Smart Road Safety and Vehicle Accident Prevention System for Mountain Roads

Abstract

Abstract: Roads that lead through mountains  present unique challenges for drivers due to their winding paths, steep inclines, and unpredictable weather conditions. To address the heightened risk of accidents in these areas, a proposed Smart Road Safety and Vehicle Accident Prevention System (SRSP) integrates advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) to bolster road safety and prevent accidents. The SRSP deploys a network of sensors along mountainous routes to gather real-time data on various factors including road conditions, weather patterns, and traffic density. Utilizing AI algorithms, this data is then analyzed to identify potential hazards and predict areas prone to accidents. Moreover, the system incorporates vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication protocols to enable proactive safety measures such as adaptive speed control, hazard alerts, and emergency braking assistance. In the event of an impending collision, the SRSP automatically notifies drivers and nearby vehicles while also alerting emergency services for rapid response. Furthermore, the system furnishes valuable insights to road authorities, aiding in the optimization of maintenance schedules and the enhancement of road infrastructure to further bolster safety measures. Ultimately, the SRSP offers a comprehensive solution to mitigate the risks associated with mountain road travel, thereby saving lives, and diminishing the economic and social toll of accidents.

Index Terms: Mountain roads, Smart Road Safety, Vehicle Accident Prevention System, IoT, Artificial Intelligence, Machine Learning, Senslives Real-time data, Hazard prediction.