Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach.

Road accidents cause a large number of deaths, especially in Thailand. When considered in depth, motorcycles account for the highest percentage of fatalities. According to Heinrich's Safety Triangle Model, a decrease in near misses will reduce the number of road accidents. There is still a lack of studies on risky behaviors contributing to near misses involving motorcycles. This study aims to comprehend the various factors that influence the frequency of near-miss experiences using a questionnaire on near-miss incidents. The contributing factors include road factors (e.g., road surface, number of traffic lanes, speed limit), environmental factors (e.g., driving at night), and driver factors (e.g., using a phone while driving). Of the 2002 respondents, a total of 1547 people have occasionally experienced a near-miss incident. A random parameter probit model (RPOP) was used for analyzing the relationship between the contributing factors and the near-miss frequency, and model statistics clearly confirm that RPOPs that import only significant variables are the most suitable models. The study found 14 factors that affect near-miss frequency, and there are 5 variables that are random parameters. Variables that increase the chance of a near-miss incident include driving at night (both with and without lights), roads with concrete road surfaces, and roads with unclear lane markings. This study provides policy recommendations for relevant agencies that were identified to reduce near-miss motorcycle accidents.