understand better the red light jumping problem. Analysis of the observation was done and used as a basis to design algorithms. From the observation it was determined that three sub algorithms have to be designed to facilitate the detection of vehicles violating traffic light rule. Red light violation detection system was implemented based on the designed sub algorithms. Violation is detected and processed without human intervention by processing video serial images. The developed system can increase the effectiveness of the traffic regulations enforcement operations without significantly increasing the human resources required. Sample data collected from the field were used to test and evaluate the implemented prototype. The evaluation showed that the prototype was capable and effective in detecting red light violation with 73% success rate. | en_US |
| dc.identifier.citation | Alexander, D. (2017) Automatic detection of traffic rule violations at road junctions. Master dissertation, University of Dar es Salaam. Dar es Salaam. | en_US |
| dc.identifier.uri | http://41.86.178.5:8080/xmlui/handle/123456789/8570 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of Dar es Salaam | en_US |
| dc.subject | traffic rule | en_US |
| dc.subject | violations | en_US |
| dc.subject | road junctions | en_US |
| dc.subject | Automation | en_US |
| dc.subject | Tanzania | en_US |
| dc.title | Automatic detection of traffic rule violations at road junctions | en_US |
| dc.type | Thesis | en_US |