Collision avoidance systems in air and maritime traffic

Abstract

In each transport mode, collisions between vehicles are one of the major operational risks. In maritime traffic collisions and groundings is the category with the highest frequency of all accidents. Although new navigational equipment, often combined with enhanced computer-based systems, is installed on ships’ bridges, the number of collisions is still at a high level. The equivalent of ship collisions in air traffic is the mid-air collision. Compared to the maritime accident rate, mid-air collisions are very rare. In this paper we investigate the onboard collision avoidance process by focusing on technical support systems with implemented alerts to support the human operator. Empirical field studies have been undertaken to analyse the situation regarding the occurrence and handling of alerts onboard seagoing vessels. Especially with respect to collision avoidance alarms, the situation was found to be unsatisfactory. The algorithms in use are based on fixed static limit values and little selected information is used although new systems provide more and enhanced situation-specific data. A comparative study of the traffic-alert and collision avoidance system used by air traffic is made to identify potentials for synergies to improve maritime operational risk management. As an innovative approach, the development of a concept to adapt alarm thresholds automatically by using enhanced fast-time simulation techniques is introduced and discussed

Time‐Varying Risk Measurement for Ship Collision Prevention

“…Specifically, this approach is to summarize the observed data into the values of several variables, and then it uses expert judgment based on the experience (Ahn, Rhee, & You, 2012;Lopez-Santander & Lawry, 2016) and navigation rules Lopez-Santander & Lawry, 2016) to combine these value into a single assessment of the collision risk. The collision alarm is then triggered by comparison of the risk level with a certain threshold that also relies on expert judgments (Baldauf, Benedict, Fischer, Motz, & Schröder-Hinrichs, 2011;Hilgert & Baldauf, 1997). In a word, the measured collision risk represents the degree of experts' belief on the occurrence of the collisions.…”

A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian Networks

“…Collision is the major type of accidents in maritime transportation due to the high probability of occurrence 18 and this type of accidents has attracted much attention in recent decades. [19][20][21] Mou et al 22 proposed an improved SAMSON model by considering the characteristics of collision avoidance to analyse the dynamic collision risk in Rotterdam Port. Qu et al 23 used several indexes including speed dispersion, degree of acceleration and deceleration, and the number of fuzzy ship domain overlaps to analyse the collision risk in the Singapore Strait.…”

Early warning system for potential train collisions: Enhancing safety levels of high-speed trains

“…TCEWS shows an ability to improve train-toground cooperation and to take full advantage of existing railway components. Table 3 shows a comparison of TCEWS with the Traffic Collision Avoidance System, 24 the Automatic Radar Plotting Aid, 25,26 and the Collision Avoidance Support System. 27 From a different perspective, in Table 4 the TCEWS is also compared with existing railway collision avoidance systems all over the world, including the Railway Collision Avoidance System, the Shinkansen Maintenance Work Safety System, and the Anti-Collision Device Network.…”