Vehicle proximity detection system for motorcycles.

dc.contributor.authorOcaya, Brian Opira
dc.date.accessioned2022-05-23T10:12:26Z
dc.date.available2022-05-23T10:12:26Z
dc.date.issued2018-05
dc.descriptionDissertation.en_US
dc.description.abstractThe automotive industry is mainly focusing on the road safety measures. The automobiles have been constantly updating with new sensing technologies to detect blind spots, rear ends which can prevent road accidents. Motorcycle accidents on the highways are a big factor of mortality and can cause severe injuries, Actually, motorcyclists nowadays ate getting more concerned about safety features in their motorcycles and thus are willing to pay the cost of acquiring safer motorcycles. The- existing systems use the side mirrors to detect rear approaching and in case of the side vehicles or other motorcycles on the sides the rider has to look behind before moving to another. lane on the grounds that side perspective mirrors don't see everything and its greatly affected by poor weather conditions and during night hours. The main objective of this project was designed and developed for vehicle proximity detection system for motorcycles. the system allows timely detection of the obstacles the system is -to be fast and reliable in delivery of notification hence the data is used to alert the motorcyclists for the safety measures.en_US
dc.description.sponsorshipMr. Arineitwe Joshua, Busitema University.en_US
dc.identifier.citationOcaya, B. O. (2018). Vehicle proximity detection system for motorcycles. Busitema University. Unpublished dissertation.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12283/1307
dc.language.isoenen_US
dc.publisherBusitema University.en_US
dc.subjectAutomotive industryen_US
dc.subjectRoad safety measuresen_US
dc.subjectRoad accidentsen_US
dc.subjectVehicle proximityen_US
dc.subjectMotorcyclesen_US
dc.subjectDetection systemen_US
dc.titleVehicle proximity detection system for motorcycles.en_US
dc.typeThesisen_US

Ocaya - Dept. of Informatics & Comp. Eng., 2018.pdf
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