Investigation of Risky Behaviour Among Indonesian Riders in Motorcycle-to-Motorcycle Collisions

Abstract

Motorcycle-to-motorcycle collisions are common, yet studies using video and questionnaire data are limited. This study analyzed 100 accident videos from social media and 100 questionnaire responses using crosstab and chi-square tests to identify patterns, key causal factors, and risky riding behaviors. Significant video variables (p < 0.05) included lighting (0.019), road category (0.034; 0.000), ignoring road markings (0.009), motorcycle brand (0.007), maneuvering (0.001), wrong-way riding (0.023), road width (0.032), traffic density (0.029), failure to use turn signals (0.007), high-speed riding (0.003), motorcycle type (0.011), intersections (0.045), and running red lights (0.031). Questionnaire data showed significant associations with failing to check mirrors (0.018), helmet use (0.043), age (0.005), and mechanical problems (0.001). The findings highlight the need for integrated prevention strategies, combining traffic discipline education with active safety technologies such as Anti-lock Braking System (ABS), Traction Control System (TCS), Forward Collision Warning (FCW), Lane Departure Warning/Lane Keeping Assist (LDW/LKA), Adaptive Cruise Control (ACC), Intelligent Speed Assistance (ISA), Traffic Sign Recognition (TSR), Driver Monitoring System (DMS), Blind Spot Monitoring, Automatic Headlamp On (AHO), Traffic Jam Assist (TJA), Intersection Assist/Cross Traffic Alert, and Automatic Turn Signal/Smart Indicators, as well as passive measures like wearable airbags and helmets with inner sun visors. By integrating these measures, the study suggests that such interventions can more effectively reduce motorcycle accident risks in Indonesia.