| Title | INVESTIGATING THE KEY FACTORS CONTRIBUTING TO FREEWAY ACCIDENT-PRONE SCENARIOS BASED ON ADAS WARNINGS AND RISK EVENTS OF FREEWAY BUSES |
| Author | Tzu-Yin Pai, Yu-Hsing Wang, Yu-Chiun Chiou, Yi-Shih Chung, Kun-Feng Wu, Tsu-Hurng Yeh, Shih-Hsuan Huang, Ching-Hsuan Lee |
| Summary | Most of previous studies identify the high-risk scenarios of road networks based on traffic accidents. However, due to the scarcity and randomness of accidents, the studies require a long-time observation and is nearly impossible to investigate the newly formed risk scenarios proactively. With the rapid growth of ADAS adoption, how to use of the crash surrogate data to investigate the risk factors is essential. Accordingly, based on the data 200 freeway trips of the bus company A, this study uses of a negative binomial model to investigate the key factors forming the high-risk freeway segments and bus trips based on the frequency of warnings and risk events. Additionally, an ordered probit model is used to examine the key factors causing the risk levels of a warning events. The estimation results (a case of unsafe distance events) show that high traffic volume, high ratio of passenger cars and high number of trips are key risk factors. Meanwhile, for the risk level of unsafe distance warnings, the warnings activated at the site with upgrade, higher speed, southbound (return trip), high number of trips and in the morning peak hours would have higher risk level. The identified risk factors helpful for road authorities to improve traffic safety. |
| Vol. | 54 |
| No. | 1 |
| Page | 1 |
| Year | 2025 |
| Month | 3 |
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