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Traffic incident detection using inrix data

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Titel: Traffic incident detection using inrix data
Autoren: Byna, Raviteja Raja
Quelle: Creative Components
Verlagsinformationen: Iowa State University Digital Repository
Publikationsjahr: 2019
Schlagwörter: TIMELI, Spark, Spring Boot Java, MongoDB, TIM, incident, Software Engineering, Systems Architecture, info, archi
Beschreibung: Over the last decade, it is estimated that 25% of the congestion on the US roads is due to traffic incidents such as crash, overturned trucks or stalled vehicles. Currently available software based intelligent transportation systems does not provide comprehensive decision support to minimize the impact of traffic incidents and do not detect the incidents on time. The aim of the TIMELI project is to develop a robust and fast incident detection on the road. Lambda architecture is used to design the architecture of TIMELI project. Different technologies are explored to finalize the best design to accomodate the given functional and non-functional requirements. In this incident detection method, real time data of speed of each segment on the road is recorded every minute. This data is used to detect any congestion or incident anomalies and alert the TIM(Traffic Management Operator) immediately. Also, it can automatically close the incident. The algorithm also captures the start of the incident as well as time it ended. The incidents are stored for data analytics and incident validation and performance.
Publikationsart: text
Sprache: unknown
Relation: https://lib.dr.iastate.edu/creativecomponents/147
Verfügbarkeit: https://lib.dr.iastate.edu/creativecomponents/147
Rights: undefined
Dokumentencode: edsbas.27840FF4
Datenbank: BASE
Beschreibung
Abstract:Over the last decade, it is estimated that 25% of the congestion on the US roads is due to traffic incidents such as crash, overturned trucks or stalled vehicles. Currently available software based intelligent transportation systems does not provide comprehensive decision support to minimize the impact of traffic incidents and do not detect the incidents on time. The aim of the TIMELI project is to develop a robust and fast incident detection on the road. Lambda architecture is used to design the architecture of TIMELI project. Different technologies are explored to finalize the best design to accomodate the given functional and non-functional requirements. In this incident detection method, real time data of speed of each segment on the road is recorded every minute. This data is used to detect any congestion or incident anomalies and alert the TIM(Traffic Management Operator) immediately. Also, it can automatically close the incident. The algorithm also captures the start of the incident as well as time it ended. The incidents are stored for data analytics and incident validation and performance.