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dc.contributor.authorMusinguzi, Yvonne Ritah
dc.date.accessioned2022-11-29T07:17:56Z
dc.date.available2022-11-29T07:17:56Z
dc.date.issued2019-07-22
dc.identifier.citationMusinguzi, Yvonne Ritah. (2019). Collision avoidance algorithm based on vehicle to vehicle(V2V) communication for autonomous vehicles. (Unpublished undergraduate dissertation) Makerere University; Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/13656
dc.descriptionA research report submitted to the College of Engineering Design and Art in partial fulfillment of the requirement for the award of the degree Bachelor of Telecommunications Engineering of Makerere University.en_US
dc.description.abstractAccording to The United Nations Economic Commission for Africa, the United Nations Road Safety Performance Review for Uganda that was written in February, 2018 established that the magnitude of the road safety challenge is serious and has unfortunately failed to attract the necessary attention for appropriate interventions in our country. In Uganda, the accident severity index is 24 people killed per 100 road crashes. On average, ten people per day in road traffic crashes which is the highest in East Africa. In this project, we design a traffic inter-vehicle communication algorithm for collision avoidance for autonomous cars based on Vehicle-to-Vehicle(V2V) communication based on Device-to Device communication, as a way to reduce the number of traffic accidents in Uganda. V2V basically allows for direct exchange of information between vehicles and with this, a collision may be avoided. This project also moves on to study frequency re-use and the Signal-to-Interference-plus-Noise Ratio (SINR) distribution within the small cells for V2V communication linksen_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectCollision avoidance algorithmen_US
dc.subjectVehicle to vehicle(V2V) communicationen_US
dc.subjectAutonomous vehiclesen_US
dc.titleCollision avoidance algorithm based on vehicle to vehicle(V2V) communication for autonomous vehiclesen_US
dc.typeThesisen_US


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