Vehicle safety depends on (a) the range of identified hazards and (b) the operational situations for which mitigations of these hazards are acceptably decreasing risk. Moreover, with an increasing degree of autonomy, risk ownership is likely to increase for vendors towards regulatory certification. Hence, highly automated vehicles have to be equipped with verified controllers capable of reliably identifying and mitigating hazards in all possible operational situations. To this end, available methods for the design and verification of automated vehicle controllers have to be supported by models for hazard analysis and mitigation.
Babin et al. @cite_13 propose a system reconfiguration approach developed with the Event-B method in a correct-by-construction fashion using a behavior pattern similar to our approach (particularly, fig:statemodel ). Reconfiguration as one way to faults is discussed in this work. Wardzi ' n ski @cite_1 discusses hazard identification and mitigation for autonomous vehicles by predetermined risk assessment ( with safety barriers) and dynamic risk assessment. For both, he provides argumentation patterns for creating AV safety cases. In addition to his work, the abstraction and the method we propose covers both paradigms in one framework. We provide formal notions of all core concepts.
@cite_1 @cite_13
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Assuring safety of autonomous vehicles requires that the vehicle control system can perceive the situation in the environment and react to actions of other entities. One approach to vehicle safety assurance is based on the assumption that hazardous sequences of events should be identified during hazard analysis and then some means of hazard avoidance and mitigation, like barriers, should be designed and implemented. Another approach is to design a system which is able to dynamically examine the risk associated with possible actions and then select the safest action to carry it out. Dynamic risk assessment requires maintaining the situation awareness and prediction of possible future situations. We analyse how these two approaches can be applied for autonomous vehicles and what strategies can be used for safety argumentation. Traffic lights used in transportation road networks have not undergone much technological advancement since their first installation in the early 1890's. The use of traffic lights still pose limitations, including very high operation and maintenance costs and limited adaptability to live traffic conditions. Virtual Traffic Lights (VTL) is a relatively novel concept based primarily on vehicle-to-vehicle communication and thus allowing removing costly traffic light installations. However, not much research has been done on the safety of these systems. This paper objective is to conduct a preliminary safety analysis of a VTL system and provide mitigation strategies for the highest safety threats. The VTL hazards identification, risk assessment, and proposed mitigation measures in this research, albeit incomplete, provide a working template for future research, development expansion and reasonable arguments for VTL system implementation.