Arduino-Based Vehicle Detection Sys.pptx

This research addresses the longstanding challenges surrounding underground lighting on curved highways, which have led to significant safety concerns and high crash rates (Adnan et al., 2020; Friesen et al., 2014). Underground lighting for curved highways poses longstanding issues for driver safety and high crash rates due to poor visibility conditions (Raj et al., 2016; Alsayaydeh et al.). Conventional vehicle detection methods are limited by poor lighting, obstructed sight lines, and radar interference in curved tunnels (Adnan et al., 2020; Raj et al., 2016). An Arduino-powered system for real-time vehicle detection and instant tunnel lighting activation shows promise to enhance visibility and safety by recognizing emergency vehicles and controlling traffic signals accordingly (Gowtham et al., 2021).

1. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

2. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS Introduction This research addresses the longstanding challenges surrounding underground lighting on curved highways, which have led to significant safety concerns and high crash rates (Adnan et al., 2020; Friesen et al., 2014). Underground lighting for curved highways poses longstanding issues for driver safety and high crash rates due to poor visibility conditions (Raj et al., 2016; Alsayaydeh et al.). Conventional vehicle detection methods are limited by poor lighting, obstructed sight lines, and radar interference in curved tunnels (Adnan et al., 2020; Raj et al., 2016). An Arduino-powered system for real-time vehicle detection and instant tunnel lighting activation shows promise to enhance visibility and safety by recognizing emergency vehicles and controlling traffic signals accordingly (Gowtham et al., 2021).

3. Objectives Develop an Arduino-based system for real-time vehicle detection on curved highways Enable instantaneous activation of additional overhead lighting as vehicles approach tunnels Enhance driver visibility and safety in underground curved highway sections Reduce energy consumption by implementing smart lighting control mechanisms. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

4. Framework The framework combines insights from traffic flow, accident causation, sensor fusion, and smart infrastructure. By incorporating concepts from these diverse fields, the framework addresses the multifaceted challenges associated with highway safety comprehensively. Quick detection methods such as interrupts and timing analysis are employed within the framework. These methods enable rapid identification of vehicles and facilitate prompt system responses, ensuring real-time monitoring and intervention to mitigate potential safety risks. The framework facilitates the generation and utilization of real-time traffic data. By continuously collecting and analyzing data from various sensors and sources, the framework provides valuable insights into traffic patterns, enabling better management and decision-making for optimizing traffic flow and enhancing safety measures. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

5. Framework ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

6. Methodology Create a prototype of the Arduino-based system and conduct initial testing in controlled environments. Choose and configure optimal sensors (such as optical or radar) and Arduino models to achieve accurate vehicle detection and rapid light activation. Fine-tune the system to ensure precise tracking of vehicles at high speeds and immediate activation of tunnel lighting upon detection. Conduct rigorous testing on real roads, spanning various curved tunnel environments to evaluate system performance under diverse conditions. Analyze test results to identify areas for improvement, focusing on enhancing detection accuracy, minimizing system lag, and optimizing light activation times. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

7. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

8. Results and Discussion The system demonstrated an impressive accuracy of 97% in detecting vehicles across various visibility conditions, as shown in the table above. This high accuracy rate ensures reliable detection even in challenging environments, thereby enhancing overall safety on curved highways. Visibility Condition Accuracy (%) Low visibility 95 Moderate visibility 97 High visibility 99 The system exhibited minimal lag, with an average delay of only 34 milliseconds between vehicle detection and system response. This swift response time ensures real-time monitoring and allows for immediate action, contributing to improved safety outcomes on the highways. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

9. Results and Discussion Upon detecting a vehicle, the system promptly activates tunnel lights within an average time of 72 milliseconds. This rapid response ensures timely illumination of tunnels, enhancing driver visibility and reducing the risk of accidents in underground sections of the highway. Implementation of the system led to a notable reduction of 51% in traffic violations. By providing real-time data and enhancing visibility, the system encourages better compliance with traffic regulations, ultimately contributing to safer driving conditions. The system's operation resulted in a significant decrease of 36% in accidents on the highways. This reduction underscores the system's effectiveness in mitigating potential hazards and improving overall safety for drivers navigating curved highway sections. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

10. Conclusion and Recommendations Demonstrated the effectiveness of the Arduino-based system in accurately detecting vehicles and promptly activating tunnel lighting, enhancing safety in underground highway sections. Documented measurable reductions in traffic violations and accident rates, highlighting the tangible benefits of improved visibility and real-time traffic data for drivers. Established the robustness of the methodology by successfully integrating principles from various disciplines to address complex transportation safety challenges. Illustrated the potential of embedded systems, such as Arduino-based solutions, to revolutionize transportation safety through innovative technology and smart infrastructure development. Suggested the need for further research and implementation of similar systems in diverse mobility contexts to maximize their impact on enhancing safety and efficiency in transportation networks. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS

11. References Adnan, Z., Hassan, M. Z., Ab Wahab, N., Najib, S. M., & Nasir, N. S. (2020). Vehicle blind spot monitoring phenomenon using ultrasonic sensor. International Journal of Emerging Trends in Engineering Research, 8(8). Friesen, M., Jacob, R., Grestoni , P., Mailey , T., Friesen, M. R., & McLeod, R. D. (2014). Vehicular traffic monitoring using bluetooth scanning over a wireless sensor network. Canadian Journal of Electrical and Computer Engineering, 37(3), 135-144. Raj, S., Ezhilarasie , R., & Umamakeswari , A. (2016). Zigbee-based collision avoidance system in blind spot and heavy traffic using ultrasonic sensor. Indian Journal of Science and Technology, 9(48), 1-5. Alsayaydeh , J. A. J., bin Yusof, M. F., bin Abdillah , M. A. A., Al- Gburi , A. J. A., Herawan , S. G., & Oliinyk , A. Enhancing Vehicle Safety: A Comprehensive Accident Detection and Alert System. Gowtham, D. R. P., Varshini, M. S., Revathi, S., Selva, T., & Munishwari , M. (2021). RECOGNITION OF EMERGENCY VEHICLE USING LIGHT DETECTION AND TRAFFIC LIGHT CONTROLLING. Yadav, A., Daharwal , K., Kale, A., Tayade , P., & Nagani , A. (2020). Density & Sound Based Vehicular Traffic Controller. ARDUINO-BASED REAL-TIME INCOMING VEHICLE DETECTION FOR UNDERGROUND LIGHTS FOR CURVED HIGHWAYS