IOT-Based Accident Prevention System: A Model Experiment for U-Turn Curves
DOI:
https://doi.org/10.5281/zenodo.15365062Keywords:
U Turn, IOT, LED Light, Sensor, Signal, Vehicle, Driver, Accident, PreventionAbstract
In today’s world, the combination of high population density and the widespread use of vehicles has led to a serious concern: the increasing number of road accidents. Every year, thousands of people lose their lives or suffer serious injuries in such incidents. In developing countries like India, road accidents remain one of the leading causes of death. National highways, as well as mountain and hill areas, have dangerous roads and curves that are narrow and single-lane. Accidents at U-turns commonly occur due to limited sight distance, especially on curved or hilly roads, where drivers cannot see oncoming traffic in time to react safely. Inadequate road signage, poor lighting, and lack of dedicated turning lanes further increase the risk. Additionally, high vehicle speeds, misjudgment of gaps in traffic, and sudden or illegal U-turns made without proper signaling often lead to collisions. In areas with high traffic volume or narrow roads, the risk multiplies as vehicles may not have sufficient space or time to complete a U-turn safely. Addressing these risks requires a combination of improved road design, warning systems, enforcement of traffic laws, and driver awareness. At these curved sections, drivers are often unable to see oncoming vehicles or obstacles, and if their vehicle is not in good condition, it becomes difficult to control, increasing the risk of accidents. To minimize such accidents, we propose a project aimed at preventing collisions at U-turns by alerting drivers to oncoming vehicles. This is done by keeping an ultra sound sonic sensor on both sides of the U-turn and so that if vehicle comes from one end of the curve, then sensor senses and it gives signal to Arduino and Arduino gives command to LED lights of the other side in order to alert the driver.
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Copyright (c) 2025 Kamireddy Devaki, Brundavanam Krishna Manojna, Bhimavarapu Jayanth Reddy, Bhimavarapu Sasank Reddy, Kamireddy Hareswara Reddy
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