A New Method of Analysing Situational Awareness in an Urban Environment.

Situational awareness is the understanding of existing conditions that humans possess. This understanding is vital in making the correct decisions or responses to an event. Improving the design of systems to enable better situational awareness will result in improvements to both performance and safety. However, to create a better system it is necessary to initially measure current performance and subsequently the effect of changes to the system. Most previous work has focused on the measurement of situational awareness gained from instrumentation whereas the objective of this research has been to find a method of measuring observation-based situational awareness of momentary events in urban environment. This research has developed a new methodology to measure the vision-derived aspects of human situational awareness by focusing on the environment. To accomplish this, situational awareness was considered to be a spherical bubble, and everything within the environment occupying an area on the bubble of awareness. The new approach was tested experimentally by generating a simulated urban environment, created using a serious games technology, and measuring the situational awareness of 36 volunteers, who carried out a situation awareness task in the simulated environment. The effectiveness of the new method was evaluated against the performance of two existing methods of measuring situational awareness. It was found that the new methodology successfully measures the volunteers’ situational awareness of events in the simulated urban environment. From this it was possible to compare their performance against ideal performance. Using this methodology it will be possible to explore new system designs which will maximise the contribution of situational awareness of humans’ operating systems. This is important in circumstances where humans must be visually aware of their surroundings, such as when controlling vehicles, using indirect vision systems, or remotely operating robots