Light detection and ranging lidar sensor-based rear-end collision awareness system for cyclists/ Kamille Rose A. Abueva, Catherine Mae A. Acuno, Neildren S. Agapay, En Jelle B. Albarida, Burton Ysaac T. Ballo, and Jean Yasmin P. Manalansan

Includes bibliography

Bicycle-related Road crashes in Metro Manila are piling up as there is a lack of bicycle-safety schemes planned and implemented in the vicinity. To improve road cycling safety in the area, this research study presents a LiDAR sensor-based rear-end collision awareness system through augmenting an Android application with auditory and visual warning capabilities, whereas it detects an approaching vehicle and alerts the cyclist in real-time before the encounter. The researchers utilized an 8-meter LiDAR sensor then interfaced with a microcontroller unit, a mobile application, and other system peripherals to simulate an awareness system. The researchers used Basic4Android IDE for the development of the Android application and Arduino Integrated Development Environment (IDE) for processing the data from the LiDAR sensor. A Dependent T-test method was used to test the functional correctness of the LiDAR sensor as this significantly proves that the LiDAR sensor was found to be accurate in terms of providing data in the visual warning display in its Android application. Using the same test method, it was verified that the LiDAR sensor can accurately provide data in the prototype's auditory warning output even in daytime and nighttime conditions. In terms of its performance efficiency, testing results using the Dependent t-test method ensures the LiDAR sensor's efficiency in providing data without any significant delays to the user during daytime and nighttime conditions. In conclusion, the testing results identified that the prototype is functionally accurate and reliable in providing safety awareness on the road.