1. An enhanced vehicle control model for assessing highly automated driving safety
- Author
-
John McDermid, Helen Monkhouse, and Ibrahim Habli
- Subjects
Hazard (logic) ,021110 strategic, defence & security studies ,021103 operations research ,business.industry ,Computer science ,media_common.quotation_subject ,Control (management) ,0211 other engineering and technologies ,Automotive industry ,Advanced driver assistance systems ,02 engineering and technology ,Automation ,Industrial and Manufacturing Engineering ,Task (project management) ,Controllability ,Risk analysis (engineering) ,Conceptual model ,Safety, Risk, Reliability and Quality ,business ,media_common - Abstract
Automation has been changing the types and causes of hazards, and influencing the way in which users interact with complex systems, particularly challenging the notion of human control as a primary basis for hazard mitigation. In this paper, we explore this challenge and use an automotive driving example to examine the distributed nature of the driving task. We define an Enhanced Vehicle Control Model (VCM) that extends the notion of controllability and joint cognition for highly automated tasks. We apply the model to three contemporary driver assistance systems by undertaking a scenario-based evaluation. As a conceptual model, the Enhanced VCM shows potential to proactively identify the hazard causes associated with a joint cognitive control. However, to provide utility and to become an effective tool for the system analyst, an accompanying methodology is needed. This is the focus of our ongoing research.
- Published
- 2020