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AI on the Road: A Comprehensive Analysis of Traffic Accidents and Accident Detection System in Smart Cities

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arxiv 2307.12128 v1 pith:767JDEIK submitted 2023-07-22 cs.CV cs.AIcs.CYcs.LG

classification cs.CVcs.AIcs.CYcs.LG
keywords trafficaccidentaccidentsanalysisdetectionsystemssmartcameras
verification ladder T0 review T1 audit T2 compute T3 formal

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Accident detection and traffic analysis is a critical component of smart city and autonomous transportation systems that can reduce accident frequency, severity and improve overall traffic management. This paper presents a comprehensive analysis of traffic accidents in different regions across the United States using data from the National Highway Traffic Safety Administration (NHTSA) Crash Report Sampling System (CRSS). To address the challenges of accident detection and traffic analysis, this paper proposes a framework that uses traffic surveillance cameras and action recognition systems to detect and respond to traffic accidents spontaneously. Integrating the proposed framework with emergency services will harness the power of traffic cameras and machine learning algorithms to create an efficient solution for responding to traffic accidents and reducing human errors. Advanced intelligence technologies, such as the proposed accident detection systems in smart cities, will improve traffic management and traffic accident severity. Overall, this study provides valuable insights into traffic accidents in the US and presents a practical solution to enhance the safety and efficiency of transportation systems.

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