Head-on railway obstruction: a probabilistic model

Abstract

It has been recently demonstrated, mostly in application to the aerospace domain, how probabilistic analytical modeling (PAM) could effectively complement computer simulations in various human-system-integration (HSI) related situations, when the system’s reliability and the human’s performance contribute jointly to the never-zero probability of an accident. One of the developed models, the convolution model, is brought here “down to earth” in application to a possible head-on railway obstruction. A situation, when an unexpected steadfast obstacle is suddenly detected in front of a train moving on a single-track railway is addressed, and the case when the machinist has to intervene is considered. The roles of the following major factors are accounted for: the swiftness in the machinist’s reaction, the effectiveness of the train’s breaking system (from the standpoint of the time required for the transition from the train’s constant speed to constant deceleration), and the available sight distance (ASD) detected by the train’s radar and/or LiDAR. It is concluded that the application of PAM in combination with computer simulations could improve appreciably the state-of-the-art in assuring railway safety. A similar formalism can be employed in automated driving (AD) engineering.

Keywords:

• Head-on obstruction
• human factor
• probabilistic risk assessment

Disclosure statement

No potential conflict of interest was reported by the author(s).