SafeRoute-A Comprehensive Travel Solution
Abstract
Travel safety is a critical concern for individuals navigating urban environments, especially in areas prone to crime or high-risk incidents. Traditional navigation systems primarily focus on the shortest or fastest routes, often neglecting security considerations. This research explores the integration of safety-based routing mechanisms to enhance secure travel experiences. By analyzing existing safe route guidance systems, crime data integration, and predictive modelling for high-risk areas, this study aims to develop an
intelligent travel safety framework. The research examines multiple factors influencing safe navigation, including crime hotspots, real-time traffic conditions, environmental factors, and user-generated data. The findings suggest that a hybrid approach combining real-time data analysis, historical crime trends, and AI-driven route optimization can significantly improve travel security. This study contributes to the development of a comprehensive Safe Route Navigation System, enhancing personal security and informed decision
making for travellers.
Keywords:
safe route, crime data, safe route navigation system, safe route guidance system, Crowd-sourcing, Intelligent Transportation Systems (ITS), Safe Path Algorithm using Feedback and Environment, MultiAttribute Decision Making (MADM)
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