Low cost vehicle driving assistance system

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dc.contributor.authorMangezi, Stewart Tatenda Maposa
dc.date.accessioned2021-01-28T11:05:50Z
dc.date.available2021-01-28T11:05:50Z
dc.date.issued2020-05
dc.descriptionCapstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2020en_US
dc.description.abstractThe project intends to increase vehicle operator awareness with the integration of a Low-Cost Driving Assistance system in older car models. Situational awareness during driving significantly reduces the number of road traffic accidents, as proved by literature. A 4-wheel mobile robot is used as the plant representing a vehicle for easier and rapid prototyping. The plant is controlled by a Raspberry Pi3 to achieve the desired control choice as well as do all required computational processes. Image processing using a retrained Resnet50 neural network is adopted for road traffic signs. A 54% accuracy rate for image recognition is recorded. The wheeled mobile robot is successfully modeled and deemed unstable while the circuit is simulated and works as expected.en_US
dc.description.sponsorshipAshesi Universityen_US
dc.identifier.urihttp://hdl.handle.net/20.500.11988/607
dc.language.isoen_USen_US
dc.subjecttraffic accidentsen_US
dc.subjectdriver awarenessen_US
dc.subjectroboten_US
dc.subjectroad accident preventionen_US
dc.titleLow cost vehicle driving assistance systemen_US
dc.typeSenior projecten_US

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