Automated vehicle (AV) minibuses, i.e., AV shuttles, are gaining popularity in the testing of new types of transportation services in real traffic conditions. AV shuttles have moved from closed test areas to low-traffic public sites such as local residential areas, technology parks, university campuses, etc. These types of vehicles are usually low-speed and rely on a lidar-camera sensor set and a self-driving software stack. These new use cases are increasing these systems’ safety demands. In addition to functional safety, many other aspects need to be considered. In this study, a risk analysis model is developed, combining the fuzzy analytical hierarchy process and the Technique for Order of Preference by Similarity to Ideal Solution method. The proposed model is utilized to prioritize risks corresponding to the particular case study, based on real AV shuttle bus development, and focuses on the low-level hardware/software safety issues and improvements.
Self-driving vehicles and mobile robots are used more and more in public transportation and industrial companies. Multiple experimental platforms, which can be operated in an urban or industrial environment have been developed recently. The key development for robust and safe control of the robot’s operation is relying on the low-level cyber-physical system (CPS). CPS is composed of a collection of tightly integrated computational (cyber) units which are communicating with the physical world. CPS integrates computation and communication aspects with control and monitoring techniques. In this paper, the scientific goals underscore the analysis of the existing state of the art solutions to increase security, safety, and reliability of the multiple experimental platforms.
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